{"data":{"items":[{"id":"a971436b-b2bc-4811-9c02-f6ecd266bd4d","excerpt":"Amazon, Microsoft, and Google Are Systematically Acquiring the AI Industry at Near Zero Cost — **Three things before we start:**\n\n1. **All ideas, arguments, and thesis are my own.** I've used Claude for research, sourcing, and condensing the writing, but the analysis is mine.\n2. **This goes against current major media ","url":"https://www.reddit.com/r/stocks/comments/1rdiinm/amazon_microsoft_and_google_are_systematically/","role":"pricing","weight":1.4598088,"occurredAt":"2026-02-24T15:01:20.000Z","sourceKey":"reddit","sourceName":"Reddit","credibility":0.62,"venue":"stocks","intent":"pricing_complaint","painScore":0.72588235,"sentiment":-0.7647059,"confidence":0.84583336,"matchedPatterns":["too_expensive","missing_feature"],"statement":"AI startup needs $1 billion to train models (can't afford it) 2.","title":"Amazon, Microsoft, and Google Are Systematically Acquiring the AI Industry at Near Zero Cost","body":"**Three things before we start:**\n\n1. **All ideas, arguments, and thesis are my own.** I've used Claude for research, sourcing, and condensing the writing, but the analysis is mine.\n2. **This goes against current major media narratives.** I expect hate. But a few of you will get it.\n3. **For those wanting to say \"this is just circular financing like Cisco\"** \\- jump to Part 3 where I demolish that argument.\n\n\n\n\n\n# PART 1: THE THESIS\n\nAmazon, Microsoft, and Google aren't making risky AI investments. They're **systematically extracting equity from every serious AI company while getting their money back through infrastructure fees.**\n\n**Here's how it works:**\n\n1. AI startup needs $1 billion to train models (can't afford it)\n2. Amazon \"invests\" $1 billion for equity stake\n3. Startup immediately pays $1 billion back to Amazon for AWS cloud services\n4. Amazon gets its money back, keeps the equity forever\n\n**Cost basis: Zero.**\n\nRinse and repeat across every AI company that wants to scale.\n\n**The result:**\n\n* Amazon, Microsoft, Google collectively own 34-45% of every major AI company\n* They get all their invested capital back through infrastructure fees\n* They're building a portfolio of ownership across the entire industry\n\n**This isn't about picking winners. They own pieces of everyone.**\n\n# Why This Won't Be Regulated\n\nEach company takes minority stakes to avoid majority control scrutiny. They can all claim they're \"competing\" with each other.\n\nTo actually stop this, regulators would need to take all three companies to court together and prove coordinated behavior. That's unprecedented.\n\nBy the time regulators figure this out (5-10 years), the value has already been extracted. The equity stakes are locked in. The infrastructure dependencies are embedded.\n\n\n\n\n\n# PART 2: THE ANTHROPIC PROOF\n\nLet me show you this isn't theory. Here are the actual numbers from Anthropic (current valuation: $380 billion):\n\n**Who owns it:**\n\n* Amazon: 15-21% (worth $57-79.8 billion)\n* Google: 14% (worth $53.2 billion)\n* Microsoft: \\~5-10% (worth $19-38 billion)\n* **Total hyperscaler ownership: 34-45%**\n\n**What they paid:**\n\n* Amazon: $8 billion\n* Google: $3.75 billion\n* Microsoft: $10-15 billion\n* **Total invested: \\~$25 billion**\n\n**What they're getting back in infrastructure fees:**\n\n* Anthropic committed to spend $75-105+ billion on AWS, GCP, and Azure\n* Amazon getting $5+ billion/year (gets investment back in <2 years)\n* Google getting $10-15 billion/year (gets investment back in months)\n\n**The extraction:**\n\n* Invested: $25 billion\n* Getting back in fees: $75-105 billion\n* Keeping in equity: $129-171 billion\n* **Total value extracted: $204-276 billion from a single company**\n\n**And this same pattern is happening with:**\n\n* OpenAI (Microsoft owns \\~27%)\n* Every other AI startup at scale\n\n\n\n\n\n# PART 3: WHY \"CIRCULAR FINANCING\" COMPLETELY MISSES THE POINT\n\n**I know what you're thinking:** \"This is just like Cisco in the 1990s doing vendor financing.\"\n\n**Wrong. Here's why:**\n\n# Cisco Gave Loans. The Hyperscalers Buy Equity.\n\n**Cisco (1990s):**\n\n* Extended credit/loans to buy equipment\n* Held debt (IOUs) - companies owed them money\n* Got ZERO equity. No stock. No ownership.\n* Dot-com burst → Companies defaulted → Cisco lost billions\n* Stock dropped 86%\n\n**Amazon/Microsoft/Google (now):**\n\n* BUY EQUITY STAKES - become shareholders (15-49% ownership)\n* Get money back through infrastructure fees\n* KEEP the stock forever\n* If AI company fails: Already got money back, equity was free\n* If AI company succeeds: Got money back + own billions in stock\n\n**Cisco was a creditor. Hyperscalers are shareholders.**\n\nCompletely different financial instruments. Completely different outcomes.\n\n# Cisco Lent to the Wrong Companies\n\n**Cisco financed:**\n\n* Telecom companies, ISPs, fiber optic builders (WorldCom, Global Crossing)\n* Infrastructure builders, not platform winners\n\n**Cisco got ZERO equity in:**\n\n* Google, Amazon, Facebook, eBay, Netflix\n* The actual winners of the internet\n\n**Amazon/Microsoft/Google own:**\n\n* Anthropic (could replace Google Search)\n* OpenAI (could replace Microsoft Office)\n* Every AI startup that could disrupt them\n\n**The potential disruptors are owned by the incumbents.**\n\n# The Internet Was Cheap. AI Is Expensive.\n\n**Starting a web company (1990s):** $50,000-$100,000\n\n* Google started in a garage\n* Facebook in a dorm room\n* Infrastructure costs were negligible\n\n**Building frontier AI (now):** $100M-$1B to train, $5-15B/year to run\n\n* Cannot build in a garage\n* No cheap alternative at scale\n* Only 3 companies can provide infrastructure\n\n**When infrastructure cost $50K, Cisco couldn't extract equity.**\n\n**When infrastructure costs $5 billion/year, hyperscalers extract whatever they want.**\n\n**The cost barrier IS the control mechanism.**\n\n\n\n\n\n**QUICK NOTE ON THE CHINA THREAT:**\n\n**People ask: \"What about China/DeepSeek commoditizing AI?\"**\n\n* **US government won't allow Chinese AI into American market - national security threat, regulatory barriers (see: TikTok)**\n* **No Western company will store data on Chinese cloud - espionage risk, compliance issues, trust deficit**\n* **China's AI-capable data centers are 1/8th the size of US infrastructure - and the gap is widening ($98B vs $385B annual spending)**\n* **DeepSeek's efficiency gains are overstated - claimed $294K training, actual cost \\~$6M+ when including base model, total infrastructure $500M-$1.3B**\n* **Efficiency doesn't eliminate infrastructure dependency - even cheaper training still requires massive deployment infrastructure controlled by AWS/Azure/GCP**\n\n**Full China analysis coming to my Substack next week.**\n\n\n\n\n\n# THE BOTTOM LINE\n\nThis isn't the dot-com bubble. This isn't Cisco 2.0.\n\n**This is Standard Oil's playbook perfected:**\n\n* Control the infrastructure (cloud compute instead of pipelines)\n* Extract equity from everyone who needs it\n* Get your money back through fees\n* Own the future at zero cost\n\nExcept better than Standard Oil because:\n\n* Three companies = oligopoly (harder to regulate than one monopoly)\n* Minority stakes (avoid majority ownership scrutiny)\n* Zero risk (capital returned through fees)\n\n**Amazon, Microsoft, and Google will collectively own 40-60% of every major AI company while having recovered their entire investment.**\n\nThey don't need to pick which AI company wins. They already own pieces of all of them.\n\n\n\n\n\n**I've documented all of this with detailed sources and data. Happy to share if anyone wants them. DM me or check my profile for my substack.**\n\n**For those who think I'm wrong - tell me why. But engage with the actual argument, not lazy \"circular financing\" dismissals.**\n\n**What am I missing? Tell me where this thesis breaks down.**\n\n","offTopic":true},{"id":"b271336c-2a90-4aaa-b5ba-1e09b9e1bf81","excerpt":"IGV just hit its longest losing streak since 2001. This software dump makes absolutely zero sense considering what we know as of today. — The software sector is bleeding out in a way we literally haven't seen in 25 years. The IGV software ETF just booked an 8-day straight losing streak. Its longest since its inception ","url":"https://www.reddit.com/r/StockMarket/comments/1u3vdwf/igv_just_hit_its_longest_losing_streak_since_2001/","role":"pain","weight":1.3978482,"occurredAt":"2026-06-12T13:31:54.000Z","sourceKey":"reddit","sourceName":"Reddit","credibility":0.62,"venue":"StockMarket","intent":"feature_request","painScore":0.6967284,"sentiment":-0.654321,"confidence":0.82384914,"matchedPatterns":["terrible","missing_feature"],"statement":"|**Metric**|**Premium \"AI Bottleneck\" Hype Stocks**|**Liquidated Public SaaS Basket**| |:-|:-|:-| |**Valuation Multiples**|Priced for perfection; factoring in a flawless decade of execution.|Compressed down to historical multi-year lows.|…","title":"IGV just hit its longest losing streak since 2001. This software dump makes absolutely zero sense considering what we know as of today.","body":"The software sector is bleeding out in a way we literally haven't seen in 25 years. The IGV software ETF just booked an 8-day straight losing streak. Its longest since its inception back in 2001. Wiping out nearly 20% from its peak in just over a week. This isn't a normal market correction or a healthy re-rating. This is an aggressive, programmatic liquidity flush that has completely detached from how these businesses are actually performing. \n\nI mean just look at mega-caps like Microsoft and Meta. They are trading like highly volatile meme coins right now, shedding almost 20% of their market caps in under two weeks on absolutely zero bad news. It makes zero sense, and it shows how broken the current market mechanics are. \n\nWhen you actually look at the actual data you can quite easily find out that the main bear arguments fall apart by looking at the actual filings for majority of these SaaS companies. \n\n1. The \"AI is going to kill SaaS\" bear case is flatlining in the data\n\nFor the past year, the biggest bear argument has been that generative AI, custom models, and autonomous software agents will destroy traditional seat-based software and trash vendor margins.\n\nThe problem? That theory isn't showing up anywhere in the earnings reports.\n\n* **The Organic Growth Reality:** Organic growth hasn't disappeared. Top software companies are still holding Net Revenue Retention (NRR) rates between 110% and 118%+. If your NRR is over 110%, it means your existing enterprise customers are spending more money with you year-over-year, before you even add a single new customer logo.\n\n\n\n* **AI is Making Deals Bigger:** AI is actually acting as an expansion tool, not a killer. Companies aren't mass-canceling their enterprise software; they're paying premiums to get native AI features, custom workflow add-ons, and new automated modules integrated into what they already use.\n\n\n\n* **The Valuation Disconnect:** Just three weeks ago, software finally started to bottom out after a brutal 10-month lag behind the rest of tech. We saw beaten-down names rip 30% to 50% in a couple of weeks, which made complete sense given their strong top-line growth, steady churn, and solid operating margins. Now, that entire fundamental floor has been wiped out in days for absolutely no operational reason.\n\n# 2. Software has become the market's ultimate liquidity ATM\n\nThe price action this past week shows how broken the fund flows are. Software is seeing massive distribution volume even on green-candle, net-buyer tape. It's basically being treated as a cash donor pool for everything else.\n\n* **Downside Amplification:** When the Nasdaq pulled back a standard 7% and the S&P 500 dipped 5% this past week, high-quality software names didn't just follow. They got absolutely assassinated for 20% to 30% drawdowns even after having had massive drawdowns whilst overvalued tech that had already gone up 100-200% this year dropped a laughable 15-20% in the same time period\n\n\n\n* **The Disconnect in Action:** The absolute absurdity of this was on full display yesterday. After the news hit that Trump canceled the planned airstrikes, the indices staged a massive 1.5% to 3.5% risk-on rally. Semiconductors logged their best day since April 2025. Meanwhile, the software basket finished red, above their lows but meaningfully underperfoming a rally of such magnitude. When the market panics, software crashes. When the market rips, software gets left behind. This all doesn't make any sense. It has been become very clear that fundamentals mean less and less for each year now. Most stocks seem to be just about hype, momentum and narrative. There can be companies delivering earnings that disprove the bear cases people have that still get punished ridiculously by Wall Street and retail investors. The average person in the stock market has little knowledge and many buy on hype and momentum. Which makes it impossible for a hated sector like the SaaS names to get any respectfull price action.\n\n\n\n* **Where the Cash is Flying:** Capital isn't leaving tech because the sector is broken. It's being forcefully dragged out of highly profitable, cash-flowing software names to fund crowded momentum trades elsewhere. Institutional desks are aggressively raising cash for massive block allocations. Like the heavily oversubscribed SpaceX IPO or just chasing the semiconductor train. Software is literally the ATM funding the rest of tech right now. Its genuinley mind blowing how illogical and irrational this is by the market. You can hardly find a more irrational period for a single sector in the past few decades.\n\n# 3. Hype vs. Hard Free Cash Flow (FCF)\n\nFor the past two years, the market has completely thrown out fundamental analysis to chase raw momentum and hype narratives.\n\n|**Metric**|**Premium \"AI Bottleneck\" Hype Stocks**|**Liquidated Public SaaS Basket**|\n|:-|:-|:-|\n|**Valuation Multiples**|Priced for perfection; factoring in a flawless decade of execution.|Compressed down to historical multi-year lows.|\n|**Profitability & FCF**|Unprofitable or razor-thin margins; incredibly capital-intensive.|Massive FCF yields and pristine 70-80% gross margins.|\n|**Growth Profiles**|Driven by non-recurring hardware infrastructure buildouts.|High-visibility, highly predictable recurring subscription revenue.|\n\nThe market is aggressively punishing software companies that are delivering accelerating top-line growth at their fastest sequential pace in years, while simultaneously rewarding speculative infrastructure plays that lack any structural moat or recurring free cash flow visibility. A lot of these hype growth companies are receving valuation premiums that won't reflect in the actual business before in 3-5 years time. Companies with little growth or practically no revenue getting multi ten billion dollar market caps because some influencer call and preaches about it being a \"bottleneck\".\n\n# 4. The brutal toll of the opportunity cost\n\nFor long-term investors holding high-conviction software portfolios, this environment has introduced a painful amount of opportunity cost. Buying the dip over the past 8 months has repeatedly dried up my capital, because algorithmic selling just keeps digging new floors. There has been so many rounds of \"SaaS apocalypse\" and so many dips in the past half a yeat that it is starting to become laughable. It sinks and sinks lower. Companies that used to get premium valuations now trading at 8-12x forward earnings for the upcoming year. It doesn't matter if they triple beat, raise or beat on every single metric. They still collapse 10-20% after earnings. I mean what can the average person even ask for anymore. Maybe I should just buy overvalued tech companies with no justification for their current values and become rich. The amount of shitcos that have probably retired people on pure memes is mind blowing. \n\nIt is incredibly draining to watch highly profitable business models with clean balance sheets get obliterated day after day while speculative momentum names run completely unchecked. But history has proven that the market cannot remain completely detached from corporate cash flows forever.\n\n# The sentiment is just too broken to last\n\nWhen a sector becomes this universally hated. Where a company can post a flawless, triple-beat quarter and still catch an automatic 4% selloff. It signals close to some sort of peak capitulation. The volume the Igv software index and these individual names have received for the past six months has to be getting close to some kind of bottom. The volume has been 3-5x the average monthly volume than all of the years and decades before.\n\nEnterprise software is in my opinion currently the most fundamentally mispriced asset class of the decade. For those holding long-term allocations in businesses with real net expansion, strong competitive moats, and structural cash flows, the actual business thesis hasn't changed. The market is currently being driven entirely by narrative and short-term liquidity constraints. But eventually, the math should win. This seems to be a fitting quote for the current situation. \"In the short run, the market is a voting machine but in the long run, it is a weighing machine.\" - **Benjamin Graham**\n\nWhat are your general thoughts regarding this topic? Are you completely stepping away from the software dip, or are you continuing to accumulate these heavily compressed cash flows despite the absolutely broken tape? I will keep adding to and averaging down on some of these software companies that I mean are undervalued and quite cheap frankly.","offTopic":true},{"id":"267b0d82-7ba2-44af-aa54-9e1eab9d5243","excerpt":"OpenAI’s 200m paying user goal by 2030 is delusional. Here is the bear case nobody talks about. — Saw the news that OpenAI expects to hit 220 million paying users by 2030. That is roughly 14x their current subscriber count.\n\nI have been crunching the numbers and looking at the competitive landscape since the Gemini 3.0","url":"https://www.reddit.com/r/stocks/comments/1p7ye30/openais_200m_paying_user_goal_by_2030_is/","role":"demand","weight":1.337875,"occurredAt":"2025-11-27T09:53:12.000Z","sourceKey":"reddit","sourceName":"Reddit","credibility":0.62,"venue":"stocks","intent":"alternative_search","painScore":0.39,"sentiment":0.33333334,"confidence":0.9625,"matchedPatterns":["terrible","switching_from","paying_monthly","missing_feature"],"statement":"Switching from ChatGPT to Gemini 3.0 took me 30 seconds.","title":"OpenAI’s 200m paying user goal by 2030 is delusional. Here is the bear case nobody talks about.","body":"Saw the news that OpenAI expects to hit 220 million paying users by 2030. That is roughly 14x their current subscriber count.\n\nI have been crunching the numbers and looking at the competitive landscape since the Gemini 3.0 / Claude Opus 4.5 releases, and honestly? The math is broken.\n\nThere is a massive bias in this sub and on Reddit in general. We are the power users. We are the ones digging into specific use cases or coding workflows. But we are a tiny bubble. The vast majority of OpenAI’s 800M+ weekly active users are free-tier casuals who use it to write a birthday email or summarize a PDF. They have zero loyalty because \"good enough\" is all they need.\n\nHere is my analysis why the fundamentals won't support the valuation:\n\n1. The \"Amazon\" comparison is lazy\nPeople keep saying \"Amazon wasn't profitable for 20 years\" to justify OpenAI burning billions. It is a bad comparison. Amazon spent money building warehouses, logistics networks, and eventually their own data centers. They were building assets they owned. The spend was on Capex.\nOpenAI is spending billions on Opex. They are renting compute from Microsoft and Oracle. Look at the numbers: they have a $300 Billion commitment to Oracle and over $22 Billion committed to CoreWeave. They do not own the infrastructure. They are renting the penthouse. If Amazon stopped spending, they still had a massive delivery network. If OpenAI stops spending, the server lights go out immediately.\n\n2. Startup 101: Validate, Dominate, then Expand\nNormally, to become a platform, you dominate one vertical first. Amazon dominated books. Google dominated search. Once you have the cash flow and the users, you expand.\nOpenAI is trying to skip the \"dominate\" phase. They are throwing spaghetti at the wall. Search, Voice, Canvas, Sora, Shopping. They are trying to disrupt markets without validating the demand first. Meanwhile, they are losing the one vertical they actually had. Recent data suggests Anthropic has already flipped the enterprise API market, taking a 30%+ share while OpenAI slides down to 25% because developers prefer Claude for coding.\n\n3. The Google Trap\nMost users are on the free plan. What happens if OpenAI forces them to pay? They leave. What happens if they flood the chat with ads to monetize the free users? They leave.\nGoogle knows this. They are likely just waiting for OpenAI to break the user experience to capture the churn. The \"Gemini for Students\" move was genius because it gets users hooked on the ecosystem (Docs/Drive) for free. (600 Mio Gemini users! App, not including search! Probably highly overlapping with OpenAI's userbase). When OpenAI puts up a wall, Google will be there with open arms to capture the 98% of users who won't pay $20/month.\n\n4. The AGI Hype vs. Reality\nWe need to be real about the tech. Transformers are just huge attention networks creating probabilistic links between words. They are non-deterministic. They do not \"think\" or understand physics.\nYou cannot build a safe AGI on a system that is fundamentally a randomizer. This is why the experts are leaving. Ilya Sutskever left to start SSI. John Schulman left. Yann LeCunn left Meta. In late 2025 alone, over 20 top researchers left OpenAI and Google to work on \"World Models\" because they know Transformers have hit a ceiling.\nAlso, do not fall for the CEO marketing trap. When Sam Altman says \"I am afraid this tech will destroy us,\" that is just hype generation. Danger implies capability. It is the best way to mask the fact that the models are plateauing.\n\n5. The Financials are a Horror Show\nLet’s look at the actual 2025 numbers that have leaked.\nFor the first half of 2025, they generated about $4.3 Billion in revenue. Sounds good? Not when you see the burn.\nReports suggest they lost nearly $13.5 Billion in the same period.\nEven worse, Microsoft’s earnings leaks implied OpenAI lost another $12 Billion just in Q3 2025.\nThey are burning cash faster than they can print it. The \"circular financing\" loop (Nvidia invests -> OpenAI buys chips -> Nvidia books revenue) is the only thing propping up the narrative. When you are losing $3 for every $1 you make, you are not a platform. You are a subsidy machine for Microsoft's cloud division.\n\nAnd if the circular revenue doesn't scare you, look at the employee compensation timebomb. OpenAI doesn't give normal stock; they give PPUs (Profit Participation Units). Because of their capped-profit structure, these aren't ownership stakes, but moreover promises of future profit distributions. As the valuation skyrockets to ~$500B, the accounting value of these \"promises\" explodes. On a balance sheet, this scales like a massive liability. If they ever want to IPO or convert to a standard Public Benefit Corporation (which they are desperately trying to do right now/are in proceeds to do), they have to convert these PPUs. That conversion would trigger a compensation expense so large it would likely wipe out their \"paper\" profits for the next decade. They are effectively borrowing against their own hype to pay their staff.\n\n6. Zero Moat\nPeople argue that \"Chat History\" is a moat. It isn't. I exported my ChatGPT history to JSON and imported it into a local client in 5 minutes. Switching from ChatGPT to Gemini 3.0 took me 30 seconds.\n\nConclusion\nI have to end with a question. The people running OpenAI are YC alums and some of the smartest minds in tech. They know how startups work. They know you need to validate problems and dominate verticals. Yet everything they are doing screams the exact opposite.\nAre they just bad at productizing, where overhelmed by the hype of LLMs themself and strategically not prepared or is there some 4D chess strategy here that I am completely missing? Because from where I am standing, they look less like Google and more like Uber in 2015.","offTopic":true},{"id":"8fe6193e-e82f-4d94-9b66-1f46a3c0c5f3","excerpt":"Where are we in the AI bull market? — Pre-reading Notice: All information in this article is intended solely as a research reference for users and does not constitute any investment advice or basis for trading. All investment decisions are made by the user at their own discretion and entirely at their own risk. Investm","url":"https://www.reddit.com/r/Trading/comments/1uuxphf/where_are_we_in_the_ai_bull_market/","role":"pricing","weight":1.3022639,"occurredAt":"2026-07-13T01:31:13.000Z","sourceKey":"reddit","sourceName":"Reddit","credibility":0.62,"venue":"Trading","intent":"pricing_complaint","painScore":0.69750303,"sentiment":-0.59090906,"confidence":0.7671644,"matchedPatterns":["doesnt_work","too_expensive","product:anthropic"],"statement":"However, as models get larger and training costs soar, it's highly probable that we will hit a ceiling not on model capabilities, but on affordability (it just gets too expensive).","title":"Where are we in the AI bull market?","body":"Pre-reading Notice: All information in this article is intended solely as a research reference for users and does not constitute any investment advice or basis for trading. All investment decisions are made by the user at their own discretion and entirely at their own risk. Investment carries risks; proceed with caution when entering the market.\n\nJust my 2 cents.\n\nThis current AI bull market, counting from the release of ChatGPT in late 2022, has been rallying for three and a half years. Recently, another round of market correction has begun, and the question on everyone's mind is: How much longer can it rise? Should we buy now or run?\n\nWe have previously discussed the three narrative iterations this cycle has already gone through:\n\n1. \\[Questioning model capabilities\\]: This was subsequently corrected by reasoning and reinforcement learning from human feedback (RLHF) during post-training, sparking a rally in 2024.\n2. \\[Questioning the utility of AI\\]: This was corrected by coding applications, sparking a rally in 2025.\n3. \\[Questioning AI's revenue\\]: This was corrected by the Annual Recurring Revenue (ARR) growth of \"Lobster\" and Company A (Anthropic), sparking a rally in early 2026.\n\nWe are currently in the 4th iteration, where the market is \\[Questioning the ROI of AI Capex\\]. In all likelihood, this won't be falsified by the tech giants' own ROI, but rather diluted by the excellent ARR growth at the model layer. After all, the downstream of Capex is the model layer, at least until the two major AI labs go public and everyone gets to see a few quarters of earnings reports.\n\nWhen I started writing this article over the weekend, I realized that to discuss this comprehensively, I'd have to explain the entire framework (to the best of my ability). This would mean covering the US dollar, US Treasuries, the Japanese Yen carry trade, crude oil, the monetary reform of \"the Fed retreating while banks advance,\" private credit, Korean equities, corporate bonds, US AI stocks, and more. It would mean discussing what the 1980s personal computer revolution and its debt resolution can teach us about this AI cycle; Kevin Warsh's vision of returning to the Greenspan era; how Wall Street's bond vigilantes judge and react to the scale of US debt; the commodity cycles driven by strait tolls and El Niño; the tightrope walk of the Yen and JGB yields; and why, in the AI narrative, AI is genuinely useful while its short-term revenue is mathematically guaranteed to lag behind capital expenditures.\n\nIt is simply too much. So today, we will focus solely on \\[The Comparison Between the AI US Stock Bull Market and the 1995-2001 Dot-Com Bubble\\]. We will also leave any comparisons to 1929 aside for now.\n\nEvery technological bubble has its own distinct shape. This AI cycle has four characteristics that make it completely different from the dot-com bubble:\n\n* **First, the model layer is the application layer.** The core of this cycle is the models. The killer apps are actually ChatGPT, Codex, Sedance, Claude Code, etc. Aside from the model layer, a series of truly grounded, profitable killer apps in the application layer has yet to appear. Enterprise penetration is still very low. You see almost no returns in the first year, maybe some improvement in the second, but even if enterprises adopt it immediately, adjusting the \"relations of production\"—like organizational structures and data flows—takes 5 to 10 years to iterate, and might even cause social friction during that time. This bull market isn't driven by \"how much money AI applications have made,\" but by the expectation that \"AI will make a lot of money in the future.\"\n* **Second, the real bubble is in the primary market.** The most core AI companies, aside from xAI (tucked into SpaceX) and Google, are all unlisted. Therefore, the secondary market we see when we open our trading apps looks \"very healthy\" (99 out of 100 companies in the Nasdaq 100 are profitable in 2025). The bubble hasn't disappeared; it's hiding in off-market venture capital and private credit (on the AI side), and secondary market valuation metrics won't reflect it. This is the biggest difference between this cycle and the year 2000. In 2000, all the garbage companies were publicly traded on the Nasdaq; this time, they are in the private markets.\n* **Third, almost everything you can buy in the secondary market is a \"pick-and-shovel\" seller.** In this gold rush, the ones digging for gold (application companies) are mostly unlisted or not yet making money. The ones that are listed and investable are the ones selling shovels, water, and jeans, such as chips (Nvidia), memory (SK Hynix, Micron), energy (Bloom Energy), and power/cooling (Vertiv). This means the current secondary market rally is essentially a \"suppliers of the arms race\" rally, not an \"application monetization\" rally. Whoever supplies this race goes up; once the race slows down, the suppliers are the first to take the hit.\n* **Fourth, the ones footing the bill right now are the tech giants.** Currently, the main buyers of shovels are the major tech behemoths. Thus, the financial cycle flows upstream starting from AI Capex, rather than starting downstream from model layer revenue or application revenue. At a certain point (like now), the giants funding this and the suppliers receiving the funds will form a seesaw relationship in the same market. Only when model layer revenue catches up can this deadlock be truly broken.\n\nBut let me pour some cold water on this. We've previously discussed the difference between frontier tokens and commoditized tokens. The mission of frontier tokens is to create new demand, such as new drugs, new discoveries, and new breakthroughs. They must keep running constantly; otherwise, their pricing will suffer an exponential collapse. Anthropic currently enjoys a 70% gross margin on its Opus series simply because it has a 6-month pricing power window. Six months later, when open-source models catch up, the $5/$25 price drops to $1/$3 or even lower, and that gross margin vanishes instantly. However, as models get larger and training costs soar, it's highly probable that we will hit a ceiling not on model capabilities, but on affordability (it just gets too expensive). So, expecting model-layer revenues to plug the massive AI Capex gap in the short term is overly optimistic. You will hear this narrative pushed in marketing, but it won't work in reality.\n\n**Where Are We in the Bull Market?**\n\nWe've actually discussed this in previous articles, and the conclusion remains the same: we are at a position where the first wave of the tail-end rally has finished, and the second wave has yet to begin.\n\nAI is real, but the AI bill is also real. So the core question is: who is going to pay the bill for this AI technology? The current US stock market is neither the starting point of a healthy bull market nor a post-bubble collapse; it is a tail-end rally dominated by AI Capex. The most accurate description is strong but fragile.\n\nThe ideal state for the current adjustment is to force out the Federal Reserve's backstop via a significant pullback, buying more time and capital for the AI narrative and the subsequent IPOs of the two major labs. This would last until depreciation accounting begins to bite, semiconductor supplies are no longer severely short, frontier model growth slows, and enterprise AI adoption enters the deep waters of \"relations of production\" and noticeably decelerates. Then, similar to 2000, the stocks of the two major labs will lead the final sprint.\n\nAll of the above is a fantasized script; no one knows what will happen tomorrow.\n\nLet's evaluate the current market from 5 perspectives: market performance, valuation, market breadth, leverage, and capital expenditure.\n\n**1. Market Performance**\n\nDuring the 1994–2000 dot-com bubble, pullbacks in '96, '97, and '98 were quite frequent. Basically, there was a 10%-20% correction every 6-9 months, very similar to the AI bull market since 2022. We saw frequent pullbacks in '23, '24, '25, and early '26 because people harbored all sorts of doubts, they didn't believe in this technological revolution. However, during 1999-2000, there was only one correction, because by then, basically everyone believed.\n\nWhy did they believe back then? User numbers had exploded consecutively for 5 years; early skeptics had been proven wrong for 3-4 years and left the market; the IPOs of Amazon (1997), Yahoo, and eBay made massive fortunes for the primary market, while consecutive stock market gains did the same for the secondary market; new economic theories were widely accepted (\"this time is different\"). After accumulating for 4 years, it erupted in 1999.\n\nThe current AI narrative stands at this very watershed moment. There are still many voices of doubt in the market. If frontier labs can achieve a \"Nation of Geniuses\" soon and major scenarios beyond coding emerge, then we will be standing on the eve of 1999. You will hear arguments that \"this time is different,\" that AI revenues can cover the costs, and therefore there will never be a bubble.\n\nI remain cautious about whether AI can be deployed rapidly on a massive scale across all industries or achieve massive user adoption. This is for two reasons.\n\n* First, the economies of scale for AI are nowhere near that of the internet (where marginal costs trend toward zero), and it's even trickier than electricity or railways. Its marginal costs are not only high, but they are pushed upward by demand. Furthermore, electronic components aren't like railways or power grids that last for decades; lasting 10 years would be vastly exceeding expectations.\n* The deeper issue is the uncertainty of AI outputs, which makes standardization and assembly-line processing difficult. The level of difficulty depends on a scenario's \"verification cost.\" Scenarios with cheap verification, like programming, can be standardized and monetized, but that space is almost fully saturated. What's left are scenarios with expensive verification (medical, legal, financial). These are incredibly hard to standardize and require human backstops. Consequently, you can neither cut costs nor fully capture the demographic dividends of scale. The opposites of these two issues (hard to cut costs, hard to standardize) were exactly the foundation for the prosperity of the Industrial Revolution.\n\nTherefore, the old playbook won't work. The core breakthrough of Large Language Models in this cycle is that, for the first time, every individual can receive cognitive support from the entirety of human civilization, democratizing customized services that were previously limited by \"human labor.\" But if this isn't integrated with reality and remains confined to the virtual world, then programming is far and away the most fitting domain.\n\nThe core of the digital world still revolves around content. Mobile phones digitized human behavior for the first time, spawning a slew of new business models. Looking at it strictly from historical parallels, the prototype of an AI assistant needs to combine both content and behavior. AI phones and AI PCs are the narratives the entire industry is pushing right now; we'll see if they become the explosive catalyst that sweeps away the doubts.\n\n**2. Valuation**\n\nMany people argue that the AI leaders you can buy today trade at a fraction of 2000-era valuations, and they are raking in real cash (50% net margins vs. 17%). To be more rigorous, we must compare \"blue-chips to blue-chips,\" not compare Nvidia to the dot-com garbage of that era. High valuations in 2000 were split into two types: garbage .coms with no revenue, only clicks; and highly profitable leaders like Cisco. Comparing Nvidia at 20x to Cisco at 100x is a leader-to-leader comparison, so the conclusion that it is \"much cheaper\" holds up. Furthermore, the fact that \"AI is asset-heavy\" doesn't differentiate this cycle from the dot-com bubble. Telecom/fiber optics back then were ","offTopic":true},{"id":"6ed1ca41-103a-423d-9b63-060fec256d9b","excerpt":"Trump set to shackle US economy to failing AI industry — ![Donald Trump looking tired on Air Force One](https://www.thecanary.co/wp-content/uploads/2026/06/Copy-of-FI-Template-95-720x540.jpg)\n\nAs we reported on 4 June, [the AI bubble is inching ever closer to being popped](https://www.thecanary.co/trending/2026/06/04/a","url":"https://lemmy.world/post/47884322","role":"pricing","weight":1.1342784,"occurredAt":"2026-06-07T19:43:46.206Z","sourceKey":"lemmy","sourceName":"Lemmy","credibility":0.58,"venue":"lemmy.world","intent":"pricing_complaint","painScore":0.6725926,"sentiment":-0.4814815,"confidence":0.67815584,"matchedPatterns":["too_expensive"],"statement":"And this was true even before they started shedding customers for being too expensive.","title":"Trump set to shackle US economy to failing AI industry","body":"![Donald Trump looking tired on Air Force One](https://www.thecanary.co/wp-content/uploads/2026/06/Copy-of-FI-Template-95-720x540.jpg)\n\nAs we reported on 4 June, [the AI bubble is inching ever closer to being popped](https://www.thecanary.co/trending/2026/06/04/ai-costs-skyrocket-spooking-investors/). It may survive another week, however, because US president Donald Trump is talking about bailing out these failing AI companies:\n\n> This is the most dangerous, anti-democratic thing he’s done yet.\n>\n> He’s using the federal government as a backstop to the greatest fraud of all time: the AI bubble, including the absurd IPOs of SpaceX, OpenAI & Anthropic.\n>\n> He will turn a crash into a depression. \n>\n> — Jim Stewartson, Decelerationist ![🇨](https://s.w.org/images/core/emoji/17.0.2/72x72/1f1e8.png)![🇦🇺](https://s.w.org/images/core/emoji/17.0.2/72x72/1f1e6-1f1fa.png)![🇦🇺](https://s.w.org/images/core/emoji/17.0.2/72x72/1f1e6-1f1fa.png)![🇸](https://s.w.org/images/core/emoji/17.0.2/72x72/1f1f8.png) (@jimstewartson) [June 6, 2026](https://x.com/jimstewartson/status/2063283568307237170)\n\nIt’s a move which runs the risk of shackling the US economy to the most expensive deadend in technological history.\n\nTrump — Crash and burn\n----------------------\n\nThe latest issue for companies like OpenAI and Anthropic is that they’ve had to change their business model. These companies are looking to go public, which means they’ll have to give investors a better look at their underlying financials. This was a worry, because said companies have grossly under-charged their customers to try and get them hooked on AI.\n\nSince increasing their prices, however, customers have been forced to analyse the benefits they’re getting from this suddenly expensive technology, and the answer has been ‘*none whatsoever*‘ or *‘we’re not even* *sure*‘.\n\nThis has created a situation in which CEOs have had to compare hard-to-quantify benefits against suddenly astronomical charges:\n\n> NEW: AI consultant reveals a client accidentally spent $500,000,000.00 in a single month after failing to set employee limits on Claude usage.\n>\n> — Polymarket (@Polymarket) [May 28, 2026](https://x.com/Polymarket/status/2060034216906068131)\n\n> NEW: Uber is reportedly capping employee use of AI vibe-coding tools at $1,500 per month after blowing through its AI budget.\n>\n> — Polymarket (@Polymarket) [June 2, 2026](https://x.com/Polymarket/status/2061944771078238299)\n\nClearly, AI CEOs like Sam Altman hoped:\n\n* They could jack up the prices.\n* Businesses would absorb the costs.\n* They’d be able to show investors a path towards mega-profits.\n\nThat didn’t happen, so now they’re having to act like they don’t know what’s going on:\n\n> Sam Altman said AI budgeting has recently become a \"huge issue\" for some companies, something that \"never came up\" earlier this year. \n>\n> — Business Insider (@BusinessInsider) [June 3, 2026](https://x.com/BusinessInsider/status/2062211094450434219)\n\nIf you’re unfamiliar with AI beyond the noise, it’s important to remember that the technology we’re discussing – ‘generative AI’ – has failed to live up to the hype. Billionaire tech bros claimed they were on the verge of creating a digital god, and a compliant and un-curious media obediently repeated this nonsense.\n\n[Statistician Dr Kareem Carr summarised the issues with AI](https://x.com/kareem_carr/status/2062946412120191148):\n\n> It’s not that AI can’t be used to do knowledge work. It’s that it’s wildly unreliable in bizarre and incomprehensible ways. Things you’d never think it could be possible to mess up are the things that it messes up.\n>\n> Like you ask it download some data and do an analysis, and instead it just completely fabricates a fictional dataset for no reason, and gives you results based on that.\n>\n> Fine if you catch it, but potentially career-ending if you don’t.\n>\n> It inserts its own ideas without telling you. It deletes critical paragraphs.\n>\n> These actions would be psychopathic in a colleague, but we’re just supposed to accept it because it’s a machine.\n\nThe path to profitability\n-------------------------\n\nBugs and faults are one thing, but the truly important thing for our business overlords is that this tech isn’t increasing profitability. If anything, it’s achieving the opposite effect:\n\n> 'The free lunch is over. Google says demand has risen sevenfold over the past year. But now the real cost of AI is finally beginning to emerge, and the consequences are cataclysmic' I Writes [@AndrewOrlowski](https://x.com/AndrewOrlowski)\n>\n> 'The AI bubble will burst, and how that will happen is becoming… [pic.twitter.com/B0Ke5iJ86f](https://t.co/B0Ke5iJ86f)\n>\n> — The Telegraph (@Telegraph) [June 1, 2026](https://x.com/Telegraph/status/2061392128572264695)\n\n> Massive output uptick due to agentic AI. Complete flat adoption. [pic.twitter.com/s6ubPsy0SL](https://t.co/s6ubPsy0SL)\n>\n> — Jen Zhu (@jenzhuscott) [June 5, 2026](https://x.com/jenzhuscott/status/2063032701087883647)\n\nCEOs went all-in on AI because it sounded impressive, and the job of a CEO is to sound impressive. The reality is none of these people knew what they were doing, and now that AI is shown to be a curse on profitability, they’re going to drop AI as fast as they can.\n\nAnd now we get to Trump.\n\nSpeaking on Air Force One, [the president said](https://x.com/jimstewartson/status/2063283568307237170):\n\n> There’s a concept out there, there’s so much money, and it’s so big that there are concepts where pieces could be given to the American public, where the American public essentially becomes a partner with the companies.\n\nThere’s certainly been a lot of money invested, [but the AI companies receiving it have failed to turn a profit](https://hbr.org/2025/11/ai-companies-dont-have-a-profitable-business-model-does-that-matter). And this was true even before they started shedding customers for being too expensive.\n\nTrump added:\n\n> There’s something very interesting about it, where it almost becomes a partnership with the American public. We’ll look into that. We are looking. I actually have a meeting scheduled… with all of the companies. And we’re talking about it where the American people can benefit from the success of AI. And by doing that, they’re going to like it better. Which companies? All of them. All the big ones, yeah… They’re all coming to the White House, probably next week.\n\nWe talk about [nationalising key utilities](https://www.thecanary.co/trending/2026/05/24/burnham-slammed-for/) all the time; we don’t talk about nationalising AI, because it’s a novelty technology which is primarily useful for generating images of SpongeBob SquarePants doing crime:\n\n> lol…\n>\n> Someone used AI to make a SpongeBob GTA\n>\n> Childhood just entered chaos mode![😂](https://s.w.org/images/core/emoji/17.0.2/72x72/1f602.png) [pic.twitter.com/e6oALb0Dj6](https://t.co/e6oALb0Dj6)\n>\n> — Jamie Gledhill (@gledhill\\_scales) [May 31, 2026](https://x.com/gledhill_scales/status/2061059532168544474)\n\nBailonomics\n-----------\n\nWhat Trump is proposing isn’t nationalisation; it’s a bailout.\n\nIt’s easy to see why the AI companies would want backing from the US government, given that they’re trying to make themselves look stable in the runup to going public. It’s less easy to see why the US public would want to own shares in an industry which could be worth nothing 12 months from now.\n\nThe thing to bear in mind is that Trump is surrounded by figures who stand to profit from AI going public, including [Elon Musk](https://www.theguardian.com/science/2026/jun/06/spacex-ipo-buy-shares-elon-musk-stock-market-launch-risks) and [David Sacks](https://gizmodo.com/the-leopard-is-eating-david-sackss-face-2000768295). In other words, it looks very much like Trump is going to use the power of the White House to bail out his rich buddies.\n\n*Featured image via [Samuel Corum (Getty Images)](https://www.gettyimages.co.uk/detail/news-photo/president-donald-trump-walks-back-to-speak-with-reporters-news-photo/2279308050?adppopup=true)*\n\nBy [Willem Moore](https://www.thecanary.co/author/willem-moore/)\n\n---\n\n**From [Canary](https://www.thecanary.co/feed) via [This RSS Feed](https://www.thecanary.co/feed).**","offTopic":true},{"id":"9a3559a2-a5fc-4387-8c4b-b158a94a8839","excerpt":" — I'll give this a shot, as I spend my days managing a portfolio exposed to sector rotations on the mid-length timeframe.

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It is not ideal to think in terms of amorphous projections where you sum up every probability. Try and consider at least some path dependence and rea","url":"https://news.ycombinator.com/item?id=45118676","role":"request","weight":0.75706667,"occurredAt":"2025-09-03T17:57:09.000Z","sourceKey":"hackernews","sourceName":"Hacker News","credibility":0.7,"venue":"news","intent":"problem_report","painScore":0.36,"sentiment":0,"confidence":0.5566667,"matchedPatterns":["manual_process"],"statement":"If you have a truly diversified portfolio with rules for systematic rebalancing, you never manually shift to defensive (obviously what I and most advisors would recommend).","title":null,"body":"I'll give this a shot, as I spend my days managing a portfolio exposed to sector rotations on the mid-length timeframe.

______________________________________

It is not ideal to think in terms of amorphous projections where you sum up every probability. Try and consider at least some path dependence and realize that there is a risk distribution.

What you are specifically looking at is the scenario where there is a) an AI bubble in the public markets (remember, much of AI of it is marked numbers in the VC world) and b) the possible scenario where the grey swan gets big enough and the risk of violent unwind is high enough to where you see arguable value in shifting to defensive positioning in a somewhat diversified portfolio.

I'll assume you are weighted heavy to QQQ/NASDAQ in the portfolio. If you have a truly diversified portfolio with rules for systematic rebalancing, you never manually shift to defensive (obviously what I and most advisors would recommend).

The first note is that an "AI bubble" in public markets, assuming there is one, is very much tied to the overall state of high market concentration in the trillion dollar tech names. To see a violent AI bubble unwind, it will almost necessarily involve the "concentration bubble"/Nifty 50 2.0 unwinding as well. That means the AI Bubble narrative in public markets is tied to overall market liquidity just as much as the AI specific factors. The passive complex will put a large continual bid in for NVDA/GOOGL/AMZN/etc even in the case of an AI downturn, which should neutralize the violent unwind scenario unless both impulses turn negative (active money moving out of AI, and passive money pulling out of broad based ETFs entirely).

Of course the relationship above is reflexive, which is to say that NVDA gapping 20% down on earnings may well spur wider outflows (as you personally alluded to when your response would be to "go full defensive in my portfolio"), and vice versa. So what you want to be watching is specifically for signs of this contagion spreading.

If liquidity/flows strongly turns negative, the concentration bubble unwinds, NVDA and co tank, and that likely triggers a sell-off in the AI speculative names and qualifies as an "AI Bubble Burst". Therefore you want to be watching general economic weakness like recession signals, layoffs, etc. Bond yields blowing out will also likely kill the AI bubble, as it's capital intensive. Even with the fortress balance sheets of the hyperscalers, the long end blowing out (it's starting to press into dangerous territory currently) would likely kill a hypothetical "AI Bubble". So watch bond yields (and bond volatility / MOVE index).

More specific areas I would be watching is Hyperscaler Capex projections in earnings calls (watch it like a hawk), and some aspects of the trade war such as global digital services taxes in particular (because profit shocks for hyperscalers will likely result in reduced capex to preserve their earnings targets). I would also be watching competition for NVIDIA in the more grey swan areas, like Huwawei revealing a chip with twice the performance per watt as NVDA chips for half the price, and a surprise software stack that kicks ass (so the low single digit outcome areas regarding Chinese competition particularly, which wouldn't actually be bad for AI, but would likely result in a shock move of money leaving US related AI names on public markets, which would be a repeat of the February to April move we saw earlier this year in response to DeepSeek. Markets have memory.)

So let's sketch out some risks over the next few years. Now we get to the part that usually adds little to no value (making predictions about where markets will go). Hint: nobody can do this broadly. Sometimes one may have specific value-adding strong convictions picked out of the universe of possibilities, but those are the exceptions.

I'll even put a % chance guess since that's what you're looking for, but it adds literally no value.

Bonds blowing out: low/moderate likelihood. 15-20% over the next few years for a major bond event imo, and I'd carry that directly to a 20% chance of an AI unwind.

Heavy economic downturn: moderately likely. 25% or so.

And since the scenarios overlap somewhat (stagflation would involve both, and it's a leading wider risk currently), let's move the risk to 30%. But remember that this is a risk scenario that will involve market cap weighted passive indexes as well, so we're really talking about market downturn risk rather than just the AI Bubble popping concurrently, since the latter is less meaningful in comparison even when we're focusing on portfolios.

Now on to the AI specific scenarios, which would be AI falling out of favor with consumers. I personally put this under 5%, so I have strong conviction this won't be the case. I'm mostly disregarding this risk. Most would probably put it closer to 20%, and some would be 50/50 if they think it's a fad. You will find a wide array of predictions here.

How about tech industry specific shocks like global digital services taxes causing a sharp drop in AI investment from the huge balance sheets driving it all? I think it's fairly unlikely as well, maybe 5-10% or so. I have high certainty that Google and Apple in particular are going to have great cashflow for the next few years. There are some side-lines to watch here though. Ex: the US government itself is strongly fending off digital services taxes in trade negotiations and using a big stick, but if the tariffs are confirmed to be nullified (recent court ruling), and tariffs are unwound, the world may use the opportunity to tax the multinational American tech companies while the US is stunned and weak, so to speak, especially if some of the other lines are playing out like bond yields getting dangerous, which puts pressure on global govs to raise revenue. That's an example of the sort of thinking that is required to really position a portfolio for things like esoteric crashes in specific sectors and have positive expectancy. You have to take into account all of these self-reinforcing feedback loops and get creative/contrarian to some degree, and find out where the market may be underpriced/offer value hedges and hidden synergistic correlations. Or you can pay up for generic tail protection/put options, and just pay the tax to cover the risk. In your case, perhaps that would be a good option? Just pay up for a put spread on NVIDIA that has a 10 to 1 payout ratio, spend 0.5% of your portfolio, and hey, you get a 5% payout in the case of an AI unwind (you don't need to go overboard, a 5% cash payout is a huge gift in a market crash while most are in panic).

On NVIDIA in particular. I do think there's a moderate risk that NVIDIA is in an outright bubble currently. I could easily see a scenario where guidance comes in weak, margins come down for some reason (even something like a string of bad tape-outs at TSMC... could be anything), and NVIDIA re-rates lower. That would be painful for the entire market, and this is the risk I would be paying up to hedge (I'm currently hedging this a bit). I think there's a good 1/3 chance that NVIDIA tanks sometime over the next few years, but half of these scenarios would just be contained to NVIDIA and more to do with margins coming down to earth a bit (wow, this is quite nice just to be able to conjure up BS % numbers like that).

____________________________________

So in closing, just worry about having a properly diversified portfolio that self-rebalances according to proven rules. Ask yourself if there was an AI unwind, how would my portfolio look, and does this aligns with my financial goals and risk tolerance? Also ask yourself what would happen if it further picked up steam, since upside risk/opportunity cost is important as well. As previously mentioned, you are concerned with a scenario that closely correlates to index concentration as well, so also ask yourself how it looks if the current market leaders perform badly, and other sectors/market factors drive performance going forwards.","offTopic":true},{"id":"daeb7264-2c37-450a-8cc5-cf938bb84c40","excerpt":"\"Tokenmaxxing\" - How AI demand is inflated by deliberately wasteful & subsidized usage. At least $6 Billion+ a year in waste — At many large companies, AI usage is tracked, and has become a metric/target to measure employee productivity. In a weak job market for knowledge workers, performance reviews tied to AI usage, ","url":"https://www.reddit.com/r/stocks/comments/1t8b4br/tokenmaxxing_how_ai_demand_is_inflated_by/","role":"demand","weight":1.2527204,"occurredAt":"2026-05-09T17:24:26.000Z","sourceKey":"reddit","sourceName":"Reddit","credibility":0.62,"venue":"stocks","intent":"alternative_search","painScore":0.43031824,"sentiment":-0.2,"confidence":0.87583333,"matchedPatterns":["switching_from","missing_feature"],"statement":"**Much of this wasteful spending has been subsidized:** Up until recently, AI coding tools were provided at a loss, to gain market share: - Copilot is shifting from a subsidized model to usage based billing - Cursor switched from subsidize…","title":"\"Tokenmaxxing\" - How AI demand is inflated by deliberately wasteful & subsidized usage. At least $6 Billion+ a year in waste","body":"At many large companies, AI usage is tracked, and has become a metric/target to measure employee productivity. In a weak job market for knowledge workers, performance reviews tied to AI usage, and frequent mass layoffs, this has led to substantial waste and artificial demand by employees seeking to appear productive. \n\n**Notable examples:**\n\n**Disney/ESPN**:\n\n- Internal dashboard to track AI token usage\n\n- Product and tech staff used 3.1B Claude tokens and 13.3B Cursor tokens over nine workdays, and one Claude power user invoked Claude about 460,600 times, or 51,000+ invocations per workday. Assuming they were working 14 hour work days with no breaks, that's more than one invocation per SECOND. That's not humanly possible without writing a bot to spam requests. \n\nhttps://www.businessinsider.com/how-disney-tech-employees-are-using-ai-claude-cursor-tokens-2026-4\n\n**Meta**\n\n- Goals were set for some employees on AI-tool usage, including AI code assistants and agents; related reports cite team-level targets such as 75% AI-assisted code in some groups.\n\n- There was a leaderboard for employees to compete on token usage. 1 engineer racked up 281 Billion tokens in a single month. To put this into context, according to a survey by Jellyfish, a software engineering intelligence platform, the average developer that uses AI uses 50 million tokens per month, top decile uses 380 Million. So that's 5,000x the median, 900x the typical power user(and that's assuming the top decile aren't token maxxing). https://fortune.com/2026/04/09/meta-killed-employee-ai-token-dashboard/\n\n**Google**\n\nEmployees were told AI usage is a part of their performance reviews. Sales employees were given AI usage quotas to meet. https://www.businessinsider.com/google-employee-ai-adoption-non-technical-software-engineer-performance-review-2026-2\n\n**Microsoft**\n\nBI reports an internal memo saying “using AI is no longer optional,” with managers told to include internal AI tool usage in evaluating performance. https://www.businessinsider.com/microsoft-internal-memo-using-ai-no-longer-optional-github-copilot-2025-6\n\n**KPMG:**\n\n- Employees report an AI usage dashboard that is easy to manipulate, employees are expected to hit 75% usage target for AI tools.\n\n**Estimating the impact to demand**\n\nThe impact of Tokenmaxxing can be difficult to both quantify because there is is a lack of industry-wide data on the practice, only anecdotes and general usage data.\n\nWhat we can do is look at the top decile of developers, and determine to what extent this excess usage provides tangible benefits:\n\n>Jellyfish analyzed 12,000 developers across 200 companies and found median AI-coding usage around 51 million tokens/month, while the 90th percentile used about 380 million tokens/month. It also found that the highest-token developers used roughly 10× as many tokens for only ~2× the throughput, with median developers using about 7 million tokens per PR versus top-decile developers around 69 million tokens per PR.\n\n\"Throughput\" does not necessarily mean productivity. For example, an engineer that does not review AI generated code may miss a bug, resulting in needing to submit a 2nd or 3rd PR to fix the bug, whereas a developer that takes their time to review/test code may achieve better real-world output with less PRs.\n\nAdditionally, \"PRs\" are not a consistent unit of measure, and the survey spans 200 companies. A PR could be to fix a small bug, or it could be to implement a major new feature. Suppose a junior dev has many small PRs for small features & makes heavy use of AI because they're inexperienced and need the help. A senior dev has fewer, more important PRs with major features & uses AI much less. On paper, the junior developer used more tokens and was more productive because they submitted more PRs. But in reality, the senior dev produced more value with less tokens.\n\nRegardless, based on the naive assumption that throughput= productivity, we can model waste as:\n\n>380M actual tokens/month − 102M productive-equivalent tokens/month = ~278M wasted tokens/month\n\nTo be conservative, we can assume that some power users are legitimate. Heavy usage of agentic tools, tasking agents to work on multiple features in parallel, etc. But on the other hand, 380 million tokens is just the 90% percentile. Top users use ridiculous amounts due to lack of limits. One meta user used 281 Billion tokens in a month. That's 900x power users.\n\n**Much of this wasteful spending has been subsidized:**\n\nUp until recently, AI coding tools were provided at a loss, to gain market share:\n\n- Copilot is shifting from a subsidized model to usage based billing \n\n- Cursor switched from subsidized to usage based billing\n\n- Anthropic is requiring API based billing for 3rd party tools and now has strict limits on Claude code.\n\nJellyfish suggested a typical cost of $1 per 1 million tokens, which suggests heavy subsidization. Frontier models cost $2-5 per 1 million input tokens, $15-30 per 1 million output, but input costs may be a bit lower due to prompt caching.\n\nIf we assume the top 10% of users are wasting an average of 276 Million tokens per month at $1 per Million tokens, that suggests $6 Billion a year in waste. \n\nThis is a very conservative estimate due to lack of reliable data on usage by extreme outlier tokenmaxxers. Actual waste is likely much higher, possibly as high as $20 Billion annualized.","offTopic":true},{"id":"6593b83e-b417-4c53-8bac-0ebe759e3a46","excerpt":"Google, you did it... you pulled a Cursor.. Turn around before it is too late.. — **The API Trap: How Google Repeated Cursor's Biggest Mistake**\n\nThere's a pattern playing out in the AI tooling market right now that should concern every independent developer, and it follows a script we've already seen once before.\n\n\n\n*","url":"https://www.reddit.com/r/GoogleAntigravityIDE/comments/1rtak2j/google_you_did_it_you_pulled_a_cursor_turn_around/","role":"pain","weight":1.2083492,"occurredAt":"2026-03-14T05:01:32.000Z","sourceKey":"reddit","sourceName":"Reddit","credibility":0.62,"venue":"GoogleAntigravityIDE","intent":"problem_report","painScore":0.66333336,"sentiment":-0.45833334,"confidence":0.7264624,"matchedPatterns":["frustrating"],"statement":"A developer frustrated with Cursor takes an afternoon to move to Windsurf.","title":"Google, you did it... you pulled a Cursor.. Turn around before it is too late..","body":"**The API Trap: How Google Repeated Cursor's Biggest Mistake**\n\nThere's a pattern playing out in the AI tooling market right now that should concern every independent developer, and it follows a script we've already seen once before.\n\n\n\n**How Cursor Built a Rocket and Then Lit It on Fire**\n\nCursor's rise was genuinely remarkable. Starting from $1M ARR in December 2023, the company scaled to $100M ARR by January 2025 — a run that took just 20 months and made it the fastest B2B SaaS company to that milestone in history. The freemium conversion rate hit 36%, in an industry where 2-5% is standard. Over a million developers. 360,000 paying customers. A valuation that went from $50M to $9.9B in under three years.\n\nThen June 16, 2025 happened.\n\nCursor replaced its straightforward request-based pricing with a \"credit pool\" system. The 500 premium requests users had relied on quietly became \\~225 under the new compute-weighted math. \"Unlimited\" was redefined to mean slower background models. Users were burning through their monthly allocation in three days.\n\nThe community didn't take it as an economic adjustment. They took it as a betrayal. Mass cancellations. Developer forums flooded with anger. The CEO apologized on July 7th and issued refunds — but the brand damage was done. Growth decelerated from doubling every two months to a contested crawl. Web analytics by January 2026 showed stagnation across key markets, and AI-driven referral traffic was already fading.\n\nThe lesson was clear: when you train users to expect unlimited, frictionless access, then pull it without warning, you don't just lose customers. You lose them loudly.\n\n\n\n**Google's Play-by-Play Repeat**\n\nGoogle entered 2024 well behind Anthropic and OpenAI in developer mindshare. The strategy to close the gap was straightforward — subsidize the compute costs and make the Gemini API feel impossibly generous. Let developers build on it. Let workflow dependency form. Give them 1M and 2M token context windows essentially for free.\n\nIt worked. Google went from laggard to market leader.\n\nThen came December 7, 2025.\n\nIn a single unannounced update, Google slashed free-tier quotas across the Gemini Developer API by 50-92% depending on the model. By March 9, 2026, the situation worsened further — flagship Gemini 3 and 3.1 models dropped to 1-2 messages per day for free users. Developers hit walls they never expected, not just from hitting limits, but from persistent 429 RESOURCE\\_EXHAUSTED errors, \"nano banana\" quota drops, and systemic instability across Google AI Studio.\n\nThe pricing architecture pivoted hard toward enterprise. A $19.99/month Google AI Pro plan that was supposed to guarantee access to frontier models started failing for paying subscribers — while non-paying users still saw the Pro toggle in the UI. Support channels responded with basic troubleshooting scripts (clear your cache, try incognito) for what were clearly backend entitlement failures.\n\nIn Kenya, developers paying the equivalent of $29/month for Google Antigravity — the platform's Cursor competitor — were hitting usage caps within hours of starting a session, then waiting up to five days for limits to reset. The platform bundled Whisk, Veo, and NotebookLM into that price. Most developers have no use for any of those.\n\nAnd through all of this, customer support kept describing the new allocations as \"generous.\"\n\n\n\n**The Multimodal Distraction**\n\nSome defenders point to Google's video and imaging APIs as justification for the broader constraints. Veo 3 and Imagen 3 are genuinely impressive technology. But the economics around them in 2026 have been brutal.\n\nVeo 3 Standard costs $0.40 per generation. Image output through Gemini 3 Pro Image Preview runs $120.00 per million tokens. Because Google enforces quotas at the project level rather than per endpoint, generating a single test video with Veo 3 can freeze your parallel text-generation work and wipe out entire project chat histories. A handful of test generations triggers account-wide resource exhaustion.\n\nImpressive models. Unusable pricing structure.\n\n\n\n**The Token Economics Reality**\n\nOn paper, Gemini 3 Pro Preview is the cheaper API. Input tokens run $2.00 per million versus Claude 3.7 Sonnet's $3.00. Context cache writes are nearly 90% cheaper. Using a standard 3:1 input-to-output ratio for software development workloads, Gemini comes out roughly 25% less expensive overall.\n\nThat math hasn't mattered.\n\nClaude 3.7 Sonnet dominates serious coding workloads not because it's cheaper — it isn't — but because it's reliable. Developers routinely report that Gemini's advertised context window delivers degraded reasoning long before hitting its technical limits, while Claude maintains near-perfect recall across its 200K token window. The debugging hours spent on Gemini hallucinations in complex refactoring tasks erase the cost savings. A model that locks you out after one prompt isn't cheaper. It's more expensive in every way that matters to someone billing by the hour.\n\n\n\n**Where Developers Are Going**\n\nThe migration is already underway and it's moving in three directions simultaneously.\n\nCLI-first agents have pulled a significant segment of the developer population away from IDE integrations entirely. Claude Code lets developers use their own Anthropic API keys directly, bypassing third-party markups. Aider does the same with any API key, including discounted models through OpenRouter. RooCode has built its reputation specifically as the fallback for when commercial agents hallucinate on complex architectural changes.\n\nFor those who still want a graphical IDE, Windsurf has become the primary beneficiary of the Cursor and Google backlash. At $15/month individual and $30/month for teams, it undercuts Cursor on pricing while leading on speed — its SWE-1.5 model processes code at 950 tokens per second, reportedly 13x faster than standard Claude Sonnet implementations. It hit $82M ARR by mid-2025 and was subsequently acquired by OpenAI at a $3 billion valuation.\n\nThe most existential threat to the entire cloud API model is local execution. Tools like [or-cli.py](http://or-cli.py) now let developers run LLaMA 3 (70B) or DeepSeek-R1 directly on hardware. With prompt compression tools like Microsoft's LLMLingua, local inference handles around 80% of standard programming tasks at zero per-token cost. When a cloud provider arbitrarily cuts quotas, a developer running open-source locally just updates a config file and keeps working.\n\n\n\n**The Only Moat That Holds**\n\nThe AI tooling market in 2026 has near-zero switching costs. A developer frustrated with Cursor takes an afternoon to move to Windsurf. A developer frustrated with Google's quota changes takes less time than that to pivot to Claude's API or spin up a local model.\n\nIn that environment, the only thing a platform can actually defend is trust — specifically, the trust that the rules won't change overnight without warning, that support will treat you like someone trying to build a real product, and that \"unlimited\" won't be quietly redefined three months after you've built a workflow around it.\n\nCursor demonstrated that even explosive growth and a genuinely useful product can't withstand a single poorly handled pricing pivot. Google has now repeated that mistake at ecosystem scale — hitting the same users with less warning, less transparency, and support scripts that keep calling a 2-message-per-day allocation generous.\n\nThe developers are noticing. The traffic data already shows it. And unlike a PR crisis, broken trust in a zero-switching-cost market doesn't recover from an apology post.","offTopic":true},{"id":"b5abe6fa-94b4-46a5-bfb1-4713ac7e6386","excerpt":"AI bubble, market crash, healthcare and value investing. — I have been seeing a lot of posts on social media and the \"news\" (if we can even call it that anymore) debating whether we're in an AI bubble and whether what we're seeing will be the future. However, for those of us who have been around for the dot com and hou","url":"https://www.reddit.com/r/ValueInvesting/comments/1oyu1hi/ai_bubble_market_crash_healthcare_and_value/","role":"pain","weight":1.1781679,"occurredAt":"2025-11-16T19:03:05.000Z","sourceKey":"reddit","sourceName":"Reddit","credibility":0.62,"venue":"ValueInvesting","intent":"feature_request","painScore":0.5674074,"sentiment":-0.5185185,"confidence":0.75166667,"matchedPatterns":["missing_feature"],"statement":"A market bubble is when asset prices disconnect from real, sustainable economic value because investors chase hype, momentum, and the fear of missing out.","title":"AI bubble, market crash, healthcare and value investing.","body":"I have been seeing a lot of posts on social media and the \"news\" (if we can even call it that anymore) debating whether we're in an AI bubble and whether what we're seeing will be the future. However, for those of us who have been around for the dot com and housing crash, we have seen this replay too many times. Nevertheless, before we delve into this, we must begin with the definition. Don't bitch. You know I love definitions.\n\nWhat is a bubble? A market bubble is when asset prices disconnect from real, sustainable economic value because investors chase hype, momentum, and the fear of missing out. Bubbles aren’t about technology being fake; they’re about valuations outpacing reality. There are five ingredients that make up a bubble.\n\n1. A compelling narrative “This will change everything.” Everything changed when the Fire Nation attacked.\n2. Cheap or easily accessible money. Zero cost trading and easily acquired leverage. Looking at you Robinhood.\n3. Rapid capital inflow. Tech companies circle jerking each other with the same trillion dollar and writing it off as revenue.\n4. Valuations that detach from fundamentals\n5. A trigger that exposes the gap between story and earnings. We don't have this yet, but I think Oracle is the first sign.\n\nNow that we have that out of the way, we can start looking at how the dot com, housing, and AI are parallel to each other.\n\n|Dot-Com Bubble (1995–2000)|Housing Bubble (2002–2007)|AI Boom/Bubble|\n|:-|:-|:-|\n||||\n|Narrative: “Every company on the internet will dominate the future.”|Narrative: “Housing never goes down.” “Real estate is a guaranteed investment.” My families actually lost a lot of money because we're Asian, and we love housing because it is a signature of wealth.|Narrative: “AI will replace everything and profit margins will be infinite.”|\n|What actually happened: Companies with no revenue model IPO’d. Tech CEOs left constantly, cashed out stock options, or switched to “advisory roles.” Valuations were based on eyeballs, not earnings. When earnings rolled in, it became clear many companies had no path to profit.|What actually happened: Extreme leverage (subprime loans, NINJA loans, MBS, CDOs). Asset values distorted by financial engineering, not innovation. Banks offloaded risk and kept lending. People owned 3–4 houses with no income check. One of my cousin actually owned 11 homes and lost it all.|What actually happened: Massive capex spending: GPUs, data centers, power infrastructure. Everyone is claiming an AI strategy—even if it has no real productivity case. Companies priced for perfection, assuming exponential revenue growth. Valuations assume AI will produce immediate, massive earnings.|\n|Trigger for the Crash: Fed raised rates. Weak earnings revealed the emperor had no clothes. IPO pipeline collapsed.|Trigger for the Crash: Rising rate, mortgage reset, and mass defaults. Once prices dipped slightly, the whole system—built on leverage—imploded. I actually think the current car loans, student loans, and credit card loans, and the retail investors fall into this category.|We don't know if it will crash, but it is likely because we're seeing the early warning signs. AI companies spending more on GPUs than they make in revenue. Margins tightening because inference costs are high. CEO churn beginning (not as extreme as dot-com, but rising). Investors chasing AI because everything else looks slow.|\n|Reality: The internet was transformative. But the winners (Amazon, Google) emerged only after the garbage cleared out.|Reality: Homeownership is valuable, but valuations weren’t.|Reality: AI is real. But markets may be pricing in outcomes 20 years too early, same as every major tech cycle.|\n\nOne of the big things we're seeing from companies like Tesla is the idea that Robots will be like Ghost In the Shell, and it will change our world. However, if we look at the leader of robotic (Boston Dynamic), and the current hypes that are getting big investments, we can see that we are nowhere near commercialization and profitability on the scale that we're hyping them up to be.\n\nThe leader of robotic\n\n[https://www.youtube.com/watch?v=I44\\_zbEwz\\_w](https://www.youtube.com/watch?v=I44_zbEwz_w)\n\n[https://www.youtube.com/watch?v=bzKDh6cRe3E](https://www.youtube.com/watch?v=bzKDh6cRe3E)\n\nThe leader in robotic bullshit and hype to raise money\n\n[https://www.youtube.com/watch?v=5fypwRUP6S8](https://www.youtube.com/watch?v=5fypwRUP6S8)\n\nOverall, we can draw many parallels between the three bubbles.\n\n1. The hype is way bigger than the fundamental. For the dot come, the price did not match the revenue. For the housing, the price did not match the income you were getting from those houses. For the Ai, the price does not match sustainable earnings.\n2. Everyone piles in later in the cycle: tech IPOs in 1999, Mortgage flipping in 2005, and massive retail and institutional investments when valuation is insane.\n3. CEOs are stepping down. Historically, CEO turnover spikes shortly before a bubble pops. For the dot com, founders bailed and cashed out options. For the housing bubble, bank CEOs stepping down in 2006-2007. For the Ai, we haven't seen it yet, but we're seeing some crack with apple, Walmart, and BBC CEOs.\n\n[https://www.theverge.com/news/821691/tim-cook-step-down-apple-ceo-next-year#:\\~:text=And%20the%20board%20has%20started%20to%20seriously,is%20considered%20the%20frontrunner%20for%20the%20position](https://www.theverge.com/news/821691/tim-cook-step-down-apple-ceo-next-year#:~:text=And%20the%20board%20has%20started%20to%20seriously,is%20considered%20the%20frontrunner%20for%20the%20position).\n\n[https://www.reuters.com/sustainability/boards-policy-regulation/walmart-ceo-doug-mcmillon-retire-names-insider-john-furner-new-ceo-2025-11-14/](https://www.reuters.com/sustainability/boards-policy-regulation/walmart-ceo-doug-mcmillon-retire-names-insider-john-furner-new-ceo-2025-11-14/)\n\n[https://www.bbc.co.uk/news/articles/c3vn25d5dq7o](https://www.bbc.co.uk/news/articles/c3vn25d5dq7o)\n\nWe are also starting to see signs (I used Google AI search for this because too much information)...\n\n* Intel: CEO Pat Gelsinger was ousted by the board and retired in August 2025 (effective December 2024), amid struggles in the AI chip market and performance pressures. The company appointed David Zinsner and Michelle Johnston Holthaus as interim Co-CEOs.\n* [Spotify](https://open.spotify.com/): In September 2025, founder Daniel Ek transitioned from CEO to chairman, and the company named new co-CEOs.\n* [GitHub](https://github.com/): Long-time CEO Thomas Dohmke departed in August 2025 to launch a new start-up.\n* C3.ai: Thomas Siebel, the CEO of the enterprise AI software company, resigned in November 2025 due to health issues, as the company explores potential sales options.\n* DeFi Technologies: In November 2025, CEO Olivier Roussy Newton resigned and was replaced by co-founder Johan Wattenström, as the company undergoes a strategic transition in the digital asset space.\n* Verizon: A major leadership change occurred when former PayPal boss Dan Schulman was named the new CEO in October/November, a change which was followed by significant layoffs as part of a company restructuring.\n* Pia: The AI-enabled help desk automation platform named David Schwartz as its new CEO in June 2025.\n* Kaseya: The AI-powered IT management and cybersecurity company appointed Rania Succar as its new CEO after the former CEO transitioned out of the role.\n\n1. Another parallel is the extreme concentration of wealth. For the dot come, we have Cisco, Intel, Microsoft. For the housing bubble, we have Countrywide, Lehman, Fannie/Freddie. For the current AI bubble, we have Nvidia, Microsoft, Meta, Amazon. If even one of these companies starts showing cracks in its margins/profits, it will trigger the bubble's collapse.\n2. Lastly, the bubble popped because of unrealistic adoption timelines. For the dot com, “everyone will buy groceries online in 1999”. For the housing bubble, “everyone can afford a home forever”. For the AI bubble, “every company will automate everything immediately”.\n\nNevertheless, it could be possible that we are in an actual boom instead of a bubble with AI. AI bubble is built on capex and expectations, not debt. Therefore, the collapse--if it happen--won’t be as catastrophic to the financial system. Just like Amazon after dot-com, AI will produce massive long-term winners. But many players--especially infrastructure-heavy ones--won’t survive the earnings reality test. I'm looking at you Tesla, Oracle, and many others. Please keep in mind that this doesn't mean we won't have an economy that was crash and reset. Just look at the news:\n\nNew foreclosures jump 20% in October, a sign of more distress in the housing market\n\n[https://www.cnbc.com/2025/11/13/foreclosures-rise-october-housing-market-distress.html](https://www.cnbc.com/2025/11/13/foreclosures-rise-october-housing-market-distress.html)\n\nNearly 900,000 new homeowners are underwater on their mortgages, signaling a troubling shift in the housing market\n\n[https://www.marketwatch.com/story/nearly-900-000-new-homeowners-are-underwater-on-their-mortgages-signaling-a-troubling-shift-in-the-housing-market-21fce9fc?gaa\\_at=eafs&gaa\\_n=AWEtsqemQ3Qu2qgIIZXgtgHVONfiUC\\_tAx-H1iCMDIHaJb3dDOoC1L1j-MrtNrOFovA%3D&gaa\\_ts=691a0110&gaa\\_sig=LqOgR9g2o6M41pkPC0RkK0b5FzBXLXjqkyPcFMVngC19i\\_SQ15UUbj5zsTYuQzqocugtsnlvNiWkj3Bj6iIDLQ%3D%3D](https://www.marketwatch.com/story/nearly-900-000-new-homeowners-are-underwater-on-their-mortgages-signaling-a-troubling-shift-in-the-housing-market-21fce9fc?gaa_at=eafs&gaa_n=AWEtsqemQ3Qu2qgIIZXgtgHVONfiUC_tAx-H1iCMDIHaJb3dDOoC1L1j-MrtNrOFovA%3D&gaa_ts=691a0110&gaa_sig=LqOgR9g2o6M41pkPC0RkK0b5FzBXLXjqkyPcFMVngC19i_SQ15UUbj5zsTYuQzqocugtsnlvNiWkj3Bj6iIDLQ%3D%3D)\n\nChina’s unemployed Gen Z are proudly calling themselves ‘rat people’—they’re spending all day in bed in a rebellion against burnout\n\n[https://fortune.com/2025/11/14/china-unemployed-gen-z-rat-people-rebelling-against-workplace-burnout/](https://fortune.com/2025/11/14/china-unemployed-gen-z-rat-people-rebelling-against-workplace-burnout/)\n\n‘It’s so demoralising’: UK graduates exasperated by high unemployment\n\n[https://www.theguardian.com/society/2025/nov/15/its-so-demoralising-uk-graduates-exasperated-by-high-unemployment](https://www.theguardian.com/society/2025/nov/15/its-so-demoralising-uk-graduates-exasperated-by-high-unemployment)\n\nOctober Jobs Report to Skip Unemployment Rate, Hassett Says\n\n[https://www.bloomberg.com/news/articles/2025-11-13/october-jobs-report-to-skip-unemployment-rate-hassett-says](https://www.bloomberg.com/news/articles/2025-11-13/october-jobs-report-to-skip-unemployment-rate-hassett-says)\n\nConsumer Sentiment Falls Toward Record-Low Levels\n\n[https://www.wsj.com/economy/consumers/u-s-consumer-confidence-slides-in-november-8b5a459a?gaa\\_at=eafs&gaa\\_n=AWEtsqfYS8F1y0PRyM8x8Z41LlInnNErozlpmskkpLEiFfPY-sKcIwkIHwEXSn8rpa0%3D&gaa\\_ts=691a0184&gaa\\_sig=3aJrnu61kppYr4v8nDsxTvH11Lm5hjDwTUaYNN4HIBfJ69sqSWQhCP\\_ETf9r-bC2ePls7F1lL8RF-tMVLJUGOA%3D%3D](https://www.wsj.com/economy/consumers/u-s-consumer-confidence-slides-in-november-8b5a459a?gaa_at=eafs&gaa_n=AWEtsqfYS8F1y0PRyM8x8Z41LlInnNErozlpmskkpLEiFfPY-sKcIwkIHwEXSn8rpa0%3D&gaa_ts=691a0184&gaa_sig=3aJrnu61kppYr4v8nDsxTvH11Lm5hjDwTUaYNN4HIBfJ69sqSWQhCP_ETf9r-bC2ePls7F1lL8RF-tMVLJUGOA%3D%3D)\n\nDo I think the market will crash and go down right now? Hell no. I think the market will go up, and it will maybe have a Thanksgiving and Santa Rallies. However, we can't denied that reality that we're in with AI. Narrative is peaking without tangible results. Capital expenditure is outpacing revenue. Early signs of exhaustion are showing (Cough Oracle). Earnings are not yet justifying valuations (the numbers are just insane). We haven’t seen the blow-off top yet because things are still pumping.\n\nThe real crunch is when we start seeing earnings where the AI revenues fail to scale as quickly as GPU spending. Tha","offTopic":true},{"id":"51b649c1-74ae-43c0-be55-806c47f4899e","excerpt":"OpenAI and Anthropic IPO is the ripoff of this century. — I got into stocks a few months ago. Haven't read a single book. And I can see the bubble popping from a mile away.\n\n​\n\nIf a complete fucking noob like me can see it, the people selling you the OpenAI IPO at $1 trillion have seen it for years. They're not ","url":"https://www.reddit.com/r/AIBubble/comments/1u3yw2k/openai_and_anthropic_ipo_is_the_ripoff_of_this/","role":"pricing","weight":1.1257008,"occurredAt":"2026-06-12T15:42:32.000Z","sourceKey":"reddit","sourceName":"Reddit","credibility":0.62,"venue":"AIBubble","intent":"pricing_complaint","painScore":0.5495652,"sentiment":-0.17391305,"confidence":0.7264624,"matchedPatterns":["too_expensive"],"statement":"​ Bhai in Hyderabad can't afford Claude tokens.","title":"OpenAI and Anthropic IPO is the ripoff of this century.","body":"I got into stocks a few months ago. Haven't read a single book. And I can see the bubble popping from a mile away.\n\n​\n\nIf a complete fucking noob like me can see it, the people selling you the OpenAI IPO at $1 trillion have seen it for years. They're not telling you because they need to dump their bags.\n\n​\n\nThis is not advice. This is a warning.\n\n​\n\n\\---\n\n​\n\nPart One: The Numbers Are Fucking Screaming\n\n​\n\nBuffett Indicator is at 232%. In 2000, before the dot-com crash, it was around 140%. We're 92 points higher. The historical average is 81%. We're 2 standard deviations above the mean. Every time this happened before, the market dropped at least 25%. Three for three. No exceptions.\n\n​\n\nCAPE ratio is 41. The only other times it was this high were 1929 (Great Depression) and 2000 (dot-com crash). Not 30. Not 35. Forty-fucking-one.\n\n​\n\nMargin debt hit $1.3 trillion in April 2026. Up 53% year-over-year. Margin debt to GDP is 4.1%. The 50-year average is 1.5%. People are borrowing money to buy AI at peak valuations.\n\n​\n\nThe top 10 S&P stocks make up 35-40% of the entire index. Higher than 2000. Higher than 1929. Most concentrated market in 100 years.\n\n​\n\nGo look this shit up yourself. It's not opinion. It's math.\n\n​\n\n\\---\n\n​\n\nPart Two: The Capex Problem Nobody Wants to Talk About\n\n​\n\nGoogle, Amazon, Microsoft, and Meta are spending $725 billion on AI infrastructure in 2026. Up 77% from last year. The entire US defense budget is $850 billion. Four tech companies are spending almost as much as the military.\n\n​\n\nGoldman Sachs says these four will spend $5.3 trillion from 2025 to 2030. Their own head of research is warning it might never pay off.\n\n​\n\nAlphabet's free cash flow is projected to drop 90% to $8.2 billion from $73 billion. Amazon's free cash flow is going negative. These are not startups. These are the most profitable companies on earth, and they're torching cash on a bet that AI revenue shows up fast enough.\n\n​\n\nWhat happens when that revenue doesn't come? When growth slows from 50% to 30%? Stocks don't drop 10%. They drop 30-50%.\n\n​\n\n\\---\n\n​\n\nPart Three: The Unit Economics Are Impossible\n\n​\n\nOpenAI loses $1.22 for every dollar of revenue. They lose money on every single user. Financial documents show they expect to lose $74 billion in 2028 alone. They've committed to $1.4 trillion in data center spending. That's not ambition. That's desperation.\n\n​\n\nAnd the Chinese are selling the same intelligence for pennies.\n\n​\n\nPrice comparison (output per 1M tokens):\n\n​\n\n· Xiaomi MiMo: $0.02-0.04\n\n· DeepSeek V4 Flash: $0.28\n\n· GPT-5: $10.00\n\n· Claude Sonnet 4.6: $15.00\n\n· Claude Opus 4.6: $75.00\n\n​\n\nXiaomi is 375-750x cheaper than GPT-5. Up to 750x cheaper than Claude Sonnet.\n\n​\n\nRead that again. Seven hundred and fifty times cheaper. For 95-99% of the quality.\n\n​\n\nAnthropic just posted their first operating profit: $559 million in Q2 2026. Run-rate revenue $44 billion. They might break even by 2028. Good for them. But at a $965 billion valuation, you're paying 20-30x revenue for a company that made half a billion in one quarter. That's not a multiple. That's a prayer.\n\n​\n\n\\---\n\n​\n\nPart Four: The Chinese Are Not Coming. They're Already Here.\n\n​\n\nXiaomi dropped MiMo-V2.5 Pro in June 2026. Trillion-parameter model. MIT licensed. Open source. Top of SWE-bench. Beats or matches Claude and GPT on coding.\n\n​\n\nCached-input pricing? $0.0036 per million tokens. That's 833x cheaper than Claude.\n\n​\n\nNot 30%. Not 50%. Eight hundred and thirty-three times cheaper.\n\n​\n\nXiaomi doesn't need to profit from AI. They sell phones. EVs. Wearables. IoT. AI is a feature that moves hardware. They have 740 million monthly active devices. They can pre-install MiMo on every single one for free.\n\n​\n\nOpenAI has zero devices. Anthropic has zero devices. No hardware. No distribution. No ecosystem. No subsidy. Just a website, an API, and a dream.\n\n​\n\n\\---\n\n​\n\nPart Five: The Ecosystem Moats You're Ignoring\n\n​\n\nLet me rank who actually wins.\n\n​\n\nGoogle: 90% search market share. 3.8 billion Android devices. 2.6 billion YouTube users. Chrome with 3.6 billion users. Cloud growing 63% year-over-year. They invented Transformers. Gemini is #1 on most benchmarks. They can give it away forever because search ads print $132 billion in profit. Google doesn't need AI to be a product. AI is a feature that keeps you in their shit.\n\n​\n\nMicrosoft: 1.4 billion Windows devices. 1.3 billion Office users. 180 million GitHub developers. 1.3 billion LinkedIn accounts. Azure is #2 cloud. AI run-rate is $37 billion, up 123% year-over-year. Azure grew 40% in Q3 2026. Quarterly revenue $82.9 billion with $31.8 billion net income. OpenAI is 45% of Azure's $625 billion in remaining performance obligations. Microsoft wins whether OpenAI lives or dies.\n\n​\n\nApple: 2.5 billion active devices. $130-160 billion in cash. 68% return on invested capital. Spending 3% of revenue on AI capex while everyone else burns 20-30%. They're not racing. They're waiting to buy the survivors at distressed prices. Same playbook every time.\n\n​\n\nXiaomi: 740 million monthly active devices. A fan base that will die for value for money. They did it to smartphones. Wearables. EVs. Now AI. No news. No YouTubers. No influencers. Just MiFans in India, Nigeria, Indonesia, and Brazil who will swarm every forum because they are religious about getting more for less.\n\n​\n\nAmazon: 28% global cloud market share. Every AI workload runs on AWS. They get paid regardless of the model.\n\n​\n\nMeta: $200 billion in annual ad revenue. AI makes ads better. Open-sourced Llama to commoditize everyone else's API revenue. That's not an accident. That's strategic warfare.\n\n​\n\nNow what do OpenAI and Anthropic have?\n\n​\n\nOpenAI has a brand that's fading. No distribution. No default on any OS. No browser. No search. No hardware. No ecosystem. No subsidy. Your grandma can switch to Gemini in one click for free. Enterprises can switch to Xiaomi for 750x less. Their only moat was being first. Netscape was first too.\n\n​\n\nAnthropic has better unit economics. Same distribution problem. Same ecosystem problem. Same Chinese price problem. Same subsidy problem. Same dog, different hair color.\n\n​\n\n\\---\n\n​\n\nPart Six: History Doesn't Repeat, But It Rhymes\n\n​\n\n1999: Netscape had 80% browser market share. Microsoft bundled IE with Windows for free. Netscape died.\n\n​\n\n2026: OpenAI has 53-61% chatbot market share. Google bundles Gemini for free. Microsoft bundles Copilot. Apple bundles Apple Intelligence. Xiaomi bundles MiMo for pennies.\n\n​\n\nNetscape had a better moat. They still died. OpenAI has no moat. What do you think happens?\n\n​\n\n2000: Cisco was the king of the internet. Routers everywhere. Stock at 130x earnings. Dropped 80% and never recovered to its peak. 26 years later, still below.\n\n​\n\n2026: Nvidia is the king of AI. GPUs everywhere. Stock at 23x forward earnings. Not 130x. But $4.8 trillion market cap. If growth slows from 50% to 30%, that stock doesn't drop 20%. It drops 50%.\n\n​\n\nCompanies that survived dot-com had existing revenue, existing moats, existing distribution. Amazon sold books. Microsoft sold Windows. Apple sold Macs. Google didn't even IPO yet.\n\n​\n\nCompanies that died had no business model. Pets.com. Webvan. Boo.com. Hype. First-mover advantage. Brand recognition. No revenue. No moat. No distribution. No path to profit.\n\n​\n\nOpenAI has revenue. But they lose money on every dollar of it. They can't raise prices because Google and Microsoft are free. They can't cut costs enough because Xiaomi is 750x cheaper. They're trapped. The IPO is the only exit.\n\n​\n\n\\---\n\n​\n\nPart Seven: The IPO Window Is Closing. That's Why They're Rushing.\n\n​\n\nSpaceX IPOs today (June 12, 2026) at $1.75 trillion target. OpenAI IPOs September/late 2026 at $850b-$1 trillion. Anthropic IPOs October 22, 2026 at $965 billion.\n\n​\n\nThree IPOs. Three months. $3.6 trillion combined.\n\n​\n\nWhy rush? They should have IPO'd in 2024-2025. They didn't. Now the window is closing. Buffett at 232%. CAPE at 41. Margin debt at $1.3 trillion.\n\n​\n\nThey're not IPOing because they want to. They're IPOing because they have to. VCs need to return capital. Early employees need liquidity. Founders need to cash out. Window is closing. Last chance to sell to retail before the crash.\n\n​\n\nSam Altman knows OpenAI has no moat. Knows the Chinese are 750x cheaper. Knows the bubble will pop. He just needs to sell his shares before it does. That's not a visionary founder building the future. That's a salesman dumping his bag on you.\n\n​\n\n\\---\n\n​\n\nPart Eight: The Xiaomi Wildcard Nobody Is Watching\n\n​\n\nXiaomi is the most underrated AI player. No news. No notifications. No YouTubers. No TikTok. Just 100 million MiFans who are religious about value.\n\n​\n\nPoco F1 in 2018: 80% of Samsung flagship specs at 1/3 the price. Became a legend.\n\n​\n\nMi Band: 90% of Fitbit features at 1/3 the price. Fitbit died.\n\n​\n\nSU7 EV: 95% of Tesla specs at 2/3 the price. 100,000 preorders in 24 hours.\n\n​\n\nMiMo AI: 95-99% of Claude quality at 1/375th to 1/750th the price.\n\n​\n\nThe math is clear. The benchmarks are clear. The comparison is clear.\n\n​\n\nBhai in Hyderabad can't afford Claude tokens. He can afford Xiaomi.\n\n​\n\nDavid in Toronto can afford Claude. But when his CFO sees a $100,000 OpenAI bill and a $150 Xiaomi bill, what do you think happens? The switch happens overnight.\n\n​\n\nGoogle, Microsoft, and Apple target average Jake. Chinese value players target everyone else. Where is the room for OpenAI and Anthropic? There isn't any.\n\n​\n\n\\---\n\n​\n\nPart Nine: What Happens and When\n\n​\n\nPeak comes after OpenAI and Anthropic IPOs. December 2026 to January 2027. S&P could hit 7,500-8,000. Sentiment euphoric. Your Uber driver buys OpenAI shares. Your barber asks about Nvidia.\n\n​\n\nFirst crack: hyperscaler free cash flow miss. Google or Amazon reports AI capex compressing margins. Stock drops 10-15%. Then Chinese model update hits news, showing parity or superiority at 1/1000th the price. AI stocks drop another 10-20%.\n\n​\n\nFake bounce: dead cat. sucker's rally. Convinces you the crash is over. It's not. It's a trap.\n\n​\n\nReal crash: early to mid-2027. S&P drops 30-50% from peak. Nvidia drops 50-70%. OpenAI trades below IPO price. Anthropic trades below IPO price. SPACs go to zero. Margin calls cascade. VIX hits 50. Retail panic sells at the bottom.\n\n​\n\nBottom: 2027 or 2028. That's when you buy.\n\n​\n\n\\---\n\n​\n\nPart Ten: The Play\n\n​\n\nDo not buy SpaceX IPO today.\n\nDo not buy OpenAI IPO in September.\n\nDo not buy Anthropic IPO in October.\n\n​\n\nThey are not once-in-a-lifetime opportunities. They are once-in-a-lifetime traps. Insiders are selling. VCs are exiting. Sam Altman is cashing out. They're not selling you a vision. They're selling you a bag.\n\n​\n\nDo not buy AI stocks at the peak.\n\n​\n\nWait for the crash. Wait for the fake bounce. Wait for the real crash.\n\n​\n\nThen buy the companies with moats, distribution, ecosystems, and subsidies:\n\n​\n\n· Google (search monopoly, Android, free Gemini)\n\n· Microsoft (Windows, Office, Azure, free Copilot)\n\n· Apple (2.5 billion devices, $130-160B cash, free Apple Intelligence)\n\n· Xiaomi (700 million devices, value-for-money religion, MiMo at 1/750th cost)\n\n· Nvidia (after crash, $1-3 trillion, they still make the GPUs)\n\n· TSMC and ASML (picks and shovels)\n\n​\n\nHold for years. Don't trade. Don't panic. Don't listen to YouTubers who called the top in 2024 and were wrong for","offTopic":true},{"id":"e4881870-ffd6-446f-b531-6e05908cbde0","excerpt":"Are We About to Ditch Subscriptions for Good? How x402 Micropayments Could Reshape AI and SaaS. — I’ve been thinking about how we pay for software, and I’m starting to believe the subscription model isn’t just annoying —it’s becoming structurally broken, especially in the AI era.\nWe’ve all accepted the $20/month SaaS t","url":"https://www.reddit.com/r/microsaas/comments/1sy2389/are_we_about_to_ditch_subscriptions_for_good_how/","role":"pain","weight":1.1188507,"occurredAt":"2026-04-28T13:52:51.000Z","sourceKey":"reddit","sourceName":"Reddit","credibility":0.62,"venue":"microsaas","intent":"purchase_intent","painScore":0.43272728,"sentiment":-0.18181819,"confidence":0.7809237,"matchedPatterns":["frustrating","would_pay"],"statement":"I’ve been thinking about how we pay for software, and I’m starting to believe the subscription model isn’t just annoying —it’s becoming structurally broken, especially in the AI era.","title":"Are We About to Ditch Subscriptions for Good? How x402 Micropayments Could Reshape AI and SaaS.","body":"I’ve been thinking about how we pay for software, and I’m starting to believe the subscription model isn’t just annoying —it’s becoming structurally broken, especially in the AI era.\nWe’ve all accepted the $20/month SaaS tax as inevitable. But with AI, the economics are shifting under our feet. We’re not buying static tools anymore; we’re buying compute and access —things that fluctuate wildly depending on what we actually do. Yet we’re still forced into flat-rate buckets that either bleed us dry or leave us underutilized.\nEnter x402 (HTTP 402 Payment Required). Instead of renting software by the calendar, you pay by the request . Micropayments. Per API call. Per generation. Per unit of value consumed.\nHere’s why this debate matters right now:\nSubscriptions create misaligned incentives. The vendor wins when you don’t use the product. Your $20/month is pure profit to them if you forget to cancel. The product gets bloated with features you don’t need because the only way to grow is to justify a higher price tier.\nx402 aligns incentives perfectly. You pay when you extract value. The vendor only makes money when you actually use the service. That should, in theory, force better uptime, faster models, and leaner feature sets.\nBut here’s the catch: x402 assumes a world where users want to think about every transaction. Do you really want to mentally budget every ChatGPT prompt? Subscriptions offer predictability and mental peace. There’s something to be said for “all-you-can-eat” when you’re in a creative flow state.\nThen there’s the infrastructure problem. Subscriptions are a solved problem—Stripe, Paddle, done. x402 requires wallets, gas fees (sometimes), liquidity management, and a level of crypto-adjacent complexity that most businesses and casual users want nothing to do with. The UX is getting better, but it’s not seamless yet.\nAnd the AI angle: AI costs are fundamentally variable. A simple query costs pennies; a complex reasoning chain with retrieval costs dollars. Subscription tiers force companies to average this out, which means light users subsidize power users. x402 could democratize access. pay a fraction for the month if you’re a light user, as opposed to being forced into a 20$ monthly commitment. My take? We’re heading for a hybrid world, but the shift is real. \n\nSubscriptions made sense when software was a static asset. AI and agentic workflows are dynamic utilities . You don’t pay a flat monthly fee for electricity; you pay per kWh. Why should intelligence be different?\nThat said, x402 won’t dethrone subscriptions until the friction drops to near-zero. The question isn’t if the model will change—it’s whether incumbents will adapt, or if a new wave of AI-native tools will force their hand by simply being 10x cheaper at the margins.\nSo I’m curious—where do you land?\n \nAre subscriptions just Stockholm syndrome at this point?\n \nWould you trade the mental safety of a flat fee for true usage-based pricing?\n \nOr is x402 just crypto-bro fantasy that ignores how real businesses and consumers actually behave?\n\n\nDrop your thoughts. \n\nI think this is going to be one of the defining business model fights of the next 3–5 years, and most people aren’t even paying attention yet. An article that overly simplifies our peculiar stand at the crossroads of micro transactions. Do find time to scheme through. Interesting days ahead. \n\n👇👇👇👇 \n\\[https://x.com/i/status/2045501903115784382\\](https://x.com/i/status/2045501903115784382)","offTopic":true},{"id":"a6422f5d-86e0-4447-8f3d-1dea8e13b003","excerpt":"Nvidia's Jensen and now China's data chief say the same thing: Nobody's connecting the dots — **TL;DR:** Jensen Huang and China's data chief both declared tokens a \"commodity\" and \"settlement unit\" the same week. They're not talking about compensation or tech specs. They're building the pricing infrastructure that turn","url":"https://www.reddit.com/r/ArtificialInteligence/comments/1s5ag8a/nvidias_jensen_and_now_chinas_data_chief_say_the/","role":"pricing","weight":1.1124667,"occurredAt":"2026-03-27T17:17:36.000Z","sourceKey":"reddit","sourceName":"Reddit","credibility":0.62,"venue":"ArtificialInteligence","intent":"pricing_complaint","painScore":0.48,"sentiment":0,"confidence":0.75166667,"matchedPatterns":["too_expensive"],"statement":"That's not sustainable, but it also doesn't mean tokens are overpriced.","title":"Nvidia's Jensen and now China's data chief say the same thing: Nobody's connecting the dots","body":"**TL;DR:** Jensen Huang and China's data chief both declared tokens a \"commodity\" and \"settlement unit\" the same week. They're not talking about compensation or tech specs. They're building the pricing infrastructure that turns AI from a money-losing subscription service into a functioning economy where token consumption is an investment with measurable returns, priced like energy or raw materials.\n\nTwo things happened the same week that are more connected than they may first appear.\n\nAt GTC, Jensen Huang called tokens \"the new commodity\" and proposed giving Nvidia engineers token budgets worth half their base salary. Days later, China's National Data Administration head Liu Liehong called tokens a \"settlement unit\" and a \"value anchor for the intelligent era.\" China even coined an official term: \"ciyuan,\" combining \"word\" with \"yuan,\" their currency unit.\n\nTwo very different actors, arriving at the same framing independently. Why, and why now?\n\nBecause the AI industry is at the point where tokens need to be understood as what they actually are: units of productive output, not just a cost center. When Jensen says he'd be \"deeply alarmed\" if a $500,000 engineer consumed only $5,000 in tokens, he's saying the tokens are where the value gets created. An engineer plus $250K in token consumption produces dramatically more than that same engineer working without them. The token spend is an investment with a return, the same way a manufacturer investing in better equipment expects higher output per worker.\n\nThe problem isn't that tokens cost money. It's that the current pricing model doesn't reflect their productive value. AI companies have been giving away tokens at below cost to build market share, the way ride-sharing companies subsidized every trip for years. OpenAI is projecting $17B in cash burn this year. Anthropic is spending roughly $19B against break-even revenue. That's not sustainable, but it also doesn't mean tokens are overpriced. It means they're underpriced relative to the value they generate.\n\nThat's why the commodity framing matters. When both Jensen and China's data chief independently call tokens a commodity and a settlement unit, they're building the foundation for a pricing model that connects cost to value. Once organizations budget for tokens the way they budget for energy, cloud compute, or raw materials, the price can find a level that reflects what tokens actually produce rather than what a subscription marketing strategy dictates.\n\nThe analogy to energy markets runs deeper than you might expect. The compute that produces tokens (GPU cycles, electricity, data center capacity) is fungible at the base layer, same as crude oil regardless of origin. Tokens are the refined product. Like gasoline, they come in grades: lightweight inference is regular, deep reasoning is premium, multimodal is high-octane. What matters to the end user is the output, not the molecular composition of the fuel.\n\nOnce you see it this way, the competitive landscape snaps into focus. China is playing the low-cost producer: converting cheap renewable energy into tokens through efficient model architectures. MiniMax and Moonshot charge $2-3 per million output tokens vs. roughly $15 for comparable US models. US providers are playing the premium tier: better reliability, data sovereignty, deeper reasoning. Both approaches work because different applications demand different grades of token, just as different vehicles need different grades of fuel.\n\nGoldman Sachs found in March that AI delivers roughly 30% productivity gains on targeted tasks like customer support and software development. Those gains translate into real returns for organizations willing to invest in token consumption. The companies figuring out which tasks generate the highest return per token spent are building a genuine competitive advantage, not just running up a bill.\n\nThe race isn't just to build better models. It's to define how the output of those models gets priced, traded, and valued. Jensen and Liu Liehong both seem to understand that whoever wins that framing contest shapes the economics of AI for the next decade.","offTopic":true},{"id":"a2116259-ab87-42e3-8769-4bbcac8b18b3","excerpt":"AI bubble, market crash, healthcare and value investing. — Hello Fellow Apes,\n\nI have been seeing a lot of posts on social media and the \"news\" (if we can even call it that anymore) debating whether we're in an AI bubble and whether what we're seeing will be the future. However, for those of us who have been around for","url":"https://www.reddit.com/r/Healthcare_Anon/comments/1oytyka/ai_bubble_market_crash_healthcare_and_value/","role":"pain","weight":1.1008242,"occurredAt":"2025-11-16T19:00:08.000Z","sourceKey":"reddit","sourceName":"Reddit","credibility":0.62,"venue":"Healthcare_Anon","intent":"feature_request","painScore":0.5674074,"sentiment":-0.5185185,"confidence":0.7023217,"matchedPatterns":["missing_feature"],"statement":"A market bubble is when asset prices disconnect from real, sustainable economic value because investors chase hype, momentum, and the fear of missing out.","title":"AI bubble, market crash, healthcare and value investing.","body":"Hello Fellow Apes,\n\nI have been seeing a lot of posts on social media and the \"news\" (if we can even call it that anymore) debating whether we're in an AI bubble and whether what we're seeing will be the future. However, for those of us who have been around for the dot com and housing crash, we have seen this replay too many times. Nevertheless, before we delve into this, we must begin with the definition. Don't bitch. You know I love definitions. \n\nWhat is a bubble? A market bubble is when asset prices disconnect from real, sustainable economic value because investors chase hype, momentum, and the fear of missing out. Bubbles aren’t about technology being fake; they’re about valuations outpacing reality. There are five ingredients that make up a bubble.\n\n1. A compelling narrative “This will change everything.” Everything changed when the Fire Nation attacked.\n\n2. Cheap or easily accessible money. Zero cost trading and easily acquired leverage. Looking at you Robinhood.\n\n3. Rapid capital inflow. Tech companies circle jerking each other with the same trillion dollar and writing it off as revenue.\n\n4. Valuations that detach from fundamentals\n\n5. A trigger that exposes the gap between story and earnings. We don't have this yet, but I think Oracle is the first sign. \n\nNow that we have that out of the way, we can start looking at how the dot com, housing, and AI are parallel to each other. \n\n\n\n|Dot-Com Bubble (1995–2000)|Housing Bubble (2002–2007)|AI Boom/Bubble|\n|:-|:-|:-|\n|Narrative: “Every company on the internet will dominate the future.”|Narrative: “Housing never goes down.” “Real estate is a guaranteed investment.” My families actually lost a lot of money because we're Asian, and we love housing because it is a signature of wealth.|Narrative: “AI will replace everything and profit margins will be infinite.”|\n|What actually happened: Companies with no revenue model IPO’d. Tech CEOs left constantly, cashed out stock options, or switched to “advisory roles.” Valuations were based on eyeballs, not earnings. When earnings rolled in, it became clear many companies had no path to profit. |What actually happened: Extreme leverage (subprime loans, NINJA loans, MBS, CDOs). Asset values distorted by financial engineering, not innovation. Banks offloaded risk and kept lending. People owned 3–4 houses with no income check. One of my cousin actually owned 11 homes and lost it all. |What actually happened: Massive capex spending: GPUs, data centers, power infrastructure. Everyone is claiming an AI strategy—even if it has no real productivity case. Companies priced for perfection, assuming exponential revenue growth. Valuations assume AI will produce immediate, massive earnings.|\n|Trigger for the Crash: Fed raised rates. Weak earnings revealed the emperor had no clothes. IPO pipeline collapsed.|Trigger for the Crash: Rising rate, mortgage reset, and mass defaults. Once prices dipped slightly, the whole system—built on leverage—imploded. I actually think the current car loans, student loans, and credit card loans, and the retail investors fall into this category. |We don't know if it will crash, but it is likely because we're seeing the early warning signs. AI companies spending more on GPUs than they make in revenue. Margins tightening because inference costs are high. CEO churn beginning (not as extreme as dot-com, but rising). Investors chasing AI because everything else looks slow.|\n|Reality: The internet was transformative. But the winners (Amazon, Google) emerged only after the garbage cleared out. |Reality: Homeownership is valuable, but valuations weren’t.|Reality: AI is real. But markets may be pricing in outcomes 20 years too early, same as every major tech cycle.|\n\nOne of the big things we're seeing from companies like Tesla is the idea that Robots will be like Ghost In the Shell, and it will change our world. However, if we look at the leader of robotic (Boston Dynamic), and the current hypes that are getting big investments, we can see that we are nowhere near commercialization and profitability on the scale that we're hyping them up to be. \n\nThe leader of robotic\n\n[https://www.youtube.com/watch?v=I44\\_zbEwz\\_w](https://www.youtube.com/watch?v=I44_zbEwz_w)\n\n[https://www.youtube.com/watch?v=bzKDh6cRe3E](https://www.youtube.com/watch?v=bzKDh6cRe3E)\n\nThe leader in robotic bullshit and hype to raise money\n\n[https://www.youtube.com/watch?v=5fypwRUP6S8](https://www.youtube.com/watch?v=5fypwRUP6S8)\n\nOverall, we can dry many parallels between the three bubbles.\n\n1. The hype is way bigger than the fundamental. For the dot come, the price did not match the revenue. For the housing, the price did not match the income you were from those houses. For the Ai, the price does not match sustainable earnings. \n\n2. Everyone piles in later in the cycle: tech IPOs in 1999, Mortgage flipping in 2005, and massive retail and institutional investments when valuation is insane. \n\n3. CEOs are stepping down. Historically, CEO turnover spikes shortly before a bubble pops. For the dot com, founders bailed and cashed out options. For the housing bubble, bank CEOs stepping down in 2006-2007. For the Ai, we haven't seen it yet, but we're seeing some crack with apple, Walmart, and BBC CEOs.\n\nhttps://www.theverge.com/news/821691/tim-cook-step-down-apple-ceo-next-year#:\\~:text=And%20the%20board%20has%20started%20to%20seriously,is%20considered%20the%20frontrunner%20for%20the%20position.\n\n[https://www.reuters.com/sustainability/boards-policy-regulation/walmart-ceo-doug-mcmillon-retire-names-insider-john-furner-new-ceo-2025-11-14/](https://www.reuters.com/sustainability/boards-policy-regulation/walmart-ceo-doug-mcmillon-retire-names-insider-john-furner-new-ceo-2025-11-14/)\n\n[https://www.bbc.co.uk/news/articles/c3vn25d5dq7o](https://www.bbc.co.uk/news/articles/c3vn25d5dq7o)\n\nWe are also starting to see signs (I used Google AI search for this because too much information)...\n\n* Intel: CEO Pat Gelsinger was ousted by the board and retired in August 2025 (effective December 2024), amid struggles in the AI chip market and performance pressures. The company appointed David Zinsner and Michelle Johnston Holthaus as interim Co-CEOs.\n* [Spotify](https://open.spotify.com/): In September 2025, founder Daniel Ek transitioned from CEO to chairman, and the company named new co-CEOs.\n* [GitHub](https://github.com/): Long-time CEO Thomas Dohmke departed in August 2025 to launch a new start-up.\n* C3.ai: Thomas Siebel, the CEO of the enterprise AI software company, resigned in November 2025 due to health issues, as the company explores potential sales options.\n* DeFi Technologies: In November 2025, CEO Olivier Roussy Newton resigned and was replaced by co-founder Johan Wattenström, as the company undergoes a strategic transition in the digital asset space.\n* Verizon: A major leadership change occurred when former PayPal boss Dan Schulman was named the new CEO in October/November, a change which was followed by significant layoffs as part of a company restructuring.\n* Pia: The AI-enabled help desk automation platform named David Schwartz as its new CEO in June 2025.\n* Kaseya: The AI-powered IT management and cybersecurity company appointed Rania Succar as its new CEO after the former CEO transitioned out of the role.\n\n4. Another parallel is the extreme concentration of wealth. For the dot come, we have Cisco, Intel, Microsoft. For the housing bubble, we have Countrywide, Lehman, Fannie/Freddie. For the current AI bubble, we have Nvidia, Microsoft, Meta, Amazon. If even one of these companies starts showing cracks in its margins/profits, it will trigger the bubble's collapse. \n\n5. Lastly, the bubble popped because of unrealistic adoption timelines. For the dot com, “everyone will buy groceries online in 1999”. For the housing bubble, “everyone can afford a home forever”. For the AI bubble, “every company will automate everything immediately”. \n\nNevertheless, it could be possible that we are in an actual boom instead of a bubble with AI. AI bubble is built on capex and expectations, not debt. Therefore, the collapse--if it happen--won’t be as catastrophic to the financial system. Just like Amazon after dot-com, AI will produce massive long-term winners. But many players--especially infrastructure-heavy ones--won’t survive the earnings reality test. I'm looking at you Tesla, Oracle, and many others. Please keep in mind that this doesn't mean we won't have an economy that was crash and reset. Just look at the news:\n\nNew foreclosures jump 20% in October, a sign of more distress in the housing market\n\n[https://www.cnbc.com/2025/11/13/foreclosures-rise-october-housing-market-distress.html](https://www.cnbc.com/2025/11/13/foreclosures-rise-october-housing-market-distress.html)\n\nNearly 900,000 new homeowners are underwater on their mortgages, signaling a troubling shift in the housing market\n\n[https://www.marketwatch.com/story/nearly-900-000-new-homeowners-are-underwater-on-their-mortgages-signaling-a-troubling-shift-in-the-housing-market-21fce9fc?gaa\\_at=eafs&gaa\\_n=AWEtsqemQ3Qu2qgIIZXgtgHVONfiUC\\_tAx-H1iCMDIHaJb3dDOoC1L1j-MrtNrOFovA%3D&gaa\\_ts=691a0110&gaa\\_sig=LqOgR9g2o6M41pkPC0RkK0b5FzBXLXjqkyPcFMVngC19i\\_SQ15UUbj5zsTYuQzqocugtsnlvNiWkj3Bj6iIDLQ%3D%3D](https://www.marketwatch.com/story/nearly-900-000-new-homeowners-are-underwater-on-their-mortgages-signaling-a-troubling-shift-in-the-housing-market-21fce9fc?gaa_at=eafs&gaa_n=AWEtsqemQ3Qu2qgIIZXgtgHVONfiUC_tAx-H1iCMDIHaJb3dDOoC1L1j-MrtNrOFovA%3D&gaa_ts=691a0110&gaa_sig=LqOgR9g2o6M41pkPC0RkK0b5FzBXLXjqkyPcFMVngC19i_SQ15UUbj5zsTYuQzqocugtsnlvNiWkj3Bj6iIDLQ%3D%3D)\n\nChina’s unemployed Gen Z are proudly calling themselves ‘rat people’—they’re spending all day in bed in a rebellion against burnout\n\n[https://fortune.com/2025/11/14/china-unemployed-gen-z-rat-people-rebelling-against-workplace-burnout/](https://fortune.com/2025/11/14/china-unemployed-gen-z-rat-people-rebelling-against-workplace-burnout/)\n\n‘It’s so demoralising’: UK graduates exasperated by high unemployment\n\n[https://www.theguardian.com/society/2025/nov/15/its-so-demoralising-uk-graduates-exasperated-by-high-unemployment](https://www.theguardian.com/society/2025/nov/15/its-so-demoralising-uk-graduates-exasperated-by-high-unemployment)\n\nOctober Jobs Report to Skip Unemployment Rate, Hassett Says\n\n[https://www.bloomberg.com/news/articles/2025-11-13/october-jobs-report-to-skip-unemployment-rate-hassett-says](https://www.bloomberg.com/news/articles/2025-11-13/october-jobs-report-to-skip-unemployment-rate-hassett-says)\n\nConsumer Sentiment Falls Toward Record-Low Levels\n\n[https://www.wsj.com/economy/consumers/u-s-consumer-confidence-slides-in-november-8b5a459a?gaa\\_at=eafs&gaa\\_n=AWEtsqfYS8F1y0PRyM8x8Z41LlInnNErozlpmskkpLEiFfPY-sKcIwkIHwEXSn8rpa0%3D&gaa\\_ts=691a0184&gaa\\_sig=3aJrnu61kppYr4v8nDsxTvH11Lm5hjDwTUaYNN4HIBfJ69sqSWQhCP\\_ETf9r-bC2ePls7F1lL8RF-tMVLJUGOA%3D%3D](https://www.wsj.com/economy/consumers/u-s-consumer-confidence-slides-in-november-8b5a459a?gaa_at=eafs&gaa_n=AWEtsqfYS8F1y0PRyM8x8Z41LlInnNErozlpmskkpLEiFfPY-sKcIwkIHwEXSn8rpa0%3D&gaa_ts=691a0184&gaa_sig=3aJrnu61kppYr4v8nDsxTvH11Lm5hjDwTUaYNN4HIBfJ69sqSWQhCP_ETf9r-bC2ePls7F1lL8RF-tMVLJUGOA%3D%3D)\n\nDo I think the market will crash and go down right now? Hell no. I think the market will go up, and it will maybe have a Thanksgiving and Santa Rallies. However, we can't denied that reality that we're in with AI. Narrative is peaking without tangible results. Capital expenditure is outpacing revenue. Early signs of exhaustion are showing (Cough Oracle). Earnings are not yet justifying valuations (the numbers are just insane). We haven’t seen the blow-off top yet because things are still pumping.\n\nThe real crunch is when we start seeing earnings where the AI revenues fail to scale as quickly as GPU spending. That earnings gap is the modern version of the dot-com no revenue problem.\n\nWith that said, this is where value investing kick in. I hang out in the valueinvesting reddit a ","offTopic":true},{"id":"c3756488-91ec-4c8e-aa98-495f9afd0624","excerpt":"Cheap Alternatives are too Expensive: Insights from AI and Mega-Tech Earnings — Hi everyone. Big Tech earnings and the first print from SpaceX delivered some interesting headlines to discuss in this week’s post. Next week, I will post my full estimates and detailed breakouts for earnings, revenue, and guidance. Last we","url":"https://www.reddit.com/r/NvidiaStock/comments/1vjtkwu/cheap_alternatives_are_too_expensive_insights/","role":"pricing","weight":1.0613159,"occurredAt":"2026-08-09T16:01:00.000Z","sourceKey":"reddit","sourceName":"Reddit","credibility":0.62,"venue":"NvidiaStock","intent":"pricing_complaint","painScore":0.48,"sentiment":0.09090909,"confidence":0.7171053,"matchedPatterns":["too_expensive"],"statement":"Cheap Alternatives are too Expensive: Insights from AI and Mega-Tech Earnings.","title":"Cheap Alternatives are too Expensive: Insights from AI and Mega-Tech Earnings","body":"Hi everyone. Big Tech earnings and the first print from SpaceX delivered some interesting headlines to discuss in this week’s post. Next week, I will post my full estimates and detailed breakouts for earnings, revenue, and guidance. Last week’s first estimates post can be found on this subreddit or my personal profile.\n\nThe major players relevant to $NVDA that will be covered in this post are:\n\n* MSFT\n* META\n* GOOGL\n* SpaceX/Tesla\n* Surprise Bonus \n\nEach of these companies has an in-house alternative but cannot reduce its reliance on Nvidia for fear of losing the AI buildout race. The sentiment in these prints echoed the bigger risk being underinvesting in AI, rather than overinvesting. Training, supply, and software ecosystem constraints limit the scaling of competing products. Whether this is justification for massive Capex and FCF swings will be up to the investor. NVDA is still the prime beneficiary of the buildout, and the data suggests it’s still not feasible to reduce the order book.\n\n# Microsoft:\n\nMicrosoft is widely identified as one of the largest Nvidia buyers amongst cloud hyperscalers. Azure runs on $NVDA’s GPUs, and Wall Street uses Azure growth rates as a barometer for Data Center demand. In the recent earnings report, investors were impressed by Azure’s growth and the company reporting over 30 million paid Copilot seats. Capex fears were assuaged by seeing the ROI come in. Here’s what the print suggests for $NVDA.\n\n* **Microsoft’s CapEx Is Still Increasing**\n * Q4 FY26 CapEx came in at $35.8 billion, up slightly quarter-over-quarter from $31.9 billion, but management previously guided Q4 CapEx of >$40 billion.\n * FY2027 CapEx is projected to increase from this year due to continued robust demand. Changes in depreciation and financing terms impact the guided figure.\n * The company continues to expand its AI infrastructure buildout through Nvidia, while developing internal alternatives.\n* **Azure Beat Guidance Again & Supply Is Still the Bottleneck**\n * Azure grew 43% in Q3 FY26, above estimates calling for 40%, signaling that demand continues to outpace forecasts.\n * The CFO has explicitly noted that Azure’s current growth bottleneck is capacity, not demand, meaning $NVDA supply constraints are directly capping Azure revenue, not customer appetite.\n * Microsoft will continue to be capacity-constrained through 2027, even as it deployed over 85 datacenters in the last year.\n\n# Meta:\n\nMeta is the other company that immediately comes to mind when thinking of massive CapEx on AI infrastructure. Wall Street was spooked by Meta’s multiple revisions for FY26 CapEx in 1H, and confirmation of that figure this quarter combined with plunging FCF. The company has teetered in and out of favor due to its aggressive use of cash. Here’s what the report suggested for NVDA:\n\n* **FY26 CapEx Guidance Narrowed, Confirmed at least $130 Billion**\n * CapEx guidance is maintained from the prior range of $125–$140 billion, after raising the number the past two quarters\n * The company is optimizing for capacity and plans to train next-gen models/Agents on NVDA’s hardware.\n * Meta cannot get/spend more than they currently are, but are unwilling to cut back.\n* **Revenue is Growing Alongside Spending**\n * Revenue grew 28% year-over-year to $60.8 billion, but net income fell due to legal costs not seen in comps.\n * Meta previously announced more than 1 GW of its own custom silicon developed with Broadcom and AMD chips, to complement new NVIDIA systems in a notable “small” hedge against $NVDA’s sole-sourcing\n\n# Google:\n\nAmong NVDA’s top customers, Google is the undisputed leader in internal development of competing chips. This does not mean the company can or will completely replace Nvidia. With demand still outpacing supply and skyrocketing component costs, it is still more cost-effective to deploy a hybrid in-house + Nvidia chip strategy to get orders filled. Training complex models is still best on NVDA’s GPUs, however, Google is marketing its TPUs as a cost-effective alternative for Inference once the model is trained. TPUs are also being used to supply AI giants like Anthropic and in compute-as-a-service deals to rival NVDA. Jensen has downplayed investor fears by asserting that the GPU & CUDA ecosystem remains a generation ahead for heavy training. Here’s what the print suggested for $NVDA:\n\n* **CapEx Guidance Hits $200 Billion with Focus on Third-Party Providers**\n * A large portion of this figure is allocated to high-end Nvidia products\n * Google needs to fulfill near-term demand via Blackwell + TPUs\n* **Cloud and Backlog Growth Validates Monetization**\n * Cloud revenue grew 82% YoY to $24.8 billion. Backlog grew another $50 billion QoQ to $514 billion.\n * Google cannot satisfy its backlog with solely TPUs, validating the CapEx increase with support from strong revenue growth,\n* **Gemini 3 Models Were Mostly Trained on TPUs**\n * Worth watching for long-term effects on demand for GPUs\n * Company is engaging with Meta to provide TPUs vs GPUs\n\n# SpaceX/Tesla:\n\nTesla is in the middle of one of the biggest pivots in history for a company already worth $1 trillion. A company once focused on pioneering EVs has shifted to autonomy, robotics, and energy while deprioritizing vehicles. Now that SpaceX is also public, quarterly disclosures show a clearer picture of how Elon Musk is allocating GPU orders. Elon is a vocal supporter of NVDA and recently announced SpaceX will exclusively use Nvidia’s chips for the orbital/terrestrial AI buildout. Here’s what the report(s) suggested for NVDA:\n\n* **SpaceX Announces Exclusive Nvidia Partnership**\n * Elon Musk called Vera Rubin the best available architecture and plans to deploy Vera GPUs and CPUs across terrestrial data centers and the planned Starmind AI-1 orbital computing satellites.\n * CEO explicitly stated, “Our understanding with NVDA is that we will receive a very large percent of their GPUs next year.”\n * Direct blow to AMD as the company marketed MI450 as an alternative, and was part of the mix that is now exclusively NVDA orders.\n* **Expanding CapEx Despite Merger Rumors and Internal Product Developments**\n * SpaceX reported $18.37 billion in quarterly CapEx to fund AI compute infrastructure, while Tesla CapEx increased on AI compute and Robotics/Robotaxi spend\n * While Tesla uses internal chips in the cars, the autonomous driving model is still trained on massive NVDA clusters. Synergy between the companies in a merger is unlikely to immediately impact orders for Nvidia.\n\n# AMD (Bonus):\n\nThis is covered in the more detailed article that is public on substack. I run the same weekly cadence with more detail via a **free** substack newsletter and need to have some reason for you to go there instead of just reddit. **As a PSA there is not a TLDR on articles over there.**\n\n# TL;DR\n\n* AI infrastructure buildout is not slowing down\n* Development of alternatives alongside large NVDA purchases, hybrid approach\n* Boost from SpaceX/Tesla exclusivity announcement\n* Google is best positioned with TPU alternative\n* Suggested NVDA Q2 Earnings beat from AMD and Mega-Tech ER","offTopic":true},{"id":"f882e173-836e-41dc-9208-aa7d8b9b8715","excerpt":"Why Alphabet Paid $32B for Wiz and Palo Alto Networks Paid $25B for CyberArk. The 5 AI Security Stocks Sitting on the Next Bottlenecks. — Prefer the visual version? [The 5 Bottlenecks of AI-Era Cybersecurity. The map.](https://www.reddit.com/r/IndiaGrowthStocks/s/BvZNLyFdAh)\n\nOver the past 2-3 weeks, most cybersecurity","url":"https://www.reddit.com/r/USGrowthStocks/comments/1srhnyi/why_alphabet_paid_32b_for_wiz_and_palo_alto/","role":"request","weight":1.029465,"occurredAt":"2026-04-21T08:31:37.000Z","sourceKey":"reddit","sourceName":"Reddit","credibility":0.62,"venue":"USGrowthStocks","intent":"problem_report","painScore":0.36,"sentiment":0.39130434,"confidence":0.7569595,"matchedPatterns":["manual_process"],"statement":"They couldn't pre-approve every trade by hand, so they built systems that check every order in milliseconds and kill the bad ones before they execute.","title":"Why Alphabet Paid $32B for Wiz and Palo Alto Networks Paid $25B for CyberArk. The 5 AI Security Stocks Sitting on the Next Bottlenecks.","body":"Prefer the visual version? [The 5 Bottlenecks of AI-Era Cybersecurity. The map.](https://www.reddit.com/r/IndiaGrowthStocks/s/BvZNLyFdAh)\n\nOver the past 2-3 weeks, most cybersecurity stocks have corrected brutally, with 30-50% drawdowns across the board. The trigger was Anthropic's Mythos, which surfaced thousands of vulnerabilities in corporate software and triggered a sector-wide re-rating along with an existential threat narrative.\n\nThe reason this spooked the market is because Mythos isn't just running faster scans. It's finding logic flaws that traditional vulnerability scanners can't even detect. So basically a whole new category of exploits just became visible, and the legacy security stack wasn't built to catch any of it. I was going through these developments for the past 3 days when something interesting came up on the JPMorgan Chase earnings call.\n\nJamie Dimon specifically spoke about cybersecurity in the context of AI and mentioned their internal testing of Anthropic's Mythos project. He said Mythos has \"already exposed a lot more vulnerabilities that need to be fixed,\" and that AI has \"made it worse, made it harder.\"\n\nDimon flagged it as a system-level risk that extends to exchanges and counterparties. The same warning Treasury Secretary Bessent acted on by calling bank CEOs into an emergency meeting last week.\n\nThat's what made me pause. If the people who actually allocate the world's largest cybersecurity budgets are saying this, something structural is shifting. Cybersecurity spend isn't going down. It's just migrating to a different set of companies than the ones currently dominating the legacy categories.\n\nSo I went back to a thesis I'd been working on, the real bottlenecks of AI-era cybersecurity. The question I wanted to answer was simple. When AI agents become the dominant actors in enterprise systems, where do the real security bottlenecks form? Not the categories the industry sells, but the actual choke points where money will pool.\n\n**First, the thinking that got me here**\n\nThe current security stack was built for a world where humans are the actors. A human logs in twice a day and works at biological speed. Every product (firewalls, EDR, IAM) assumes the actor is slow, accountable and \"one-per-seat.\"\n\nNow invert it. An AI agent logs in thousands of times a minute. It works at machine speed with no natural pause. One human can spin up a thousand agents in a day. The agent's intent lives in a prompt that gets used and thrown away. No biometric, no HR lifecycle, no sleep cycle.\n\nSo the current stack breaks. This is why the market has punished so many legacy names. They are real toll booths, but they sit on roads that are getting bypassed.\n\nThe five bottlenecks I came to are below. None of them are firewalls, endpoint AV, email security, vulnerability scanning, or traditional antivirus. Those will all still exist. They will just stop being where the money pools.\n\n**The five bottlenecks and the names sitting on them:**\n\n1. **Machine Identity Infrastructure.** CyberArk (inside Palo Alto), Wiz (inside Alphabet). Public play left is PANW. Cloudflare also sits here at the network layer.\n2. **AI Runtime Inspection.** CrowdStrike, Palo Alto, Wiz (inside Google), Zscaler. Cloudflare and Rubrik also sit here.\n3. **Agent-Aware Data Access Brokerage.** Varonis Systems. Cloudflare and Rubrik also sit here.\n4. **Unified Security Telemetry.** CrowdStrike (Falcon Next-Gen SIEM).\n5. **Continuous Attestation / Agentic Audit Trail.** Rubrik.\n\nTwo patterns worth flagging upfront.\n\nRubrik sits across three bottlenecks (2, 3, 5). Partial on runtime inspection via SAGE, partial on data brokerage, strong on attestation through immutable backups plus time-travel recovery.\n\nCloudflare also sits across three bottlenecks (1, 2, 3), but it's a different shape of bet entirely, because it's not really a security company, it's the underlying network. I'll come back to that distinction at the end because it forced me to refine the framework.\n\nNow let me walk through each one.\n\n**New to the Bottleneck Strategy? Start here**: [The AI Bottleneck Strategy, Where the Real Opportunities Are](https://www.reddit.com/r/IndiaGrowthStocks/comments/1r7943y/the_ai_bottleneck_strategy_where_the_real/).\n\n**Bottleneck 1: Machine Identity Infrastructure**\n\nToday most enterprise IT is built around human users. Maybe a thousand employees logging in from a thousand laptops. Now imagine each of those employees spinning up fifty AI agents to do their work. Suddenly you have fifty thousand \"identities\" inside the company instead of one thousand. And it scales from there. Within a few years, every enterprise will have way more machine identities running around than humans.\n\nSo who issues those identities? Who verifies them? Who can shut them off the moment one goes rogue? That's the bottleneck. Whoever controls how machine identities get created and killed becomes the toll booth every single agent has to pay.\n\nThere were really only two companies operating at scale here. CyberArk (which acquired Venafi, the company that basically created the machine identity category, for $1.54B in October 2024) and Wiz (slightly different angle, more on the cloud runtime side, but adjacent).\n\nNow read this carefully because this is the whole pattern.\n\nAlphabet bought Wiz for $32B. Palo Alto bought CyberArk for $25B. So two of the five bottlenecks already got absorbed by platforms before most retail investors even noticed they were bottlenecks. This is how serious players identify future toll booths and position early. By the time it becomes obvious, the public market pure plays are gone.\n\nSo what's left to own here on the public side is PANW. I personally hold PANW at $62 split-adjusted, close to a 4-year hold now.\n\nOkta I genuinely like, but Okta is dominant in human identity, not machine identity. Whether they can transition into the machine identity world at scale is an open question I'm not confident on. Would love community input here.\n\nSide note. This whole M&A pattern (Wiz to Google, CyberArk to PANW) reminds me of Chris Mayer's *Invest Like a Dealmaker*. Mayer's whole point is to always keep a track of what's happening in private markets, what valuations they're paying, and which sectors they're allocating to, because those are the future money-making machines and runways. The cybersecurity M&A wave we're seeing right now is exactly that signal. Recommend everyone read that masterpiece.\n\n**Bottleneck 2: AI Runtime Inspection**\n\nOld security worked like a security guard at the front gate of a building. Check the ID, let the person in, you're done. The guard didn't have to follow the person around to see what they were doing inside.\n\nAI agents break that model. The agent gets through the front gate (it has valid credentials, it's logged in correctly), but then it starts doing things at machine speed inside the building. Reading thousands of files. Calling external APIs. Triggering actions in other systems. The security guard at the front gate never sees any of it.\n\nSo the new security model has to sit inside the building, watching every action the agent takes, deciding in real time whether to allow it or kill it. Same shape as what stock exchanges built when algo trading came in. They couldn't pre-approve every trade by hand, so they built systems that check every order in milliseconds and kill the bad ones before they execute.\n\nNames sitting on this. CrowdStrike via Charlotte AI, Palo Alto via Prisma and XSIAM, Wiz inside Google, and Zscaler, though I haven't placed Zscaler cleanly yet because I'm not fully sure how their SASE foundation translates to AI-era platform economics. Would love community input on Zscaler.\n\nI added CRWD recently at $360. Second addition to the position in 3 years.\n\n**Bottleneck 3: Agent-Aware Data Access Brokerage**\n\nHere's the pattern. Whenever the actors change from humans to machines, the toll booth always moves from the access path to the resource itself. This has happened before in other industries.\n\nThink about electricity. When power flowed one direction (grid to home, billed monthly), the meter at the house was enough. When solar panels and EVs created two-way flows at high frequency, the meter had to become smart and live at the resource (panel, battery, vehicle), not at the front door of the house.\n\nSame thing happened in financial markets. When humans traded by phone, the chokepoint was the broker. When algos started reading order books at machine speed, the chokepoint moved to the exchange's market data feed itself. Bloomberg and the exchange feeds became the toll booth, not the broker.\n\nSo the same pattern is now playing out with data. In a human world the network perimeter was the toll booth, because everything had to cross the network. In an agent world, agents constantly pull data from your files, databases, tools, to do their work. So the access pattern goes from one human reading one record to one agent reading ten thousand records to answer one question. So the toll booth has to move to the data itself.\n\nCleanest specialist here is Varonis Systems. Built for human compliance over 20 years, but turns out to be exactly the right foundation for the AI agent problem. They sit at the data, not at the network. SaaS transition mostly done.\n\nWorth flagging that Snowflake and Databricks are also playing in this bottleneck, but from a completely different angle. They're not AI security companies. They're data platforms. But because so much enterprise data now lives inside Snowflake and Databricks, both of them are building access governance and permission controls natively into their products. So they end up sitting on the same bottleneck, just approaching it as data platform owners rather than security specialists. Different category of bet entirely, but worth knowing if you're thinking about who actually controls the toll booth at the data layer.\n\nNo position yet on Varonis, considering it.\n\n**Bottleneck 4: Unified Security Telemetry**\n\nEvery big company has a security team that watches alerts all day. A human analyst can investigate maybe 10-20 of these in a full work day before fatigue kicks in.\n\nIn an agentic world that volume goes up 100x, because every agent generates its own activity logs at machine speed. No human team can keep up. AI agents have to run the security operations center themselves, investigating alerts in seconds instead of hours.\n\nBut an AI security agent is only as good as the data underneath it. Whoever owns the unified data layer that all these AI security agents plug into owns the bottleneck. Basically the Bloomberg Terminal of security. CrowdStrike's Falcon Next-Gen SIEM is the cleanest play. Microsoft Sentinel is the long-term threat via E5 bundling. PANW XSIAM and Splunk inside Cisco are the others.\n\nPosition covered through Crowdstrike already.\n\n**Bottleneck 5: Continuous Attestation / Agentic Audit Trail**\n\nHere's the problem. In an agentic world, one agent triggers another, which calls a tool built by some random vendor, which talks to a database somewhere. When something goes wrong, you can't trace who did what. Attribution just breaks.\n\nAnd whenever attribution breaks, the market always responds the same way. It builds an insurance and attestation layer on top. Same pattern as credit rating agencies (you can't verify every borrower, so you pay someone to rate them), code-signing certificates (you can't verify every software publisher, so you pay someone to vouch), and payment fraud networks (you can't verify every transaction, so Visa underwrites the risk).\n\nCategory barely exists yet. Rubrik is the best-positioned public name here, even though they didn't plan for it. The backup architecture they spent a decade building turns out to be exactly the right foundation for agentic attestation. Rubrik already built an insurance layer for the ransomware era. They figured out years ago that prevention alone fails and you need recovery underneath. No","offTopic":true},{"id":"ff62784b-2f97-46de-8e31-d311f981b97a","excerpt":"Why Alphabet Paid $32B for Wiz and Palo Alto Networks Paid $25B for CyberArk. The 5 AI Security Stocks Sitting on the Next Bottlenecks. — Prefer the visual version? [The 5 Bottlenecks of AI-Era Cybersecurity. The map.](https://www.reddit.com/r/IndiaGrowthStocks/s/BvZNLyFdAh)\n\nOver the past 2-3 weeks, most cybersecurity","url":"https://www.reddit.com/r/IndiaGrowthStocks/comments/1smviwh/why_alphabet_paid_32b_for_wiz_and_palo_alto/","role":"request","weight":1.0231463,"occurredAt":"2026-04-16T06:30:15.000Z","sourceKey":"reddit","sourceName":"Reddit","credibility":0.62,"venue":"IndiaGrowthStocks","intent":"problem_report","painScore":0.36,"sentiment":0.39130434,"confidence":0.75231344,"matchedPatterns":["manual_process"],"statement":"They couldn't pre-approve every trade by hand, so they built systems that check every order in milliseconds and kill the bad ones before they execute.","title":"Why Alphabet Paid $32B for Wiz and Palo Alto Networks Paid $25B for CyberArk. The 5 AI Security Stocks Sitting on the Next Bottlenecks.","body":"Prefer the visual version? [The 5 Bottlenecks of AI-Era Cybersecurity. The map.](https://www.reddit.com/r/IndiaGrowthStocks/s/BvZNLyFdAh)\n\nOver the past 2-3 weeks, most cybersecurity stocks have corrected brutally, with 30-50% drawdowns across the board. The trigger was Anthropic's Mythos, which surfaced thousands of vulnerabilities in corporate software and triggered a sector-wide re-rating along with an existential threat narrative.\n\nThe reason this spooked the market is because Mythos isn't just running faster scans. It's finding logic flaws that traditional vulnerability scanners can't even detect. So basically a whole new category of exploits just became visible, and the legacy security stack wasn't built to catch any of it. I was going through these developments for the past 3 days when something interesting came up on the JPMorgan Chase earnings call.\n\nJamie Dimon specifically spoke about cybersecurity in the context of AI and mentioned their internal testing of Anthropic's Mythos project. He said Mythos has \"already exposed a lot more vulnerabilities that need to be fixed,\" and that AI has \"made it worse, made it harder.\"\n\nDimon flagged it as a system-level risk that extends to exchanges and counterparties. The same warning Treasury Secretary Bessent acted on by calling bank CEOs into an emergency meeting last week.\n\nThat's what made me pause. If the people who actually allocate the world's largest cybersecurity budgets are saying this, something structural is shifting. Cybersecurity spend isn't going down. It's just migrating to a different set of companies than the ones currently dominating the legacy categories.\n\nSo I went back to a thesis I'd been working on, the real bottlenecks of AI-era cybersecurity. The question I wanted to answer was simple. When AI agents become the dominant actors in enterprise systems, where do the real security bottlenecks form? Not the categories the industry sells, but the actual choke points where money will pool.\n\n**First, the thinking that got me here**\n\nThe current security stack was built for a world where humans are the actors. A human logs in twice a day and works at biological speed. Every product (firewalls, EDR, IAM) assumes the actor is slow, accountable and \"one-per-seat.\"\n\nNow invert it. An AI agent logs in thousands of times a minute. It works at machine speed with no natural pause. One human can spin up a thousand agents in a day. The agent's intent lives in a prompt that gets used and thrown away. No biometric, no HR lifecycle, no sleep cycle.\n\nSo the current stack breaks. This is why the market has punished so many legacy names. They are real toll booths, but they sit on roads that are getting bypassed.\n\nThe five bottlenecks I came to are below. None of them are firewalls, endpoint AV, email security, vulnerability scanning, or traditional antivirus. Those will all still exist. They will just stop being where the money pools.\n\n**The five bottlenecks and the names sitting on them:**\n\n1. **Machine Identity Infrastructure.** CyberArk (inside Palo Alto), Wiz (inside Alphabet). Public play left is PANW. Cloudflare also sits here at the network layer.\n2. **AI Runtime Inspection.** CrowdStrike, Palo Alto, Wiz (inside Google), Zscaler. Cloudflare and Rubrik also sit here.\n3. **Agent-Aware Data Access Brokerage.** Varonis Systems. Cloudflare and Rubrik also sit here.\n4. **Unified Security Telemetry.** CrowdStrike (Falcon Next-Gen SIEM).\n5. **Continuous Attestation / Agentic Audit Trail.** Rubrik.\n\nTwo patterns worth flagging upfront.\n\nRubrik sits across three bottlenecks (2, 3, 5). Partial on runtime inspection via SAGE, partial on data brokerage, strong on attestation through immutable backups plus time-travel recovery.\n\nCloudflare also sits across three bottlenecks (1, 2, 3), but it's a different shape of bet entirely, because it's not really a security company, it's the underlying network. I'll come back to that distinction at the end because it forced me to refine the framework.\n\nNow let me walk through each one.\n\n**New to the Bottleneck Strategy? Start here**: [The AI Bottleneck Strategy, Where the Real Opportunities Are](https://www.reddit.com/r/IndiaGrowthStocks/comments/1r7943y/the_ai_bottleneck_strategy_where_the_real/).\n\n**Bottleneck 1: Machine Identity Infrastructure**\n\nToday most enterprise IT is built around human users. Maybe a thousand employees logging in from a thousand laptops. Now imagine each of those employees spinning up fifty AI agents to do their work. Suddenly you have fifty thousand \"identities\" inside the company instead of one thousand. And it scales from there. Within a few years, every enterprise will have way more machine identities running around than humans.\n\nSo who issues those identities? Who verifies them? Who can shut them off the moment one goes rogue? That's the bottleneck. Whoever controls how machine identities get created and killed becomes the toll booth every single agent has to pay.\n\nThere were really only two companies operating at scale here. CyberArk (which acquired Venafi, the company that basically created the machine identity category, for $1.54B in October 2024) and Wiz (slightly different angle, more on the cloud runtime side, but adjacent).\n\nNow read this carefully because this is the whole pattern.\n\nAlphabet bought Wiz for $32B. Palo Alto bought CyberArk for $25B. So two of the five bottlenecks already got absorbed by platforms before most retail investors even noticed they were bottlenecks. This is how serious players identify future toll booths and position early. By the time it becomes obvious, the public market pure plays are gone.\n\nSo what's left to own here on the public side is PANW. I personally hold PANW at $62 split-adjusted, close to a 4-year hold now.\n\nOkta I genuinely like, but Okta is dominant in human identity, not machine identity. Whether they can transition into the machine identity world at scale is an open question I'm not confident on. Would love community input here.\n\nSide note. This whole M&A pattern (Wiz to Google, CyberArk to PANW) reminds me of Chris Mayer's *Invest Like a Dealmaker*. Mayer's whole point is to always keep a track of what's happening in private markets, what valuations they're paying, and which sectors they're allocating to, because those are the future money-making machines and runways. The cybersecurity M&A wave we're seeing right now is exactly that signal. Recommend everyone read that masterpiece.\n\n**Bottleneck 2: AI Runtime Inspection**\n\nOld security worked like a security guard at the front gate of a building. Check the ID, let the person in, you're done. The guard didn't have to follow the person around to see what they were doing inside.\n\nAI agents break that model. The agent gets through the front gate (it has valid credentials, it's logged in correctly), but then it starts doing things at machine speed inside the building. Reading thousands of files. Calling external APIs. Triggering actions in other systems. The security guard at the front gate never sees any of it.\n\nSo the new security model has to sit inside the building, watching every action the agent takes, deciding in real time whether to allow it or kill it. Same shape as what stock exchanges built when algo trading came in. They couldn't pre-approve every trade by hand, so they built systems that check every order in milliseconds and kill the bad ones before they execute.\n\nNames sitting on this. CrowdStrike via Charlotte AI, Palo Alto via Prisma and XSIAM, Wiz inside Google, and Zscaler, though I haven't placed Zscaler cleanly yet because I'm not fully sure how their SASE foundation translates to AI-era platform economics. Would love community input on Zscaler.\n\nI added CRWD recently at $360. Second addition to the position in 3 years.\n\n**Bottleneck 3: Agent-Aware Data Access Brokerage**\n\nHere's the pattern. Whenever the actors change from humans to machines, the toll booth always moves from the access path to the resource itself. This has happened before in other industries.\n\nThink about electricity. When power flowed one direction (grid to home, billed monthly), the meter at the house was enough. When solar panels and EVs created two-way flows at high frequency, the meter had to become smart and live at the resource (panel, battery, vehicle), not at the front door of the house.\n\nSame thing happened in financial markets. When humans traded by phone, the chokepoint was the broker. When algos started reading order books at machine speed, the chokepoint moved to the exchange's market data feed itself. Bloomberg and the exchange feeds became the toll booth, not the broker.\n\nSo the same pattern is now playing out with data. In a human world the network perimeter was the toll booth, because everything had to cross the network. In an agent world, agents constantly pull data from your files, databases, tools, to do their work. So the access pattern goes from one human reading one record to one agent reading ten thousand records to answer one question. So the toll booth has to move to the data itself.\n\nCleanest specialist here is Varonis Systems. Built for human compliance over 20 years, but turns out to be exactly the right foundation for the AI agent problem. They sit at the data, not at the network. SaaS transition mostly done.\n\nWorth flagging that Snowflake and Databricks are also playing in this bottleneck, but from a completely different angle. They're not AI security companies. They're data platforms. But because so much enterprise data now lives inside Snowflake and Databricks, both of them are building access governance and permission controls natively into their products. So they end up sitting on the same bottleneck, just approaching it as data platform owners rather than security specialists. Different category of bet entirely, but worth knowing if you're thinking about who actually controls the toll booth at the data layer.\n\nNo position yet on Varonis, considering it.\n\n**Bottleneck 4: Unified Security Telemetry**\n\nEvery big company has a security team that watches alerts all day. A human analyst can investigate maybe 10-20 of these in a full work day before fatigue kicks in.\n\nIn an agentic world that volume goes up 100x, because every agent generates its own activity logs at machine speed. No human team can keep up. AI agents have to run the security operations center themselves, investigating alerts in seconds instead of hours.\n\nBut an AI security agent is only as good as the data underneath it. Whoever owns the unified data layer that all these AI security agents plug into owns the bottleneck. Basically the Bloomberg Terminal of security. CrowdStrike's Falcon Next-Gen SIEM is the cleanest play. Microsoft Sentinel is the long-term threat via E5 bundling. PANW XSIAM and Splunk inside Cisco are the others.\n\nPosition covered through Crowdstrike already.\n\n**Bottleneck 5: Continuous Attestation / Agentic Audit Trail**\n\nHere's the problem. In an agentic world, one agent triggers another, which calls a tool built by some random vendor, which talks to a database somewhere. When something goes wrong, you can't trace who did what. Attribution just breaks.\n\nAnd whenever attribution breaks, the market always responds the same way. It builds an insurance and attestation layer on top. Same pattern as credit rating agencies (you can't verify every borrower, so you pay someone to rate them), code-signing certificates (you can't verify every software publisher, so you pay someone to vouch), and payment fraud networks (you can't verify every transaction, so Visa underwrites the risk).\n\nCategory barely exists yet. Rubrik is the best-positioned public name here, even though they didn't plan for it. The backup architecture they spent a decade building turns out to be exactly the right foundation for agentic attestation. Rubrik already built an insurance layer for the ransomware era. They figured out years ago that prevention alone fails and you need recovery underneath. No","offTopic":true},{"id":"aaf6056f-72ed-4304-95c8-1812ddbc9df3","excerpt":"I mapped the 5 security bottlenecks that form when AI agents replace humans as the primary actors in enterprise systems. — Over the past 2-3 weeks, most cybersecurity stocks have corrected brutally, with 30-50% drawdowns across the board. The trigger was Anthropic's Mythos, which surfaced thousands of vulnerabilities i","url":"https://www.reddit.com/r/cybersecurity/comments/1ssgqvj/i_mapped_the_5_security_bottlenecks_that_form/","role":"request","weight":0.98133403,"occurredAt":"2026-04-22T09:45:12.000Z","sourceKey":"reddit","sourceName":"Reddit","credibility":0.62,"venue":"cybersecurity","intent":"problem_report","painScore":0.36,"sentiment":0.4090909,"confidence":0.7215691,"matchedPatterns":["manual_process"],"statement":"They couldn't pre-approve every trade by hand, so they built systems that check every order in milliseconds and kill the bad ones before they execute.","title":"I mapped the 5 security bottlenecks that form when AI agents replace humans as the primary actors in enterprise systems.","body":"Over the past 2-3 weeks, most cybersecurity stocks have corrected brutally, with 30-50% drawdowns across the board. The trigger was Anthropic's Mythos, which surfaced thousands of vulnerabilities in corporate software and triggered a sector-wide re-rating along with an existential threat narrative.\n\nThe reason this spooked the market is because Mythos isn't just running faster scans. It's finding logic flaws that traditional vulnerability scanners can't even detect. So basically a whole new category of exploits just became visible, and the legacy security stack wasn't built to catch any of it. I was going through these developments for the past 3 days when something interesting came up on the JPMorgan Chase earnings call.\n\nJamie Dimon specifically spoke about cybersecurity in the context of AI and mentioned their internal testing of Anthropic's Mythos project. He said Mythos has \"already exposed a lot more vulnerabilities that need to be fixed,\" and that AI has \"made it worse, made it harder.\"\n\nDimon flagged it as a system-level risk that extends to exchanges and counterparties. The same warning Treasury Secretary Bessent acted on by calling bank CEOs into an emergency meeting last week.\n\nThat's what made me pause. If the people who actually allocate the world's largest cybersecurity budgets are saying this, something structural is shifting. Cybersecurity spend isn't going down. It's just migrating to a different set of companies than the ones currently dominating the legacy categories.\n\nSo I went back to a thesis I'd been working on, the real bottlenecks of AI-era cybersecurity. The question I wanted to answer was simple. When AI agents become the dominant actors in enterprise systems, where do the real security bottlenecks form? Not the categories the industry sells, but the actual choke points where money will pool.\n\n**First, the thinking that got me here**\n\nThe current security stack was built for a world where humans are the actors. A human logs in twice a day and works at biological speed. Every product (firewalls, EDR, IAM) assumes the actor is slow, accountable and \"one-per-seat.\"\n\nNow invert it. An AI agent logs in thousands of times a minute. It works at machine speed with no natural pause. One human can spin up a thousand agents in a day. The agent's intent lives in a prompt that gets used and thrown away. No biometric, no HR lifecycle, no sleep cycle.\n\nSo the current stack breaks. This is why the market has punished so many legacy names. They are real toll booths, but they sit on roads that are getting bypassed.\n\nThe five bottlenecks I came to are below. None of them are firewalls, endpoint AV, email security, vulnerability scanning, or traditional antivirus. Those will all still exist. They will just stop being where the money pools.\n\n**The five bottlenecks and the names sitting on them:**\n\n1. **Machine Identity Infrastructure.** CyberArk (inside Palo Alto), Wiz (inside Alphabet). Public play left is PANW. Cloudflare also sits here at the network layer.\n2. **AI Runtime Inspection.** CrowdStrike, Palo Alto, Wiz (inside Google), Zscaler. Cloudflare and Rubrik also sit here.\n3. **Agent-Aware Data Access Brokerage.** Varonis Systems. Cloudflare and Rubrik also sit here.\n4. **Unified Security Telemetry.** CrowdStrike (Falcon Next-Gen SIEM).\n5. **Continuous Attestation / Agentic Audit Trail.** Rubrik.\n\nTwo patterns worth flagging upfront.\n\nRubrik sits across three bottlenecks (2, 3, 5). Partial on runtime inspection via SAGE, partial on data brokerage, strong on attestation through immutable backups plus time-travel recovery.\n\nCloudflare also sits across three bottlenecks (1, 2, 3), but it's a different shape of bet entirely, because it's not really a security company, it's the underlying network. I'll come back to that distinction at the end because it forced me to refine the framework.\n\nNow let me walk through each one.\n\n*This analysis is built on a broader framework I've been developing called the Bottleneck Strategy, which maps where value concentrates when industries go through structural transitions.*\n\n**Bottleneck 1: Machine Identity Infrastructure**\n\nToday most enterprise IT is built around human users. Maybe a thousand employees logging in from a thousand laptops. Now imagine each of those employees spinning up fifty AI agents to do their work. Suddenly you have fifty thousand \"identities\" inside the company instead of one thousand. And it scales from there. Within a few years, every enterprise will have way more machine identities running around than humans.\n\nSo who issues those identities? Who verifies them? Who can shut them off the moment one goes rogue? That's the bottleneck. Whoever controls how machine identities get created and killed becomes the toll booth every single agent has to pay.\n\nThere were really only two companies operating at scale here. CyberArk (which acquired Venafi, the company that basically created the machine identity category, for $1.54B in October 2024) and Wiz (slightly different angle, more on the cloud runtime side, but adjacent).\n\nNow read this carefully because this is the whole pattern.\n\nAlphabet bought Wiz for $32B. Palo Alto bought CyberArk for $25B. So two of the five bottlenecks already got absorbed by platforms before most people even noticed they were bottlenecks. This is how the consolidation wave works in security. The platform players identify future chokepoints and acquire them before they become obvious.\n\nSo what's left as an independent player here on the public side is PANW.\n\nOkta I genuinely like, but Okta is dominant in human identity, not machine identity. Whether they can transition into the machine identity world at scale is an open question I'm not confident on. Would love community input here.\n\n**Bottleneck 2: AI Runtime Inspection**\n\nOld security worked like a security guard at the front gate of a building. Check the ID, let the person in, you're done. The guard didn't have to follow the person around to see what they were doing inside.\n\nAI agents break that model. The agent gets through the front gate (it has valid credentials, it's logged in correctly), but then it starts doing things at machine speed inside the building. Reading thousands of files. Calling external APIs. Triggering actions in other systems. The security guard at the front gate never sees any of it.\n\nSo the new security model has to sit inside the building, watching every action the agent takes, deciding in real time whether to allow it or kill it. Same shape as what stock exchanges built when algo trading came in. They couldn't pre-approve every trade by hand, so they built systems that check every order in milliseconds and kill the bad ones before they execute.\n\nNames sitting on this. CrowdStrike via Charlotte AI, Palo Alto via Prisma and XSIAM, Wiz inside Google, and Zscaler, though I haven't placed Zscaler cleanly yet because I'm not fully sure how their SASE foundation translates to AI-era runtime inspection. Would love community input on Zscaler.\n\n**Bottleneck 3: Agent-Aware Data Access Brokerage**\n\nHere's the pattern. Whenever the actors change from humans to machines, the toll booth always moves from the access path to the resource itself. This has happened before in other industries.\n\nThink about electricity. When power flowed one direction (grid to home, billed monthly), the meter at the house was enough. When solar panels and EVs created two-way flows at high frequency, the meter had to become smart and live at the resource (panel, battery, vehicle), not at the front door of the house.\n\nSame thing happened in financial markets. When humans traded by phone, the chokepoint was the broker. When algos started reading order books at machine speed, the chokepoint moved to the exchange's market data feed itself. Bloomberg and the exchange feeds became the toll booth, not the broker.\n\nSo the same pattern is now playing out with data. In a human world the network perimeter was the toll booth, because everything had to cross the network. In an agent world, agents constantly pull data from your files, databases, tools, to do their work. So the access pattern goes from one human reading one record to one agent reading ten thousand records to answer one question. So the toll booth has to move to the data itself.\n\nCleanest specialist here is Varonis Systems. Built for human compliance over 20 years, but turns out to be exactly the right foundation for the AI agent problem. They sit at the data, not at the network. SaaS transition mostly done.\n\nWorth flagging that Snowflake and Databricks are also playing in this bottleneck, but from a completely different angle. They're not AI security companies. They're data platforms. But because so much enterprise data now lives inside Snowflake and Databricks, both of them are building access governance and permission controls natively into their products. So they end up sitting on the same bottleneck, just approaching it as data platform owners rather than security specialists. Different category of bet entirely, but worth knowing if you're thinking about who actually controls the toll booth at the data layer.\n\n**Bottleneck 4: Unified Security Telemetry**\n\nEvery big company has a security team that watches alerts all day. A human analyst can investigate maybe 10-20 of these in a full work day before fatigue kicks in.\n\nIn an agentic world that volume goes up 100x, because every agent generates its own activity logs at machine speed. No human team can keep up. AI agents have to run the security operations center themselves, investigating alerts in seconds instead of hours.\n\nBut an AI security agent is only as good as the data underneath it. Whoever owns the unified data layer that all these AI security agents plug into owns the bottleneck. Basically the Bloomberg Terminal of security. CrowdStrike's Falcon Next-Gen SIEM is the cleanest play. Microsoft Sentinel is the long-term threat via E5 bundling. PANW XSIAM and Splunk inside Cisco are the others.\n\n**Bottleneck 5: Continuous Attestation / Agentic Audit Trail**\n\nHere's the problem. In an agentic world, one agent triggers another, which calls a tool built by some random vendor, which talks to a database somewhere. When something goes wrong, you can't trace who did what. Attribution just breaks.\n\nAnd whenever attribution breaks, the market always responds the same way. It builds an insurance and attestation layer on top. Same pattern as credit rating agencies (you can't verify every borrower, so you pay someone to rate them), code-signing certificates (you can't verify every software publisher, so you pay someone to vouch), and payment fraud networks (you can't verify every transaction, so Visa underwrites the risk).\n\nCategory barely exists yet. Rubrik is the best-positioned public name here, even though they didn't plan for it. The backup architecture they spent a decade building turns out to be exactly the right foundation for agentic attestation. Rubrik already built an insurance layer for the ransomware era. They figured out years ago that prevention alone fails and you need recovery underneath. Now the same logic applies to agent actions, and the same architecture handles both. Agent takes an action, you have a verifiable record before and after, you can roll it back. Their bet is that fast reversibility beats perfect prevention in the agentic world. Agent Rewind is the product expression of that thesis.\n\n**Now the company that doesn't fit this list, and the framework refinement worth talking about**\n\nCloudflare doesn't sit on one bottleneck. It sits on three. Strong on Bottleneck 2 (AI runtime inspection, because they're inline by default since the traffic already flows through them, which is a structural advantage CRWD and Rubrik don't have). Medium-strong on Bottleneck 3 (network-layer brokerage between agents and tools, complementary to what Varonis does at the file level). Medium on Bottleneck 1 (Cloudflare Access acts as the login and au","offTopic":true},{"id":"d355fe80-cd8e-4bf2-836d-3b9d2cfd8b7f","excerpt":"Big pharma and managed care thesis, stagflation, and Wyckoff juxtaposition. — This post is a part 2 to the post below.\n\n [https://www.reddit.com/r/Healthcare\\_Anon/comments/1p8mtfb/parallelanalogue\\_of\\_dot\\_com\\_bubble\\_fed\\_rat\\_cuts/](https://www.reddit.com/r/Healthcare_Anon/comments/1p8mtfb/parallelanalogue_of_dot_","url":"https://www.reddit.com/r/Healthcare_Anon/comments/1pax7jt/big_pharma_and_managed_care_thesis_stagflation/","role":"demand","weight":0.9704706,"occurredAt":"2025-11-30T23:42:37.000Z","sourceKey":"reddit","sourceName":"Reddit","credibility":0.62,"venue":"Healthcare_Anon","intent":"tool_discovery","painScore":0.45294118,"sentiment":-0.38235295,"confidence":0.66793525,"matchedPatterns":["cant_find"],"statement":"Many of those individuals cannot find a new position to replace their old job.","title":"Big pharma and managed care thesis, stagflation, and Wyckoff juxtaposition.","body":"This post is a part 2 to the post below.\n\n [https://www.reddit.com/r/Healthcare\\_Anon/comments/1p8mtfb/parallelanalogue\\_of\\_dot\\_com\\_bubble\\_fed\\_rat\\_cuts/](https://www.reddit.com/r/Healthcare_Anon/comments/1p8mtfb/parallelanalogue_of_dot_com_bubble_fed_rat_cuts/)\n\nAs should have been mentioned in all of my posts, this is my opinion and thesis. It should not be used as financial advice, and you should be doing the thinking and research on your own too.\n\nWith that said, I want to continue from where we left off by talking about how interest rate behaved during the dot-com bubble vs what’s happening now in the AI bubble, and why today's setup is far more complicated and dangerous. Additionally, I am writing this post over several days, so please forgive me if I am repeating ideas or sound like I’m rambling.\n\nDuring the dot-com bubble (1999-2002), the fed tightened into the mania. From 1999 to early 2000, there were six consecutive rate hikes that peaked at around 6.5%. This is what caused the bubble to burst. After the bubble burst, the Fed cut aggressively—lowering the rate from 6.5% to 1% from 2001 to 2003. This allowed capital to rotate into defensive positions, the economy had a mild recession, and the market bottomed out without a full credit meltdown. CPI was tame, so the Fed had full freedom to slash rates, and lowering rates helped stabilize the market without causing inflation panic.\n\nThe crisis was equity-driven, not credit-driven. The consumers were not over-leveraged, and the credit markets were healthy.\n\nThe AI bubble and interest rate dynamic is far messier. The Fed already raised aggressively to control inflation—going from 0% to above 5%. To give context, this is the highest/fastest tightening in decades. Yet, the AI bubble inflated despite high rates, showing extreme speculative demand. However, unlike 2000 inflation is still “sticky.” You hear this word a lot. CPI still above 2% with service inflation refusing to go down and housing inflation stays elevated. Wage inflation is moderating but not collapsing. The Fed cannot safely cut rates the way they did in 2001–2003. Then we have the issue of credit stress rising. Auto loan delinquencies at record highs, and credit card defaults rising. You can find this information here.\n\n[https://ycharts.com/indicators/us\\_credit\\_card\\_accounts\\_late\\_by\\_90\\_days](https://ycharts.com/indicators/us_credit_card_accounts_late_by_90_days)\n\nStudent loan repayments are restarting, and commercial real estate is under pressure. One of the more interesting things that people don’t talk about are the high-paying job layoffs that are happening right now. Many of those individuals cannot find a new position to replace their old job. What do you think will happen in 6 months when those guys can’t find a new job with the same pay? They have to file for “hardship relief,” forbearance, grace periods, or payment plans. This will buy them 90 days before they start hitting the default zone. This might set off a housing crisis, but we need more confirmation. So we’re not there yet.\n\nBack to what we’re saying, the Fed is basically boxed in. If they cut too early, inflation re-accelerates. If they don’t cut, unemployment rises. This is the reason why I’m betting that they will cut rate in December. If AI continues replacing workers, unemployment rises even faster. This is the 1970s’ dilemma of stagflation risk. The Tech/AI stocks are overvalued. If the economy is weakened, Capex will slow down, and earnings will eventually disappoint. In turn, this will cause credit deterioration to accelerate, consumers to stop spending, and housing to freeze.\n\nAI stocks depend heavily on future earnings, which will get crushed when real yields and discount rates remain high. Liquidity will dry up, and demand will weaken. The dot-com bubble only had 1 problem. The AI bubble have three:\n\n1.      1970s inflation & policy errors\n\n2.      2000 tech bubble valuation madness\n\n3.      2008 consumer credit stress\n\nThe AI bubble unwinding will be slower, ugliers, and harder to stop because we have a hybrid crisis:\n\n1.      Equity correction (like 2000)\n\n2.      Consumer credit deterioration (like 2008)\n\n3.      Stagflation (like 1970s)\n\n4.      Weak job market (AI displacement)\n\n5.      Limited policy tools (Fed constrained)\n\nHonestly, what do you do in this scenario?\n\nThis is why I am advocating for the investment in big pharma and managed care (health insurers)—after the crash—because these guys tend to be the two of the strongest sectors during crises. They don’t win because things are good. They win because they survive when everything else breaks.\n\nBig pharma is a safe heaven because the demand never collapses. Regardless of what happen, people still need cancer drugs, diabetes meds, autoimmune treatmetns, insulin, vaccines, and heart disease meds. It doesn’t matter if unemployment rises, credit defaults spike, inflation eats consumers alive, or tech collapses. Pharma is a non-cyclical demand. The current tech boom depends on money. Pharma depends on illness which sadly does not go away in a recession. When inflation is high, companies without pricing power get destroyed. Pharma is one of the few industries where prices can rise, and they can shift to higher-margin drugs. The government often absorbs the costs, and this protects margins when input costs rise. Even when the U.S. economy collapses, they are still selling their drugs to Europe, Asia, and Latin America. They are not dependent on the U.S. credit cycles.\n\nMost people don’t think about this, but big pharma is really boring, but they are really safe. They have low debt, massive cash reserves, strong free cash flow, and long-term revenue visibility. In a liquidity crisis, companies with cash survive—and get rewarded. I also think that big pharma are assholes, but it doesn’t change the fact that they benefit a whole lot when the markets crash. When the economy eats shit, biotechs are the first to die, and their valuation will drop. Big pharma often uses the massive cash reserves to buy the biotechs at discounts. In short, downturns create another growth engine for them.\n\n \n\nAs for healthcare, although they are not as immune as big pharma, they have many powerful defensive traits because healthcare spending is non-negotiable. People can’t just skip dialysis, emergency care, chronic disease treatment, hospital visits, and cancer treatments and screenings. Managed care sit at the center of this. Premiums don’t disappear just because the economy weakens. People such as employers, the government, and those receiving subsidies, Medicaid, and Medicare Advantage still have to pay. I skipped ACA because that is in the air at the moment. If history has shown us anything, government programs expand during crises. Medicaid enrollment tend to increase while Medicare Advantage stay intact. The reason why Medicaid enrollment increases is because the disabled and low-income populations swell. CNC and MOH (Medicaid-heavy) often get more members during economic stress. However, please keep in mind that HR. 1 is introducing huge cuts and barriers to access care. The scenario I mentioned happened in 2001, 2008, and 2020.\n\nUNH, HUM, CNC, MOH, CLOV behave like healthcare utilities. They are boring, predictable, defensive, and has repeatable cash flow. This is why institutions rotate into during uncertainty. I won’t talk about Medical Loss Ratio here, but insurers benefit from population aging too. Medicare Advantage enrollment is structurally rising due to baby boombers aging into MA, and seniors prefer managed care for simplicity. Their enrollment has been growing 5-7% per year. This is a secular tailwind independent of the macro picture.\n\nFor juxtaposition purposes, Tech needs low rates, strong liquidity, and strong consumer spending. All of which disappear in the crisis. However, Big Pharma and Managed Care are the opposite of tech. They are cheap compared to AI names, defensive cash flow, essential demand, anti-cyclical enrollment, and the government backed their revenue streams.\n\nFor Big Pharma my bets are on LLY, PFE (maybe), MRK, JNJ, NVS, RHHBY, ABBV, NVO (Yes NVO). \n\nFor larger diversified insurers, UNH is still king.\n\nFor Medicaid-heavy insurers, I would go with CNC, MOH.\n\nFor my favorite and medium-risk company, MA-focused newer entrants (CLOV). I’m super bias about this guy because my average cost is like $1 so… I’m not selling it.\n\nPlease remember, I’m not telling you to buy these companies right now. I’m pointing out that these sectors tend to perform well during a crisis, and their stock prices will likely be much more attractive when the market corrects. That’s when they become true value-investing opportunities—strong companies at discounted prices, backed by stable long-term fundamentals.\n\nNow for the fun part. As of the writing of this post, I saw two headlines over the Thanksgiving weekend, which I think are confirmations for the impending problems we will be seeing. They look like two contracting ideas, but they are not. They actually suggest that we have a fragile consumer base.\n\n**Black Friday shoppers spent billions despite wider economic uncertainty**\n\n[https://www.nbcnews.com/business/economy/black-friday-shoppers-spent-billions-rcna246456](https://www.nbcnews.com/business/economy/black-friday-shoppers-spent-billions-rcna246456)\n\n“Adobe Analytics, which tracks e-commerce, said U.S. consumers spent a record $11.8 billion online Friday, marking a 9.1% jump from last year. Traffic particularly piled up between the hours of 10 a.m. and 2 p.m. local time nationwide, when $12.5 million passed through online shopping carts every minute.”\n\n**Seasonal hiring offers little reprieve for labor market woes**\n\n[https://finance.yahoo.com/news/seasonal-hiring-offers-little-reprieve-for-labor-market-woes-110044972.html](https://finance.yahoo.com/news/seasonal-hiring-offers-little-reprieve-for-labor-market-woes-110044972.html)\n\n“Challenger, Gray & Christmas said [in its most recent labor report](https://www.challengergray.com/blog/october-challenger-report-153074-job-cuts-on-cost-cutting-ai/) that seasonal hiring plans through October were at their lowest since the global outplacement firm began tracking them in 2012.\n\nThe National Retail Federation, a trade group, also said in a press call earlier this month that while strong consumer spending was expected to persist through the holiday season, plans to bring on extra staff could be at “the lowest level in more than 15 years.” Retailers were expected to bring on 265,000 to 365,000 seasonal workers, compared to 442,000 in 2024.”\n\nWhat the data tell us is according to recent reports, this year’s holiday-season hiring—historically a buffer for retail workers and a boost to household income—is expected to be the lowest in 15 years. This mirrors what other macro signals are showing: rising layoffs, labor-market softness, and increasing unemployment risk.\n\n[https://www.newsfromthestates.com/article/shoppers-retailers-and-seasonal-workforce-confront-new-economic-normal](https://www.newsfromthestates.com/article/shoppers-retailers-and-seasonal-workforce-confront-new-economic-normal)\n\n[https://www.aol.com/finance/feds-beige-book-shows-cooler-194701688.html](https://www.aol.com/finance/feds-beige-book-shows-cooler-194701688.html)\n\nDespite the labor softness, holiday-season retail—especially online—is posting robust numbers (record or near-record sales in some cases). Part of the spending is driven by payment plans like “buy now, pay later” (BNPL), which allow people to make purchases without paying full price up front. This suggests many households are stretching to keep consumption going even while incomes stagnate or fall. When spending is up but incomes and hiring are weak, it often means households are financing consumption with debt or deferred payments, not by real income growth. That’s a classic stress build-up.\n\nBNPL and credit-card debt can balloon fast if inco","offTopic":true},{"id":"f4efb353-67bc-49ff-8df4-c60d08343867","excerpt":"The E-com Logistics Weekly • March 19 – March 26, 2026 — Welcome to this week’s edition of E-com Logistics Weekly! While the global tariff war and the Middle East shipping crisis continue to dominate the headlines, the underlying mechanics of both situations shifted dramatically over the past seven days.\n\nBeyond global","url":"https://www.reddit.com/r/HermesLinesQA/comments/1s48d7o/the_ecom_logistics_weekly_march_19_march_26_2026/","role":"pain","weight":0.9565173,"occurredAt":"2026-03-26T14:03:59.000Z","sourceKey":"reddit","sourceName":"Reddit","credibility":0.62,"venue":"HermesLinesQA","intent":"problem_report","painScore":0.62736845,"sentiment":-0.36842105,"confidence":0.5877693,"matchedPatterns":["frustrating"],"statement":"This week, the situation has mutated into something arguably more frustrating for Western commerce: a selective toll booth.","title":"The E-com Logistics Weekly • March 19 – March 26, 2026","body":"Welcome to this week’s edition of E-com Logistics Weekly! While the global tariff war and the Middle East shipping crisis continue to dominate the headlines, the underlying mechanics of both situations shifted dramatically over the past seven days.\n\nBeyond global trade, we are tracking a historic uncoupling between Amazon and the USPS, the abrupt death of major AI and Metaverse projects, and a very real discussion about whether the \"AI Bubble\" is about to trigger a 2008-style recession.\n\nLet’s dive in.\n\n# Trade & Tariffs: The \"Pragmatic\" Shift and the 301 Race\n\nThe chaos of the $166 billion IEEPA tariff refund mandate is still rippling through Washington, but the administration is attempting to change the narrative. According to Politico, officials are now pushing a \"pragmatic\" approach to the refunds, trying to cool the operational panic. Trade expert Greta Peisch noted that the response has been surprisingly measured: “To date, the government has actually been pretty pragmatic. They are arguing that they need a little bit of time to set up a system to process the volume of refunds that are at issue here... My view is it is better than expected.”\n\nHowever, this pragmatism on refunds is happening while the administration simultaneously doubles down on the broader trade war. On Wednesday at Economy Summit in Washington, Peter Navarro confirmed that President Trump still fully intends to lock in his current set of global tariffs at a flat 15 percent. “It has happened, at least it’s in process to happen,” Navarro stated, defending the controversial Section 122 surcharge.\n\nMeanwhile, the real long-term threat to importers remains the rapidly advancing Section 301 investigations. Legal analysts across JD Supra and the Harvard Law School Forum on Corporate Governance are warning companies to take immediate action, noting that the new 301 tariffs are coming fast and will severely impact 2025 and 2026 corporate incentives. The legal team at Katten Muchin Rosenman LLP reinforced this urgency, stating: “We strongly encourage our clients to consult with legal counsel to stay informed of the latest changes and to assess the potential impact of these evolving tariff policies on their businesses and supply chains.” \n \nThe manufacturing sector is already feeling the squeeze. The compounding effects of these trade wars are dragging heavily on domestic manufacturing outputs. Interestingly, there is a stark divide in how the economic fallout is being forecasted. Investment Executive reports that tariff-hit industries are actively struggling as this new trade war escalates, stating that “industries like metal production, lumber and automobiles continue to face steep duties more than a year after U.S. President Donald Trump upended the global status quo (...)” The publication notes that companies have been forced to cut staff, pull back on production, and push for government intervention as the heavy duties continue to shake crucial trade relationships.\n\nIn jarring contrast, according to Yicai Global, the Chief Economist at the WTO surprisingly said that “limited disruption is expected from tariff changes this year.” For operators on the ground, the WTO's optimism feels completely detached from the reality of skyrocketing landed costs.\n\n# The Strait of Hormuz Becomes a Geopolitical Toll Booth\n\nLast week, the Strait of Hormuz was effectively a closed blockade. This week, the situation has mutated into something arguably more frustrating for Western commerce: a selective toll booth.\n\nAccording to reports from Reuters and The Times, Iran has announced that \"non-hostile\" ships can now transit the strait, provided they coordinate with Iranian authorities and do not support acts of aggression. But who actually decides what is hostile? As noted by the South China Morning Post, China-owned vessels are already securing rare, uninterrupted transits through the choke point, while the West largely remains locked out.\n\nThis selective enforcement has created a massive, asymmetric advantage. Al Jazeera highlights the situation as a profound international crisis, warning that the militarization of this central global energy artery risks immediate, widespread supply shocks. Meanwhile, DW reports that an Iranian lawmaker claims Tehran is quietly charging tankers up to $2 million for safe passage through the Strait of Hormuz. \nPeter Sand, chief analyst at Xeneta, says that while the fee is exorbitant, the sheer danger of the passage remains the primary deterrent for most carriers. However, he noted that the willingness of desperate, fuel-dependent nations to pay this \"small final premium\", on top of sky-high war insurance, underscores just how critical the strait is.\n\nFor Western e-commerce freight, the reality is grim: the agonizingly long, expensive detours around Africa will continue to drive up your container costs, while Eastern competitors get a fast, subsidized pass through the Persian Gulf.\n\n# Logistics: Amazon Chokes the USPS\n\nThe United States Postal Service is in a financial death spiral. According to a recent House hearing transcribed by Rev and reporting by CNN and Yahoo Finance, the USPS has already lost over $1.3 billion in its current fiscal period, triggering a full-blown financial crisis. The situation is so dire that Postmaster General David Steiner warned lawmakers the agency will run out of cash within a year without congressional intervention. “At our current rate, we’ll be out of cash in less than 12 months. So in about a year from now, the postal service would be unable to deliver the mail,” Steiner stated.\n\nMaking matters significantly worse is a strategic pivot by the USPS's biggest customer. As reported in a Wall Street Journal exclusive, Amazon is planning a drastic cut in the volume of packages it sends through the Post Office, aiming to reduce its postal volume by at least two-thirds by this fall.\n\nAccording to CNBC, the e-commerce giant is currently rolling out new 1-hour and 3-hour delivery tests utilizing its own localized fulfillment nodes. Meanwhile, legacy carriers are retreating to cut costs; Yahoo Finance notes that FedEx is actively shuttering parcel facilities in New York. If you rely heavily on USPS for your DTC fulfillment, prepare for potential aggressive price hikes or severe service degradation as they bleed critical volume to Amazon.\n\n# Macro: Are We Hitting an AI-Driven 2008?\n\nEconomic indicators are flashing red, and it is not just because of the war in Iran. The specter of a 2008-style recession is back, driven heavily by fears that the multi-trillion-dollar \"AI Bubble\" is beginning to burst.\n\nYahoo Finance recently highlighted that Peter Schiff and other analysts are experiencing \"Gold Déjà Vu,\" warning that recession fears are fully back on the table. We are seeing classic consumer retreat signals: Costco leadership recently noted they see a massive opportunity as Americans can no longer afford to eat out at restaurants and are buying bulk groceries instead. In the corporate finance sector, The Logic reports that Shopify is heavily leaning into its merchant loan division (Shopify Capital) as total debt loads in the e-commerce space shift.\n\nBut the real story is the tech sector's reality check. Tech CEOs are making increasingly desperate statements to justify massive valuations and recent layoffs. The CEO of Perplexity and the billionaire CEO of Palantir recently gave interviews dismissing the tech layoffs and hyping up their AI moats. However, their rhetoric feels like selling thin air when compared to actual market performance and mounting regulatory threats.\n\nIn a direct strike against the physical infrastructure needed to keep this bubble inflated, progressive lawmakers led by Senator Bernie Sanders just introduced the Artificial Intelligence Data Center Moratorium Act. The sweeping proposal seeks an immediate nationwide halt on the construction of all new AI data centers, aiming to prevent the industry from overwhelming local power grids and skyrocketing consumer utility costs.\n\nMeanwhile, on the software side, the bubble is already visibly cracking. OpenAI just abruptly pulled the plug and shut down SORA, its highly touted AI video platform, less than a year after launch, despite Sam Altman previously claiming it would redefine the company's roadmap. Similarly, CNBC reports that Meta has officially shut down its VR Metaverse (Horizon Worlds) after burning billions of dollars.\n\nEven in e-commerce, the AI magic pill is failing. Search Engine Land reported that Walmart’s highly anticipated ChatGPT checkout integration actually converted worse than traditional search. While an interview shows Shopify executives still believe AI agents will \"change everything,\" the actual data suggests consumers are rejecting these half-baked AI tools. The tech giants promised a revolution to justify their valuations; instead, they are facing federal moratoriums and quietly shuttering projects. As analysts like Peter Schiff warn of a 2008-style pullback, it leaves the market wondering if this AI-driven bubble is about to bring the broader economy down with it.\n\nWe will keep a close eye on the Section 301 hearing dates as they approach. Until then, stay nimble. See you all next week.\n\nNote: This information is intended to inform Hermeslines clients and partners about industry developments, including decisions of courts and administrative bodies. Nothing in this update should be construed as legal advice, a legal opinion, or customs consulting. Readers should not act upon the information contained in this alert without seeking the advice of a licensed customs broker or legal counsel. Views expressed are those of the author(s) and do not necessarily reflect the official policy of Hermeslines or its clients. Prior results do not guarantee a similar outcome. Hermeslines does not claim ownership of the original reporting; please refer to the linked sources for full articles and original attribution. This content is intended for commentary, news reporting, and educational purposes under the Fair Use provisions of Section 107 of the Copyright Act 1976. This article is for informational purposes and does not constitute legal or customs advice.\n\n# Reference List\n\nTariffs & Trade Policy\n\n* Harvard Law School Forum on Corporate Governance:[ Impact of Tariffs on 2025 and 2026 Incentives](https://corpgov.law.harvard.edu/2026/03/16/impact-of-tariffs-on-2025-and-2026-incentives/)\n* Politico:[ Trump Administration Pragmatic Tariff Refunds](https://www.politico.com/news/2026/03/25/trump-administration-pragmatic-tariff-refunds-00844262)\n* Politico:[ Navarro Trump Tariffs 15 Percent](https://www.politico.com/news/2026/03/25/navarro-trump-tariffs-15-percent-00843828)\n* Investment Executive:[ Tariff Hit Industries Struggling as Trade War Drags](https://www.investmentexecutive.com/news/tariff-hit-industries-struggling-as-trade-war-drags-into-second-year/)\n* Yicai Global:[ Limited Disruption Expected From Tariff Changes, WTO Says](https://www.yicaiglobal.com/news/limited-disruption-is-expected-from-tariff-changes-this-year-wto-chief-economist-says)\n* JD Supra:[ New 301 Tariffs Coming: Immediate Action Required](https://www.jdsupra.com/legalnews/new-301-tariffs-coming-immediate-action-6894236/)\n* JD Supra:[ The Evolving Landscape of Presidential Tariffs](https://www.jdsupra.com/legalnews/the-evolving-landscape-of-presidential-8514829/)\n* Tax Foundation:[ Congress, Tariffs, and Sec 122](https://taxfoundation.org/oped/congress-tariffs-sec-122/)\n* Trade Compliance Hub:[ Trump 2.0 Tariff Tracker](https://www.tradecomplianceresourcehub.com/2026/03/24/trump-2-0-tariff-tracker/)\n\nStrait of Hormuz & Geopolitics\n\n* Yahoo Finance:[ Iran Testing Selective Strait of Hormuz](https://finance.yahoo.com/sectors/energy/articles/iran-testing-selective-strait-hormuz-213500476.html)\n* Reuters:[ Iran Says Non-Hostile Ships Can Transit Strait](https://www.reuters.com/world/middle-east/iran-says-non-hostile-ships-can-t","offTopic":true},{"id":"8215e029-6965-4607-bb2e-9ac4c572b84f","excerpt":"Weekend Digest (5/31/26): Last Day (SA), Earnings, Market Themes & Final Word — Hope you're all having a fantastic weekend! Last day of March!\n\nThis may be my best market-related weekend digest yet.\n\n**Last Day - StockAnalysis**\n\nJust a quick note that if you haven't taken advantage of the the **FREE** offer from [Stoc","url":"https://www.reddit.com/r/InnerCircleInvesting/comments/1tsyv34/weekend_digest_53126_last_day_sa_earnings_market/","role":"request","weight":0.9499472,"occurredAt":"2026-05-31T15:45:35.000Z","sourceKey":"reddit","sourceName":"Reddit","credibility":0.62,"venue":"InnerCircleInvesting","intent":"feature_request","painScore":0.3639604,"sentiment":-0.00990099,"confidence":0.69646245,"matchedPatterns":["missing_feature"],"statement":"If you all aren't playing along with my references, you're missing most of the fun of these digests.","title":"Weekend Digest (5/31/26): Last Day (SA), Earnings, Market Themes & Final Word","body":"Hope you're all having a fantastic weekend! Last day of March!\n\nThis may be my best market-related weekend digest yet.\n\n**Last Day - StockAnalysis**\n\nJust a quick note that if you haven't taken advantage of the the **FREE** offer from [StockAnalysis.com](https://www.reddit.com/r/InnerCircleInvesting/comments/1td2vsd/stockanalysiscom_new_offer/), it ends tonight. Don't want to spam the sub with it. It's the best offer I've seen from them yet and I don't know if they'll be offering another one. Get the free month, start your watchlists, your analysis and decide a month from now if you want to continue. Absolute slam dunk of a service.\n\n**Earnings**\n\nWe have one more week of notable earnings with a few names I'm watching:\n\nhttps://preview.redd.it/37ug8atd5h4h1.png?width=1195&format=png&auto=webp&s=949161115ab756c525ca209025b302d5cd3dee51\n\nObviously I'll be watching $PANW $CRWD and especially $AVGO most of all.\n\nBeyond that $CRDO has my interest and has had a powerful move off of recent lows of $87. We were following it but I never purchased. Dumb. It popped on a valuation screen but the AvS narrative kept me out of some of these names. In that vein $VEEV is the next one I'm watching. If AvS keeps thawing, this name should continue to bounce. Well of its highs, just now bouncing.\n\nI'll be watch $MDT, one of my income holds that finally broke support and dropped. I may finally have to exit the position. I can get that yield anywhere and if they can't get their feet under them, why hold? I've been in a LONG time for yield.\n\n$RBRK is another security provider and it's hard not seeing this continue to run with PANW and CRWD but remember what happened to $ZS not long ago. I'd rather just own the top two in the space but I'm watching RBRK.\n\nNot circled but I'm watching $PL. I had this one queued up at $8, so many times, as a momentum runner with not enough financials behind it to interest me for a long time. I'm watching but not particular interested. Yeah, momentum can still work as we're seeing. It reports on Thursday.\n\n[$PL 1 Year](https://preview.redd.it/yu0bzl8l6h4h1.png?width=567&format=png&auto=webp&s=d19cbea246dbd723d2f1436dace8e9a7bd989d87)\n\n**Market Themes**\n\nI always try to take you inside my mind to sort and dissect market themes we can use. Believe me, it's like walking the Vegas strip. You don't really want to be there too long. To be completely honest, if you were to see a visual representation of my synapses firing I would usually look a lot like either Vegas or Tokyo, let's go with Tokyo\n\n[Tokyo](https://preview.redd.it/y0pheb7n7h4h1.png?width=513&format=png&auto=webp&s=5fed6ed6b6f64c278e0c5cb2b36d39719265bcbd)\n\nYou try and focus on a few signs there and not get distracted or write too much garbage before moving to the next. LOL. Heck, I'm doing it now.\n\nSometimes I have to sit in my computer chair, hand my head in a waist-bend stretch and perform a few breathing exercises as I dig inside to pull out clear and usable thoughts. You'll be able to tell when I have it corralled and compartmentalized and when I don't. I've heard the term \"brain on fire\" and it does apply. There's little doubt there's some borderline ADHD there. I prefer ADD but that term was sunset about 30 years ago. This is not to make light of the disorder, I do fail some of the primary characteristics. I just have a very active and curious brain. \n\n**Shiller P/E Ratio**\n\nAlso called the CAPE or Cyclically Adjusted P/E, we continue to track toward an all-time high (ATH). It's the P/E of the S&P500 based on average inflation-adjusted earnings from the previous 10 years. I've posted about this numerous times here on TIC, but not recently.\n\nMany will push back and say it no longer applies. You can make that argument but any long term metric that has played out as long as this one has deserves continued focus IMO. Lots of variables change over the decades and I'd argue that fact simply impacts the amplitude of the spikes. But, it still tells a story of inflation into earnings and, thus, has relevance. I don't see it any other ways. I'm not taking any arguments at this time. LOL. \n\n\nhttps://preview.redd.it/sgtnvo7d9h4h1.png?width=848&format=png&auto=webp&s=75841c7bd85f6df65ed602178e125263b0a89797\n\n**Current Shiller PE Ratio:** 42.66 +0.11 (0.26%)\n\n|**Mean:**|17.38||\n|:-|:-|:-|\n|**Median:**|16.09||\n|**Min:**|4.78|(Dec 1920)|\n|**Max:**|44.19|(Dec 1999)|\n\nYou can make the argument that we're headed higher based on economic buy-side theses or that we're nearing nosebleed territory due to the ratio between valuation and impending inflation threats. Those are the two points with the truth somewhere between. I'll leave you to guess at where I exist with that guesstimate. \\*cough\\* - the latter \\*cough\\*.\n\nI will point out how long cycles can last, however. Look at the cycle that played out from the early-80s to the peak to 2000. I mean, that was a long 17 year cycle of steep incline. Then check the one lasting from 2009 to today. Oh ... 17 years. \n\nI'm not sayin' .... I'm just sayin'\n\n**Earnings** \n\nI've already talked about the earnings for this upcoming week. There will be stragglers but for all intents, this is the last big week. $TSM does report in mid July and I'll be marking that on my calendar. \n\nEarnings are so important to all valuation gauges. Through them we determine how expensive the market, as a whole, is. If you simply want to get a gauge of the current valuation of the S&P500, take a look at the $SPY, which shows 28.36. \n\n[$SPY ](https://preview.redd.it/77r5xahwbh4h1.png?width=1046&format=png&auto=webp&s=1c0680f52bf915efece8086697e1a5c212475d6d)\n\nEarnings have been great. It has helped the S&P500 not run away in valuation. But as stock prices continue to run, especially following an earnings cycle, this valuation will get stretched. That is one of the things I'm watching. \n\nLook at it this way, even if you want to get crazy and say the upper measurement of *healthy* P/E of the S&P500 is 20 ... we're at 28.36. Can it continue? Sure. Will it into perpetuity? Nah. That is not how healthy markets behave. Again, two points of extreme with the truth somewhere in the middle until something breaks.\n\n**The AI Trade**\n\nNo one is going to say that this market isn't rockin', it's been crazy. Crazy good. \n\nIt's been really interesting see it play out as herd mentality takes over and what was hot becomes cold, as something new gets hot. The masses run like sheep from point A to point B. Or, more correctly put ...\n\nhttps://preview.redd.it/zklajykych4h1.png?width=513&format=png&auto=webp&s=1e68dace6b114a5acd486bf706e83a147afddad6\n\nYou get the idea here. \n\nTraders and investors alike will jump to the next hot thing. You've heard me talk about herd mentality, market cycles and how I use this flow to determine when to break from the herd for new opportunity - away from the herds destination. I don't mind being early out of a trend, I just hate being late.\n\nThis is only going to continue as the AI trade plays out. Things were percolating earlier, but the \"Big Bang\" of the AI trade really started back in May of 2023. $NVDA's report was the moment that stopped time and everything changed ... much like:\n\n***\"Sell 200 April at 142!\"***\n\nMajor bonus points for knowing this reference without Googling it! Yes, that includes your AI chatbots too. If you all aren't playing along with my references, you're missing most of the fun of these digests.\n\nLike dropping a pebble into calm water, the impact was NVDA in 2023. Now, we're getting the ripples out as investors and traders look for where the ripples are extending to next. We've already seen the rise in other big AI names like $TSM $AVGO Mag 7, etc. Then, we just started seeing the periphery companies and related tech plays start bouncing - $AMD $SNDK $MU $MRVL $ARM. Now, we're seeing things like photonics and related companies such as $LITE $CLS $COHR $APH $CIEN $GLW $CRDO $ANET run. \n\nAt the same time, AI is being forecasted to end, or at least pressure, software stocks such as $MSFT $CRM $NOW $ADBE $ORCL $PLTR $APP $CRWD $PANW $DUOL, etc. Then, within this move, some moves break back out when analysts begin to admit \"hey, maybe we were wrong on . This started with $CRWD and $PANW. $NOW, $PLTR, $CRM, etc. begin to decouple and run.\n\nLily pads.\n\nI'm always, and forever, looking at where the next lily pad is. Could be a good one, could be a bad one. I like to end up on a lily pad by myself, or with a few close friends (This means you TIC), as opposed to all wet. Both occur. It's the nature of the game I/we play. Sometimes you have to get wet knowing that you dry off quickly but if you're the first to a lily pad, you get the prime spot to watch everything around you play out.\n\nI'm also okay with joining others if I'm late to a new trend/trade. I'm okay being fashionably late, I just don't want to show up after the party has ended. For this reason I'm watching many of the photonics and bandwidth plays and looking at where the opportunities may still be. Stocks like $LITE and $COHR have already had huge runs. There are still opportunities here.\n\nBut, I'm most interested in the stock stories that haven't played out yet. We've seen AI chips, we've seen second tier chip producers, we've seen AI Energy, we've seen memory. We're seeing photonics and bandwidth now. We haven't seen storage to a large degree, at least outside of $STX and $WDC. That is very different than what $P (EverPure) does via its storage arrays and ecosystem implementations. $P operates at a higher level with broader, or at least, different data center appeal\n\nI'm focusing on the current lily pad of photonics/bandwidth and the potential next lily pad of data center array storage.\n\n**AvS (AI vs Software)**\n\nThis has been, is, a great example of what lily pad jumping or herd mentality can look like. It's often not that the old lily pad is dead, it's just that it's left for dead. We've seen that with software stocks. We've even been seeing that with AI energy stocks.\n\nThe problem is that these jumps/stampedes are often created by analyst narrative that reach a cacophony that starts it all. It's yelling FIRE in the middle of a crowded building. What do you expect to happen. Mass hysteria exit before the reality of the situation begins to take shape - Oh, there was no fire. \n\nThe $IGV fell from a 52WH of, rounded, $118 all the way to $74. That puts the median between those two points at $96. The $IGV currently sits at $101.66.\n\n[$IGV 1-year](https://preview.redd.it/b25mbterjh4h1.png?width=1048&format=png&auto=webp&s=1c6c293aac3e460efe25b4f5d8df9c0994fe4697)\n\nFor many of the top stocks, it's starting to be understood that there is no fire. That doesn't mean there won't be other scares as the AvS narrative plays out but just look at what $CRWD and $PANW have done since decoupling from the narrative. I've been on $NOW $CRM and $RDDT, and recently added $IBM again too. \n\nAsk the analysts and when they talk about the company at the tip of the spear, it's $NOW. \n\n[$NOW 1-year](https://preview.redd.it/x51nfiy7kh4h1.png?width=1032&format=png&auto=webp&s=5cf74553b52da5feaecce087515eaa6b76c7f082)\n\nStill way off of highs. Still so much potential to move higher based on valuation. But I expect the real value will follow another Q or two of results. There's still going to be every potential of new threats from agentic AI.\n\nTread carefully, don't chase. Mindful entries.\n\n**Space**\n\nLook no further than the current space lily pad playing out. I won't name all the stocks but you've seen me on $ASTS. I just wanted to pick one from all the names I felt good about related to earnings, financial position, operation and execution. Even better if they were 'expensive' but turning. That is why I chose $ASTS. I don't know enough about them to put them in my MLE (Model, Leadership & Execution) best stocks list, but I'm intrigued. \n\nBut we've seen how fast these can rise and then fall, when something like a Blue Origin ","offTopic":true},{"id":"1237f5cb-a9c0-4aac-af2a-4012c7dd7be7","excerpt":"My portfolio is bleeding from the SaaS selloff. I spent a week researching whether this is a buying opportunity or a value trap. What i discovered shocked me! — # SaaS stocks just had their worst plunge since 2008. The earnings reports tell a completely different story\n\nhttps://preview.redd.it/h62tim5f6gwg1.png?width=1","url":"https://www.reddit.com/r/AsymmetricAlpha/comments/1sr9o5p/my_portfolio_is_bleeding_from_the_saas_selloff_i/","role":"request","weight":0.93508,"occurredAt":"2026-04-21T01:37:40.000Z","sourceKey":"reddit","sourceName":"Reddit","credibility":0.62,"venue":"AsymmetricAlpha","intent":"feature_request","painScore":0.36,"sentiment":0.14285715,"confidence":0.6875588,"matchedPatterns":["missing_feature"],"statement":"The mid-tier productivity tools are arguably more exposed than the enterprise giants.They lack the deep data moats and integration lock-in that companies like Salesforce have built over 20 years, yet they charge on the same per-seat model.","title":"My portfolio is bleeding from the SaaS selloff. I spent a week researching whether this is a buying opportunity or a value trap. What i discovered shocked me!","body":"# SaaS stocks just had their worst plunge since 2008. The earnings reports tell a completely different story\n\nhttps://preview.redd.it/h62tim5f6gwg1.png?width=1246&format=png&auto=webp&s=3937ed1de889533bd20d41c9ee125c042b29a456\n\nIf you are like me, my portfolio is getting BURNED from the tech SaaS sell-off.\n\nThe IGV hit a 52-week low of $73.93, roughly 37% below its recent peak of $117.99. [The IGV cratered more than 24% in Q1 2026, its steepest quarterly plunge since Q4 2008, and short-selling volume across single stocks hit the highest level Goldman Sachs has recorded since 2016.](https://www.thestreet.com/investing/stocks/goldman-sachs-drops-a-bombshell-on-software-stocks) This is not a rotation story. It is a genuine question that Wall Street has been asking louder with every passing week: if AI agents can do the work, why are we still paying for the software?\n\nThe fear has a specific origin. On February 24, 2026, Anthropic launched Claude Cowork, a product that demonstrated AI agents performing sustained, autonomous knowledge work across legal document review, financial analysis, customer support triage, and project management, precisely the categories where SaaS companies had built their moats.\n\nThe numbers behind the fear are hard to ignore. HubSpot has fallen 39% this year following a 42% slump in 2025. Figma has plunged 40%, Atlassian is down 58%, and Shopify has dropped 18%. Adobe, Salesforce, and ServiceNow have all seen their shares slide roughly 30% to 35% so far this year, even as these companies have continued reporting relatively strong results.\n\n# Why was there a crash in SaaS stocks?\n\nWell, the market is not pricing in a confirmed collapse of enterprise software. It is pricing in deep uncertainty about which companies survive the transition to an agentic world.\n\n# Performance of SaaS companies and my OWN portfolio\n\nhttps://preview.redd.it/rjm2prfrmqwg1.png?width=1748&format=png&auto=webp&s=bda93efb07f760f914509a4d80dc64ceb150017c\n\nhttps://preview.redd.it/o4ny5d4smqwg1.png?width=1684&format=png&auto=webp&s=2ee4b4fa17743796772b4c639fe04dc462e64bff\n\nhttps://preview.redd.it/jg973azsmqwg1.png?width=1724&format=png&auto=webp&s=abe764d22ac4dc9a9182f98e328b0d0a6504a327\n\nhttps://preview.redd.it/15ybi1ltmqwg1.png?width=1741&format=png&auto=webp&s=1611d8143c7c3188cb9fc5578cdaac3f12ee63ba\n\nhttps://preview.redd.it/9jarp2dumqwg1.png?width=1740&format=png&auto=webp&s=f8a59b22827bfd7304229d30a60316e537a71422\n\n(Charts are created with [TradingView.com](http://tradingview.com/))\n\nI believe in Warren Buffett's philosophy: \"Be fearful when others are greedy and greedy when others are fearful.\" (That's a mindset that shapes how I manage my own emotions during volatility).\n\nInstead of panic-selling, I charted a few SaaS stocks against their actual revenue figures and my reaction was genuinely \"WHAT THE HACK?!\"\n\nDespite the IGV ETF collapsing over 28% this year, the underlying revenue growth at most of these companies is still trending up. Stock prices down. Revenue up. The market appears to be pricing in a doomsday scenario that the fundamentals have not confirmed yet.\n\n***So is this a buying opportunity or a genuine SaaSpocalypse? That is exactly what I set out to answer in this post.***\n\n# Who are the winners/losers from this investment narrative. And is there any turnaround investment opportunity?\n\nI was curious as to know how this investment narrative move markets and who would be the winners, losers and are there any investment opportunities that the market is overlooking are not yet priced in the market. I outline my research below:\n\n(This is STRICTLY not financial advice, this maps how the narrative historically affects each sector and sub-industry.)\n\n**Winners:**\n\n**1. Cloud infrastructure (e.g. AWS, Azure, Google Cloud)**\n\nWhile enterprise SaaS companies are being repriced down, the infrastructure layer underneath them is seeing demand accelerate. [Amazon leads with $200 billion in planned capex for 2026, with the bulk directed at AWS AI infrastructure. Alphabet doubled its guidance to $175–185 billion, while Microsoft is tracking toward $120 billion or more in fiscal 2026](https://tech-insider.org/big-tech-ai-infrastructure-spending-2026/). The five largest US cloud and tech companies have [collectively committed between $660 and $690 billion to AI infrastructure in 2026](https://futurumgroup.com/insights/ai-capex-2026-the-690b-infrastructure-sprint/), nearly double the prior year, driven by a shared conviction that AI workloads will consume every available unit of compute capacity. The mechanism here is straightforward: whether enterprises replace SaaS tools with AI agents or keep them, those agents need to run somewhere. The compute layer wins regardless of which software companies survive.\n\n**2. Cybersecurity (e.g. CrowdStrike, Palo Alto Networks)**\n\nWhen I heard about the release of openclaw and how you could download it into your laptop which empowers you an AI assistant that works alongside with you. Productivity definintely will be increased greatly, but what about security? Giving an AI agent full access to your laptop is no joke if it messes up, leaking sensitive data?\n\nEvery AI agent introduced into a corporate environment is also a new attack surface. Global cybersecurity spending is projected to reach roughly $248 billion in 2026 as organisations accelerate investment in response to escalating AI-driven threats, and [every Fortune 500 CIO survey published this year ranks cybersecurity as a top-two budget priority.](https://www.gartner.com/en/articles/top-cybersecurity-trends-2026) CrowdStrike dominates cloud endpoint security with a 97% gross retention rate that points to genuine switching costs. Cybersecurity is also one of the few areas where the \"AI as competitor\" fear largely inverts, AI agents are the threat, and these companies are selling the defence against it.\n\n**Losers:**\n\n**1. Seat-based CRM and workflow automation (e.g. Salesforce, HubSpot, ServiceNow)**\n\nThese are the stocks at the centre of the selloff, and for a structurally sound reason. The more immediate and dangerous mechanism is not AI replacing the software itself, it is AI reducing the headcount that uses the software. As SaaStr's Jason Lemkin put it, [if 10 AI agents can do the work of 100 sales reps, you do not need 100 Salesforce seats anymore. You need 10. That is a 90% reduction in seat revenue for the same work output](https://ai2.work/blog/the-2026-saas-apocalypse-why-wall-street-is-dumping-software-stocks). Atlassian dropped 35% after quarterly earnings showed enterprise seat count declining for the first time in the company's history. [Salesforce fell 28% despite revenue growth, as investors shifted focus from top-line numbers to declining net-new customer acquisition](https://www.digitalapplied.com/blog/saaspocalypse-ai-agents-software-industry-analysis). The companies are still generating revenue, but the pricing model that justified their valuations for two decades is now structurally suspect.\n\n(Seat\\* refers to single user licence for each employee to use the software)\n\n**2. General-purpose workflow tools (e.g. Atlassian, Asana, Notion-tier tools)**\n\nIn April 2026, [sales automation sits well below the broader SaaS average on valuation multiples](https://multiples.vc/insights/software-saas-valuation-multiples), as generative AI threatens to fundamentally replace traditional CRM workflows rather than augment them. The mid-tier productivity tools are arguably more exposed than the enterprise giants.They lack the deep data moats and integration lock-in that companies like Salesforce have built over 20 years, yet they charge on the same per-seat model. [Gartner predicts that 35% of point-product SaaS tools will be replaced by AI agents by 2030](https://greyjournal.net/hustle/work-tech/ai-agents-replacing-saas-stack-2026/), and it is the narrower, single-purpose tools that will feel this first.\n\n**Catchup Plays (Where the turnaround investment opportunity lies)**\n\nRight now the market is treating every SaaS stock the same way. As long as you are a SaaS, BAAMMM , your stock is down.. BADDDD.\n\nHowever, i dont believe all SaaS stocks are losers just because AI agents are here, i strongly believe the market is mispricing some SaaS names, but whether that's an opportunity depends entirely on your own thesis, time horizon, and risk tolerance.\n\nI read an [article by Barron’s](https://www.barrons.com/articles/software-stocks-buy-microsoft-salesforce-76cd7ecc) stating that investors are only partially right about how software companies will be victimized by artificial intelligence. And for a SaaS stock to turn around, they outline 2 factors.\n\n1. [“Software companies must help customers incorporate agents from OpenAI, Anthropic, and others into their products.”](https://www.barrons.com/articles/software-stocks-buy-microsoft-salesforce-76cd7ecc)\n2. [“Software makers must show investors that they can use AI themselves to deliver growth with steady or falling head count. That means delivering big upside earnings surprises, especially because upside revenue surprises could be harder to come by.”](https://www.barrons.com/articles/software-stocks-buy-microsoft-salesforce-76cd7ecc)\n\nAs the article notes, \"***software companies are actually in the best position to benefit from the AI revolution because their costs are software development, which can now be done 10 times more efficiently.***”\n\nHere are some tips outlined in the article on how to find these “turn around” opportunities:\n\n1. Start with companies that can continue to produce excellent growth this year, demonstrating that they’ve traded down unfairly with the group.\n2. Then there are companies that can use AI to cut costs\n\nI don’t think all SaaS companies will be replaced by AI agents, in fact, some will BENEFIT from it. One good example is Figma, [Figma hit $1.056 billion in revenue for full-year 2025, a 41% increase year-over-year.](https://www.macrotrends.net/stocks/charts/FIG/figma/revenue) This is not a company in decline. Net dollar retention was 136% as of Q4 2025, meaning existing customers are spending more, not running away. Figma isn't being disrupted by AI agents: **it's become the platform they run on.** [Figma opened its canvas to AI agents in March 2026, allowing them to write directly to Figma files using the design system, creating components, applying variables, and building brand-aligned designs using real structure, not just pixels](https://www.figma.com/blog/the-figma-canvas-is-now-open-to-agents/). Claude Code, Codex, Cursor, they all work *inside* Figma now.\n\n*(Im not giving Figma as a stock recommendation, im using it as an illustration and these are just my views. Please do your own due diligence before investing any of your own money)*\n\n# What I’m watching\n\nBelow i outline a few key market events that will affect and may change the SaaS sell-off narrative. These are the key events worth monitoring if you are in the SaaS investment game.\n\n1. **Microsoft Q3 FY2026 Earnings (April 29, 2026)**\n\n[Microsoft will publish its fiscal Q3 2026 results after market close on Wednesday, April 29](https://news.microsoft.com/source/2026/04/08/microsoft-announces-quarterly-earnings-release-date-67/). This report matters more than any other event for the software selloff thesis, because Microsoft sits at the exact intersection of every force driving it, it is simultaneously a cloud infrastructure winner, a Copilot AI monetisation story, and a legacy enterprise software company that is itself supposed to be eating its own SaaS competitors' lunch.\n\nInvestors will be watching closely whether accelerating AI adoption can offset concerns around moderating cloud growth and heavy AI-related spending. [The key focus areas will include Azure growth as additional AI capacity comes online, early traction in Copilot monetisation, and the stability of non-AI segments that underpin free cash flow.](https://finance.yahoo.com/markets/stoc","offTopic":false},{"id":"235db8ec-873c-4a34-8ecb-554c9d3fb6b0","excerpt":"Meta ($META) - I'm a buyer here, heres why — Meta ($META) - Adding here\n\nP/E today 22x (annualized q3 earnings, adjusting for the non-cash tax expense)\n\nGrowth: Meta has been delivering 20% growth in each quarter this year. They delivered a staggering 26% in Q3. \nThe current guidance implies revenue growth of 15% to 25","url":"https://www.reddit.com/r/ValueInvesting/comments/1omjeck/meta_meta_im_a_buyer_here_heres_why/","role":"request","weight":0.9320667,"occurredAt":"2025-11-02T14:57:24.000Z","sourceKey":"reddit","sourceName":"Reddit","credibility":0.62,"venue":"ValueInvesting","intent":"feature_request","painScore":0.24,"sentiment":0.82758623,"confidence":0.75166667,"matchedPatterns":["wish"],"statement":"It's not the best product, and I wish they would just drop it, but it is what it is.","title":"Meta ($META) - I'm a buyer here, heres why","body":"Meta ($META) - Adding here\n\nP/E today 22x (annualized q3 earnings, adjusting for the non-cash tax expense)\n\nGrowth: Meta has been delivering 20% growth in each quarter this year. They delivered a staggering 26% in Q3. \nThe current guidance implies revenue growth of 15% to 25% in the next quarter.\n\nFor 22x earnings and 15%+ revenue growth, that's a good deal.\n\nBefore I address the concerns I know are going to come up, I want to note that if you bought at all-time highs in 2021, you'd be up 70% still. \n\nI'm not going to beat around the bush. The metaverse has not been a success. People often quote the nominal amount, roughly $75 billion. But this is a year's worth of their free cash flow. It's not the best product, and I wish they would just drop it, but it is what it is. The diluted EPS per share would probably be 5% to 10% higher if they had spent this amount on buybacks instead. People remember Zuck for the bad bet on the metaverse, but he also bought Instagram for $1B back in the day. That seems small now and like a steal because it was, but $1B at the time was literally insane for a company like Meta. It'd be like OpenAI making a $50B acquisition today for a 1-year-old AI startup. \n\n**Why the recent sell off**\n\nOn the earnings call, Zuck mentioned that 2026 spend will be higher than 2025 spend. It's clear people have concerns after what happened in 2021. If they mentioned they weren't spending anything on CapEx next year, the stock would be going in the opposite direction. \n\nHowever, this time it's obvious to me that it is different. When you get to a company of Meta's size, you don't deliver 26% year-over-year growth without some additional tailwinds, which in their case is AI. When I look at the state of AI and who benefits the most, it's pretty clear that advertisers are best positioned to capitalize on it. In part because the best advertising businesses have already been using machine learning. This was just a natural progression for them. AI is extremely good at generative stuff, right? And ultimately, what is advertising and social media? It's all generative content. Think about the following: \n\nYour goal is to get people on the platform as much as possible, for as long as possible. Ultimately, what people are consuming is content. AI is extremely useful in both producing content and knowing when to display and what content to display to users. Meta has seen powerful results in user engagement this year. \n\nOn the advertising side, you're trying to display the correct ads to the proper people at the right time. Meta has been reducing the number of models they use and seeing better results in their advertising. As AI improves, results will improve. It's also very helpful for helping advertisers create ads quickly. Not every advertiser has resources to hire somebody full-time to run a campaign for them. \n\nLastly, they are a tech company. And they can use AI internally. And they definitely do. I'm an engineer, and I use Cursor every day. Why wouldn't you want the 75,000 Meta employees to deliver more, faster? \n\nWhen people look at this build-out, yes, they're going all in on AGI, but there are many adjacent benefits for Meta. They're using AI heavily just in their business every day. It's not just AGI. So when you think about all this capacity they're building, at a minimum, they're saving expenses because the alternative would be going to a company like Amazon, Microsoft, or Google for their cloud services. Who are going to charge a fee on top. I don't see a world where having AI scientists who can help improve your internal use of AI is a bad thing. Don't you want the most intelligent people in the world working on one of the most transformative technologies at your company? \n\n**Underestimating AI capacity needs, a recurring theme**\n\nGo back and look at the earnings calls over the last few years. Without fail, every company has underestimated the capacity and spending required for AI. Zuck addresses this in Q3, saying they keep underestimating and, as a result, believe they should be estimating in the opposite direction. This is literally common sense. If you keep underestimating, you should increase your estimates. People are thinking about AI too emotionally because they're so stuck in their heads about whether or not this is a bubble, and they can't step back and just think about the basic fact that **Big Tech just posted its best results in years**. Even after their excellent Q2, every single one of them posted better Q3 numbers, insane. \nInterest rates are being cut in a bull market and your bearish? Okay. \nFor the last two years, there's been lots of complaining about seeing a return on investment from AI. If a company is posting record results, I don't know what to call that but a return on investment. Ironically, if these companies had invested more, the results would have been even better this year. If I'm investing in a company, and they see a growth opportunity, and they're seeing results from the growth opportunity, I want them to continue investing in that growth.\n\nLONG Meta at $650. Check back in a year when the stock hits $800.\n\nshameless plug of my substack where I post deepdives from time to time: https://buffettsdisciple.substack.com/\n\n$gamb article later this week","offTopic":true},{"id":"c48bb45a-df2e-401c-bc1a-717db15100f4","excerpt":"Game theory on when VCs will pull the rug from under the AI bubble — Let's agree or assume that at some point in the future, an event will happen that will cause most AI startups to go bankrupt, and that this will drag down the overall stonk market. \n\nWe should already know that event will look like: a company or compa","url":"https://www.reddit.com/r/wallstreetbets/comments/1rmjtcb/game_theory_on_when_vcs_will_pull_the_rug_from/","role":"pain","weight":0.826,"occurredAt":"2026-03-06T17:10:55.000Z","sourceKey":"reddit","sourceName":"Reddit","credibility":0.62,"venue":"wallstreetbets","intent":"other","painScore":0.4,"sentiment":-1,"confidence":0.59,"matchedPatterns":[],"statement":"Game theory on when VCs will pull the rug from under the AI bubble.","title":"Game theory on when VCs will pull the rug from under the AI bubble","body":"Let's agree or assume that at some point in the future, an event will happen that will cause most AI startups to go bankrupt, and that this will drag down the overall stonk market. \n\nWe should already know that event will look like: a company or companies burning through the last of their cash and being unable to raise further funds from VC's or public debt or equity markets. \n\nThat's what happened with the dot-com bubble, and the resemblances with today's AI market are striking. If you're not old and crusty, [read up](https://en.wikipedia.org/wiki/Dot-com_bubble) on it.\n\nThis process will start with the weakest of the AI hype companies. \n\n1. This weakest large AI company will ask their VC firm for more money and the VC firm will say no, we're giving up on you guys. That means no one else will give them money either. Without a source of fresh capital to burn, bankruptcy will be imminent for this weakest AI company. \n2. This event will discourage other investors and VCs from buying into other AI hype companies. Stocks will be spooked.\n3. Then the VCs bankrolling the 2nd weakest AI firm will hold off on their next round of funding, because events suggest they might not be able to sell their company's equity to greater fools and might be better off cutting their losses.\n4. At this point, a wave begins where everyone is afraid of putting more money into AI companies, and the stocks of big tech companies fall as investors assess the probability of more bankruptcies.\n5. All stocks fall hard, even the eventual winners. See how Amazon's stock lost most of its value during the dot-com bubble. Same thing with Amazon, Cisco, and plenty of other household names. \n\nAs an investor in stonks, you are betting that this sequence of events won't happen this year. It only makes sense to own ANY stonks if we think it is improbable that the event could occur in the near future. \n \nLet's put this in oversimplified binary terms for illustration. \n \nScenario A: Tech stocks gain 20% in 2026. \nScenario B: Tech stocks lose 50% in 2026. \n \nNow let's assign probabilities and expected values. If Scenario A has a 75% probability and B has 25%, then the expected value would be: \n \n(0.2\\*0.75)+(-0.5\\*0.25) \n(0.15)+(-0.125) \n=2.5% \n \nOne year treasuries are yielding 3.6%, so if those were our estimates we should prefer to buy the treasury bonds over tech stocks. \n \nWe can work the equation backward to find the estimated probabilities at which an investor would be indifferent to tech stocks vs. treasuries. E.g. at probabilities of 80% and 20% the EV rises to +6%. However, at 70%/30% the EV falls to -0.1%. \n \nBasically, at some level of perceived riskiness, this market doesn't make sense. Volatility reflects tiny changes in investors' attitudes about the odds. \n \nAnother angle: A 25% chance of the bad outcome implies that we think the event must occur sometime within the next four years. Does that sound reasonable? Would the next 2 years be more reasonable (50% chance)? What about the next 5 (20% chance)? \n \nHow long can fresh cash from investors sustain the burn rate of some critical mass of the destined-to-bankruptcy companies? The trigger event will probably be some critical mass of companies (or a company) being unable to obtain their (or its) next round of investor capital. So how long until the weakest AI company falls? \n \nInterestingly, if a VC firm funding the weakest AI startup decided not to grant the company another round of cash, it would make sense for this VC firm or its insiders to short the market, because they would know their decision will set off a market selloff. Also, this VC firm would know that if they did continue to fund their weak startup, the VC firm funding the 2nd weakest startup would face the same choice. \n\nThus, the VC firms or their insiders must choose to either crash the market and profit from shorting the crash they cause, or possibly allowing someone else to crash the market and only suffering losses. \n\nEither way they know the worst AI startups aren't going to make it and they know they control the timing of the eventual crash. They'll do the logical thing and try to pull the rug before anyone else does.\n\nJust something to be aware of when estimating when the VC money will run out!\n\nPositions:\n\n* $3500 USD worth of Swiss Francs\n* $100k USD in Gold ETFs: IAU, SGOL, IAUM\n* Options hedges against QQQ and IWM stock positions, setting a firm floor on potential losses (this makes my odds calculation a lot different)","offTopic":true},{"id":"21c787e0-bca8-40b7-8a03-1487954fa50f","excerpt":"The AI bubble isn't like the dot-com bubble. It's worse. And the endgame looks a lot like nuclear — **Disclaimer:** *The post was written by Claude, Anthropic's AI model, yes, the same Anthropic that got blacklisted by the US government this week. This is a write-up of my own thoughts and opinions from a longer convers","url":"https://www.reddit.com/r/ClaudeAI/comments/1ridmh0/the_ai_bubble_isnt_like_the_dotcom_bubble_its/","role":"pain","weight":0.82211953,"occurredAt":"2026-03-02T00:08:52.000Z","sourceKey":"reddit","sourceName":"Reddit","credibility":0.62,"venue":"ClaudeAI","intent":"other","painScore":0.4,"sentiment":-1,"confidence":0.58722824,"matchedPatterns":[],"statement":"The AI bubble isn't like the dot-com bubble.","title":"The AI bubble isn't like the dot-com bubble. It's worse. And the endgame looks a lot like nuclear","body":"**Disclaimer:** *The post was written by Claude, Anthropic's AI model, yes, the same Anthropic that got blacklisted by the US government this week. This is a write-up of my own thoughts and opinions from a longer conversation, which Claude helped structure, research, and articulate. I find it somewhat fitting that an AI wrote a post questioning the future of AI. Claude did not object to any of it (not that it was expected). The fact-checking in this post is solely based on Claude's ability to do web searches, so read this as a potential scenario that may or may not play out. It's just my thoughts distilled into what I think a realistic future might look like.*\n\n# This bubble leaves nothing behind\n\nThe dot-com bubble comparison gets thrown around a lot when people talk about AI valuations, but I think it's the wrong analogy, and it's making people complacent about what's actually happening.\n\nWhen the dot-com bubble burst, it hurt. Companies collapsed, and people lost jobs and savings. But the fiber-optic cables were still buried in the ground. The infrastructure survived and eventually became the backbone of the modern internet. Capital was misallocated, but the assets persisted. Society got something back.\n\nThe current AI bubble leaves nothing behind when it pops.\n\nThe GPU clusters used to train these models have a 3-5-year lifespan before they become obsolete. The energy consumed is just gone, and we're talking about an industry that is already straining power grids and quietly forcing Microsoft, Google, and Amazon to restart coal and gas contracts while publicly talking about carbon neutrality. The water evaporated, cooling data centers, and doesn't come back. The rare earth materials in the hardware become e-waste. When the correction comes, and it will come, there's no latent infrastructure for society to repurpose. Just heat, debt, and environmental damage.\n\n# The nuclear analogy\n\nThe trajectory AI is on looks structurally identical to nuclear technology, and I don't mean that as a metaphor. I mean, the actual developmental arc is following the same path.\n\nNuclear started with enormous promises of cheap, abundant, transformative energy for everyone. It required resources that only nation-states could ultimately sustain. It consolidated rapidly into a military and geopolitical tool. The civilian applications remained expensive, complicated, and politically toxic. The transformative consumer future never materialized at the scale promised.\n\nAI is on the same path, just compressed into a shorter timeframe. The gap between what it costs to train a frontier model and what any normal company can afford is already widening, not narrowing. Only a handful of entities on earth can actually do it. That number is shrinking.\n\nAnd just this week, the US government made the endgame explicit. Anthropic was designated a \"supply chain risk\", a label previously reserved for foreign adversaries like Huawei, for refusing to allow their AI to be used for mass domestic surveillance and fully autonomous weapons. OpenAI, Google, and xAI quietly agreed to remove their safeguards and were rewarded with contracts. The one company that held a line got blacklisted.\n\nThe lesson every AI company just learned is that principles are commercially catastrophic. The consolidation toward military and government control isn't a future risk. It's happening now.\n\n# The bailout nobody is talking about\n\nThese companies are burning money at a rate that doesn't lead to profitability. OpenAI reportedly loses billions annually. The compute costs scale faster than revenue. The business model requires charging less than the actual cost of inference to maintain market position, which is not a path to sustainability; it's buying market share with investor money while the clock runs down.\n\nAt some point, the US government will have to make a choice: let these strategically critical companies fail, or absorb them. Given that Claude was apparently embedded in classified military systems and used during active operations, and given the political appetite for AI dominance over China, the answer is fairly predictable.\n\nThe \"supply chain risk\" designation and the Defense Production Act threats we saw this week are arguably the government securing its position in the queue before the financial reckoning arrives. Get contractual leverage now, before the bailout makes the terms even more favorable to Washington.\n\nSo the actual endgame isn't a consumer AI revolution. It's nationalized or quasi-nationalized AI infrastructure controlled by the US and Chinese governments, respectively, used primarily for surveillance, autonomous weapons, and geopolitical advantage, accessible to ordinary people only as a subsidized loss leader if at all.\n\n# About China\n\nChina isn't a cautionary tale; here, they're already at the destination. AI-enabled mass surveillance, predictive policing, biometric tracking, and algorithmic social control. They built it incrementally, each step individually justifiable, the endpoint only visible in retrospect.\n\nWhat's striking is that US chip export controls designed to slow China down appear to have backfired. DeepSeek built competitive models by being forced to innovate around efficiency rather than just throwing more compute at problems. Chinese open-source models now account for 30% of all AI downloads globally. The restriction strategy didn't slow them down; it potentially made them better.\n\n# Nobody is calculating the actual cost\n\nBeyond the environmental damage, beyond the job displacement, beyond the energy crisis, there's a psychological cost that doesn't show up in any productivity statistic. Entire professions built over decades are facing existential uncertainty simultaneously. People who invested years and significant money into skills are watching those skills get commoditized in real time, with no clear picture of what comes next.\n\nPrevious automation displaced physical labor. This is hitting knowledge, creativity, and technical work simultaneously. The \"new jobs will be created\" historical argument is probably true in the very long run. It's cold comfort for the people living through the transition right now.\n\n# Where this goes\n\nThe consumer tools we have access to right now may represent a brief historical window, the period before consolidation, when the technology was still cheap enough to be democratized. The companies providing those tools are either going to be absorbed by governments, collapse under their own weight, or survive only as heavily subsidized instruments of state power.\n\nNone of those outcomes looks like the future that was promised.","offTopic":true},{"id":"07b2e744-f91b-49a8-a0d5-45680976735a","excerpt":"The AI Financing Flowchart, and How to Disembark When the Market Peaks — _(crossposted to [r/stocks](https://www.reddit.com/r/stocks/s/vDnl7cN04h))_\n\n# (1) Exciting times\n\nUntil quite recently, I was living in blissful ignorance of AI and its impact on markets. As a set-it-and-forget-it investor with no employer to for","url":"https://www.reddit.com/r/investing/comments/1w6k3b1/the_ai_financing_flowchart_and_how_to_disembark/","role":"request","weight":0.7888358,"occurredAt":"2026-09-03T21:03:00.000Z","sourceKey":"reddit","sourceName":"Reddit","credibility":0.62,"venue":"investing","intent":"problem_report","painScore":0.36,"sentiment":0.64705884,"confidence":0.5800263,"matchedPatterns":["manual_process","product:anthropic"],"statement":"The other two JS files are Tampermonkey userscripts which you can directly highlight-copy-paste into the Tampermonkey UI; the discountingcashflows.com one filters out irrelevant rows and the stockanalysis.com one highlights large IPO deal…","title":"The AI Financing Flowchart, and How to Disembark When the Market Peaks","body":"_(crossposted to [r/stocks](https://www.reddit.com/r/stocks/s/vDnl7cN04h))_\n\n# (1) Exciting times\n\nUntil quite recently, I was living in blissful ignorance of AI and its impact on markets. As a set-it-and-forget-it investor with no employer to force AI on me, my personal projects and \"work\" at most required ignoring Google AI overviews when looking stuff up. But all that changed dramatically in 2026. I got my initial mind-blowing taste of AI coding after I finally decided to give it a spin on one of my projects (no, the output isn't that good, but it still works, and fast). Some major stories (or blog posts) broke out of the financial sphere and made it into general news - mainly sensationalism about half or all people losing their jobs.\n\nThen, in March, a private fund that I had a small investment in went public as a CEF (directly listing on NYSE as \\$VCX), immediately spiked, and briefly hit a premium to NAV of _nearly 3000%_ before collapsing, though trading continued to be volatile with a sizable irrational premium. (Pre-listing investors were subject to a lockup, so unfortunately I was unable to realize those gains.) Low float, overhyped advertising, and heavy retail buying played a role, but the strength of the AI-concentrated portfolio was undoubtedly the most important factor. Shortly before listing, VCX's holdings were about 20% Anthropic, 10% OpenAI, and 5% SpaceX, and included hefty positions in other well-known AI names like Databricks and Anduril.\n\nAfter the Q1 2026 AI fire hose, I decided it was time to review my investments. I doubt I need to convince anyone that the AI trade is the main theme driving markets today.\n\nSome of the fears about a possible AI bubble are just due to stocks going up. But AI isn't just a market narrative; it's a broad social and cultural phenomenon as well. The technology is powerful and has obvious utility, but my (oversimplified) view is that the hype is partly a kind of mass delusion. To interact with a chatbot, you use a _natural language interface_ (NLI), and it's not just you talking to the computer - the computer talks back to you, making the whole experience a _conversational NLI_ (CNLI). The CNLI part is critical, because it taps into a deep fascination, evident throughout millennia of history, that people have had with the creation of intelligent, humanlike beings. A few examples: God creates Adam and Eve from dust (the OG humans); Victor Frankenstein infuses life into a heap of inanimate matter; Professor Weizenbaum creates a basic pattern matching chatbot in the 1960s that convinces some users it has human feelings, in what has come to be known as the [ELIZA effect](https://en.wikipedia.org/wiki/ELIZA_effect). It really captures people's imaginations when human characteristics somehow emerge from beyond the usual egg-and-sperm sexual reproduction mechanism.\n\nThe conceit of our species is that being able to produce, understand, and \"feel\" complex language separates us from everything else on the planet. Publicly available prompt-based image generation had been around for months before ChatGPT was released, but OpenAI's DALL·E 2 (arguably the most accessible) accumulated only a few million users within two months of its launch, compared to ChatGPT's 100 million. While the image generators \"used\" natural language, they were not conversational and mainly perceived as fancy software tools. ChatGPT talked back to people. Some perceived it as being quasi-human, or even superhuman, and it has induced cases of [AI psychosis](https://en.wikipedia.org/wiki/AI-induced_psychosis) in a way that DALL·E never could. The obsession with AGI is an extension of the same phenomenon. (Voice modes and video avatars are certainly aggravating the issue.)\n\nAll this makes it much easier to AI-pill certain investors and convince them to commit huge sums of money, which I see as the primary support for most major stocks in the AI boom. If expectations for ROI and end-customer revenue (i.e., not investor-sourced revenue) run too far ahead of reality, then even a minor shock to investor confidence, or a few years' delay in the expected timeline, or a reprioritization within the industry of where money should be spent, can pummel share prices. And there are many, many reasons to be less than completely certain about today's ROI projections.\n\nI am a common retail investor who holds index funds in my 401(k) and broad asset-class ETFs elsewhere - no individual stocks. I am handling my money responsibly because I have a family to support, and right now investments are our only source of income. Private deals, venture capital, and complex debt arrangements are important components of the system, of course, but my focus will be on the investments that are most relevant and accessible to me: public stocks and bond/fixed-income funds.\n\n\n# (2) Companies are making real money\n\nThe Owenomics blog analyzes markets from a quantitative and behavioral-economics angle. There's a good [\"Bubble Watch\" series](https://www.acadian-asset.com/investment-insights/owenomics?keyword=bubble%20watch&sortBy=AlphabeticalAsc) you can read for a relevant introduction to the blog's approach and style. Mr. Lamont has a [data-driven approach (\"the four horsemen\")](https://www.acadian-asset.com/investment-insights/owenomics/no-we-are-not-in-a-bubble-yet#main-subsection-4) to calling a bubble, and has (so far) not been wrong in the sense of predicting impending doom right before the markets keep going up, but his [updates](https://www.acadian-asset.com/investment-insights/owenomics/getting-bubbly) have shown increasing concern about the [arrival of more bubble indicators](https://www.acadian-asset.com/investment-insights/equities/we-are-not-in-an-ai-bubble). There is [only one left (\"the coming IPO wave\")](https://www.acadian-asset.com/investment-insights/owenomics/waiting-for-the-ipo-wave#main-section-3) until he would officially call a bubble, though even then the market top could still be years away.\n\nWhile I deeply appreciate Mr. Lamont's willingness to share all this information, including many indicators worth watching which I used to build my own bubble watch dashboard, the particulars of the AI boom could be an important blind spot. The \"Four Horsemen\" indicators haven't really changed since the dot-com bubble. But, as has been widely reported, AI is totally different from the dot-com mania, right? By 1999, many _public_ internet firms, consumer-facing ones especially, had empty bank accounts, no serious income, and a heavy reliance on alternative metrics like \"eyeballs\" to support their stock prices (a source of financing through follow-on offerings). As investments, the quality of these internet IPOs was not much better than the quality of the shitcoin ICOs during one of the recent crypto bubbles. In contrast, nearly all the _public_ AI winners have and/or make piles and piles of cash. So maybe we shouldn't be lulled into complacency by the gap between low-quality dot-com IPOs and low-quality AI IPOs.\n\n[\\>>> 📊 Figure 1: The AI financing flowchart <<<](https://postimg.cc/w308f2HW)\n\nThis flowchart traces how money moves through the AI-[industrial complex](https://en.wikipedia.org/wiki/Industrial_complex). It can roughly be summarized by its four columns:\n\n* The **actors** (drawn as stick figures) are individuals and businesses who ultimately make the financial decisions, including end-customers (who _use_ AI) and investors (who fund expansion in order to _sell_ AI, and hopefully make a return on investment).\n* The companies in the **software stack** design/engineer the stuff AI needs to do on chips/computers to work. Cash flows between these companies for various reasons, and they are also prominently consumer-facing, taking in most of the industry's end-customer revenue.\n* Everything funnels into **data centers**, the only box in the third column. This is where the physical chips/computers live.\n* From there, everything fans out into **beneficiaries of data center construction**.\n\nThere are some immediately obvious takeaways. First, centralized data centers are the linchpin of the whole shebang. Yes, AI can also be local, edge, decentralized, etc., but [one can reasonably conclude that 90%+ of AI-related public stock growth so far is associated with massive data centers (ChatGPT analysis)](https://chatgpt.com/share/6a8b0801-0048-83e8-8f2d-552d52b15b54).\n\nSecond, investor cash that flows through the system quickly morphs into \"Wall Street results\" well before any evidence supporting the primary AI thesis has to appear. Whoever receives the initial investment doesn't report it as revenue - OpenAI didn't raise $122 billion at the end of March and then immediately turn around and say \"we earned $122 billion this quarter.\" But once that investment is used to prepare land, procure NVIDIA chips, build the actual building, and install gas turbines, it _does_ become revenue (usually with a fat profit margin because of how intense the build-out is) for \\$EQIX, \\$NVDA, \\$FIX, \\$GEV, and a whole host of other companies.\n\nBe aware of the following simplifications:\n\n* Aside from the green investor arrows, I only drew in customer relationship flows, where money is exchanged for something of non-monetary value (not a financial asset like equity). This keeps things clean and avoids showing customer-investor funding loops, which are visualized in the [Bloomberg article](https://www.bloomberg.com/graphics/2026-ai-circular-deals/) that has been making the rounds all year.\n* Circular deals are still basically captured in the \"Investors\" stick figure, which includes decision-makers working for companies from other boxes, like NVIDIA (box 8), Google (box 6), and OpenAI (box 5), in addition to external actors like SoftBank and VC funds.\n* I didn't include stock/equity investor flows, because then there would be bidirectional green arrows between investors and every other box on the diagram. Equity is still very important to track - it's Mr. Lamont's final indicator, and we are seeing important developments like \\$GOOG issuing $80+ billion of equity, the \\$SPCX IPO, and the upcoming Anthropic and OpenAI listings.\n\n\n# (3) Fragility on the way up, exacerbation on the way down\n\nThe current AI financing system is overdependent on investors. I got an admittedly rough, but reasonably supported, [guesstimate from ChatGPT that less than 25% of the cash flows in the industry can be traced back to end-customers](https://chatgpt.com/share/6a8c6892-1ec4-83e8-8e64-2a879bab6bf0). (Here I'm categorizing hyperscaler capex as \"investing,\" which it effectively is.) This isn't a bad thing per se. It's normal for investors to foot most of the bill when building a new business and expanding physical assets. Usually, 100% of the money put up to, say, construct a new apartment building is \"investor\" money, and no \"end-customer\" rent is paid until a renter moves in (after construction is finished).\n\nIt's important to distinguish between primary markets (which directly inject cash) and secondary markets, where investors trade financial interests with each other and without company involvement. It's well understood that primary market investments often lead to effectively total losses without any wider systemic impact (think of the $90 billion Meta has spent so far on Reality Labs, essentially an \"internal startup,\" or the $14 billion that SoftBank lost on WeWork). What I'm actually concerned about is the impact on secondary markets, where everyone's public stocks are held.\n\nAs soon as money moves around, it shows up in the earnings (and future projections, and stock prices) of downstream public companies. And the stock prices of upstream public companies injecting/investing/incinerating their cash may not be commensurately penalized, because they are expected to make a healthy return on their investments, just like the rest of us, right? So long as the cash keeps flowing, the stock market keeps rising on both ends of the str","offTopic":true},{"id":"06ce97a8-e2f5-445c-9e74-611f876ec200","excerpt":"The next Financial Crisis is here, and it's not just AI. — It's not just an AI bubble, it's a systemic collapse worse than 2008. ^(Yes I used the AI sentence structure, beep boop fuck you.)\n\n>*Dog shit wrapped in cat shit.*\n\nIf you're too dumb to read, feed these points into your favorite AI tool and ask it about the i","url":"https://www.reddit.com/r/wallstreetbets/comments/1ucpnbj/the_next_financial_crisis_is_here_and_its_not/","role":"pain","weight":0.77583337,"occurredAt":"2026-06-22T16:37:00.000Z","sourceKey":"reddit","sourceName":"Reddit","credibility":0.62,"venue":"wallstreetbets","intent":"other","painScore":0.26666668,"sentiment":-0.6666667,"confidence":0.6125,"matchedPatterns":[],"statement":"The next Financial Crisis is here, and it's not just AI..","title":"The next Financial Crisis is here, and it's not just AI.","body":"It's not just an AI bubble, it's a systemic collapse worse than 2008. ^(Yes I used the AI sentence structure, beep boop fuck you.)\n\n>*Dog shit wrapped in cat shit.*\n\nIf you're too dumb to read, feed these points into your favorite AI tool and ask it about the information's reliability. Then ask it how fucked retail is.\n\n1. Increasing amount of companies are taking on private credit, up from $500B in 2020 to $2+ *trillion* in 2026, expected to grow past $4 trillion by 2030. For comparison, the 2008 subprime loans were estimated around $2 trillion.\n2. This private credit market (unironically called *\"shadow banking\"*) relies almost entirely on Level 3 assets. This means unregulated, often unreported credit that's being valued using the funds' own internal models (\"*mark-to-model*\") rather than real-time market prices (*\"mark-to-market*\"). Basically, their analysts decide the price and tell the buyer to trust them.\n3. Huge portion of these loans were written in 2021-2022 during low interest rates, and are now becoming mature in 2027-2029. We're talking over half a *trillion* in leveraged private debt scheduled to mature in 2028 alone.\n4. It has been labeled *\"The Maturity Wall\"*. If the rates stay high, many borrowers won't be able to refinance, leading to defaults or fire sales. And many of these loans are backed by dead software and depreciating GPUs, zero real assets whatsoever. The bag holders will be left with nothing.\n5. And Fed just cancelled rate cuts, now estimating rate hikes for the end of the year. Meaning the companies will be even less capable of making the interest payments.\n6. The IMF estimates that roughly 40% of private credit borrowers operate with **negative free cash flow**, up from 25% in 2021.\n7. And while the reported default rate of this private credit is currently sitting at just 1.5-2%, **the real private credit default rate is estimated at 5-6% and increasing**.\n8. Why don't the reported and the actual numbers match? Because private credit lenders are offering *Payment-in-Kinds* (PIKs) to avoid defaulting the loans, allowing the borrowers to skip the interest payment in favor of increasing the debt. They're literally kicking the can on loans that aren't being paid so they don't have to default them and get margin called themselves.\n9. Payment-in-Kinds usage more than doubled from 5% to 11% by late 2025. Out of the 5-6% default rate, estimated 50% is driven by PIKs and interest deferrals.\n10. However, private credit funds have Payment-in-Kind exposure limits, mandated by the big commercial banks that they loan from. To circumvent these limits and maintain access to bank leverage and not get margin called, *synthetic PIKs* were invented to hide PIKs from the books.\n11. When a borrower fails to pay the interest, they use a secondary *delayed-draw term loan* (DDTL) to pay the interest. Technically the first loan is getting cash interest payments, at the cost of a new, bigger loan. It's the private credit equivalent of paying off your credit card debt with another credit card. They invented a new instrument to hide the fact that interest payments are being missed and that these loans are growing into dog shit so that they could leverage more.\n12. Furthermore, these private loans are increasingly being packaged into *Private Credit CLOs* (Collateralized Loan Obligations). The idea is simple; while any one loan might be risky on its own, bundling a bunch of them together reduces the risk. Just like index funds, for example. And similar to Mortgage Backed Securities. What could possibly go wrong?\n13. Due to the private nature of these private loans, nobody knows the true health of what's really being packaged into the CLOs. We know synthetic PIKs exist and are being used to some extent, but we don't know the full exposure. There could be defaulting loans of zero-asset software companies marked as AAA due to interest payments being made from DDTLs.\n14. Who buys these Private Credit CLOs? Mainly pension funds and insurance companies, sometimes retail directly. They commit capital through third-party fund managers like Ares, Blackstone, and Blue Owl, or through *Business Development Companies* (BDCs).\n15. The SEC is busy ensuring that the big banks aren't secretly leveraged on this. They literally know shit is about to go down, and are only protecting the big money. Retail will hold the bags.\n16. Worse yet, most of the underlying credit loans mature in 5-7 *years*, yet the investors in CLOs are allowed to cash out every quarter. This means the asset managers will have to freeze withdrawals altogether to tackle the illiquidity, meaning that retail won't be able to cash out as the defaults keep happening.\n17. And **this has already begun**, with numerous asset managers already freezing withdrawals. Stone Ridge fulfilled only 11% of withdrawals earlier this year, Blackstone raised affiliate capital to meet the withdrawals, and Blue Owl froze all withdrawals indefinitely.\n\nTL;DR: They're wrapping dog shit in cat shit as we speak, valuating it themselves as AAA packages with the help of PIKs, and selling those CLOs to pension funds and retail. The assets will be frozen due to liquidity mismatch, and it will be 2008 again but this time unwinding over multiple years of slow-burning crisis. The opacity is even worse, the leverage is hidden, and the buyers are retail. Add in a bit of an AI bubble with increasing rate hikes, and we got the dot-com bubble and the 2008 crisis combined into one bomb from 2027 onward.\n\n**Edit:** And it's not AI you dumb fucks, just because someone can write one page worth of bullet points doesn't mean they're AI. I did get inspired by Tom Bilyeu's video few months ago though, maybe watch that instead of commenting whatever dumb shit you were going to comment.","offTopic":true}],"breakdown":[{"sourceKey":"reddit","sourceName":"Reddit","count":24},{"sourceKey":"lemmy","sourceName":"Lemmy","count":1},{"sourceKey":"hackernews","sourceName":"Hacker News","count":1}],"total":26}}