N Adam @nunoadam

Every job invented in the 20th Century is threatened by AI.

Impoverishment Of Spaniards Is The Result Of Years Of Interventionist Policies zerohedge.com/economics/impo…

Elon Musk just identified which jobs go first, and it destroys every assumption about who’s safe. Musk: “AI is going to take over those jobs like lightning. Anything that is digital, which is like just someone at a computer doing something.” Not factory workers. Office workers. The people who spent decades assuming education and desk jobs meant security are actually first. Musk: “Anything that’s physically moving atoms… those jobs will exist for a much longer time.” Output is a file? Vulnerable. Output is physical? Protected. That’s the entire framework. Musk: “AI is really still digital.” AI doesn’t need a body. Doesn’t need an office. Just needs access to the same software you use. Executes faster. Never tires. Costs nothing to scale. But it can’t weld. Can’t wire a building. Can’t fix pipes or work soil. Musk: “Literally welding, electrical work, plumbing. Those jobs will exist for a much longer time.” Trades aren’t the vulnerable jobs. They’re the durable ones. Physical presence, real-world adaptation, manual dexterity provide protection no digital credential offers. Analyst, accountant, paralegal, programmer, anyone producing files and documents, automates first because digital work is exactly what AI does natively. Person moving atoms has natural defense. Physics, unpredictable environments, material resistance create friction AI can’t scale past. Person moving bits has nothing. No friction. No physical barrier. Just software AI already operates better than most humans. The assumption that desk work and degrees represent safety just inverted completely. College graduate producing documents faces faster displacement than the electrician producing installations. Society spent generations telling people trades were beneath them. Pushed everyone toward offices and screens. Turns out the people who didn’t listen built the most automation-resistant careers. Most ironic outcome of the AI revolution. The work society treated as inferior turned out to be the work society couldn’t replace. And the work society valued most turned out to be the easiest to eliminate.

Bitcoin price today is 66k. The cost of electricity wasted to create one is $96k. You do the math. It is a wasteful garbage which services no purpose . It needs to be 0.

Software slump may not be about AI killing the software…. It may be about it killing the jobs

People are discussing SaaS bloodbath opportunities while backtesting, hunting investment plays, and building winning portfolios with just a few prompts

Long atoms, short bits In the mid of the IA industrial revolution the market has no clue what is next... just zoom out and play the long term safe narrative

This is the biggest irony in tech history. Microsoft beat revenue estimates. Stock plunged 11%, wiped out $400 BILLION in market cap. Salesforce reported growth. Stock fell 5.6%. ServiceNow beat earnings. Stock crashed 11%. SAP beat projections. Stock dropped 16%. Entire software sector entered bear market territory. Down 22% from peak. These are the companies everyone said would WIN from AI. They spent billions BUYING AI companies. ServiceNow: $7.75 billion for Armis. Salesforce: $8 billion for Informatica. They launched AI products. Built AI workflows. Hired AI teams. And the market said: You're all dead. Because investors just realized something nobody wanted to admit: AI doesn't make software companies stronger. AI makes software companies OBSOLETE. Morgan Stanley: "In an environment of heightened investor skepticism, stable growth falls short of shifting the narrative." Good earnings aren't enough anymore. The market is pricing in a world where AI replaces the software these companies sell. ServiceNow CEO tried defending on the earnings call: "AI needs workflow orchestration. ServiceNow is the gateway to this shift." Market response: 11% crash. Because here's what he didn't say: If AI can write code, automate workflows, and generate apps at a fraction of the cost, why would anyone pay $50,000 per year for enterprise software licenses? The per-seat pricing model that made SaaS companies rich is getting murdered by AI efficiency. One AI agent replaces 10 seats. One prompt replaces months of custom development. One LLM call replaces entire software categories. Klarna already proved it. CEO said they pulled Salesforce out of their stack. Built everything themselves using AI. And that's just the beginning. The software apocalypse hit hardest on companies that INVESTED IN AI: Atlassian: down 12.6% Intuit: down 7.8% HubSpot: down 11.5% Zscaler: down 6.3% Meanwhile, the companies ENABLING AI made money: Nvidia: up Semiconductor stocks: surging Memory firms: rallying The divide is brutal. Hardware companies print cash. Software companies get destroyed. Because in an AI-first world, you need GPUs to build the models. But you don't need software subscriptions when the AI builds the software for you. Jim Cramer called it the "P/E multiple compression crisis." Translation: Investors don't care about earnings anymore. They care about whether your business model survives the next 5 years. And right now software business models look doomed. They're literally stuck: If they DON'T invest in AI, they fall behind. If they DO invest in AI, they cannibalize their own products. It's a death spiral with no exit. ServiceNow spent $12 BILLION on acquisitions in 2025 alone. Trying to buy their way into relevance. And yesterday the market cooked them. The craziest thing to me tho... Most software companies beat earnings. Revenue was solid. Growth was fine. But it didn't matter. Because the market stopped pricing software on what it earns TODAY. It's pricing software on what it's worth in a world where AI does the job for free. And in that world these companies are worth nothing. This is the biggest sector repricing since 2008. $500 billion in market value gone in ONE DAY. And it's not stopping. Because every company watching this is thinking the same thing: "If I can replace ServiceNow with 3 AI agents and save $10 million per year, why wouldn't I?" The answer used to be: "Because you need enterprise-grade reliability." But now? AI agents are getting reliable. Fast. Software companies just realized they're competing with open-source models that cost $0.02 per 1,000 tokens. You can't win a pricing war against free. The companies that spent BILLIONS preparing for AI are getting killed BY AI. What an irony.

10 Years Ago I Needed to Hear This On Risk & Survival → The market doesn't reward bravery. It rewards survival. → Size kills more accounts than bad entries ever will. → If you're calculating how much you could make, you've already lost. → The best trade is often the one you didn't take. → Never add to a loser. You're not "averaging down." You're compounding a mistake. → Risk 1% and you can be wrong 50 times in a row. Risk 10% and you're done in a month. On Losses → A small loss is a victory. It means your rules worked. → The stock doesn't know you own it. It doesn't owe you a bounce. → Cut your losses fast. Not because you're scared-because you're disciplined. → Every blown account started with "I'll just wait for it to come back." → Your ego wants to be right. Your P&L wants you to be flexible. → The loss you avoid is worth more than the gain you chase. On Winners → Sell your losers and your winners ride themselves. → The hardest skill isn't finding winners. It's holding them. → Nobody went broke taking profits-but plenty stayed poor doing it too early. → A stock up 10% can go up 100%. Let the trend do the work. → You don't need to catch the bottom or the top. The middle 60% is where the money is. On Patience & Timing → Cash is a position. Sometimes the best one. → The setup comes to you. You don't go hunting for it. → Boredom is profitable. Excitement usually isn't. → The best swing traders I know spend 90% of their time waiting. → "I need to be in something" is the most expensive sentence in trading. → When nothing looks good, nothing is good. That's information. → The market will be there tomorrow. Your capital might not. On Psychology → You're not trading the market. You're trading your beliefs about the market. → Revenge trading is just paying tuition twice for the same lesson. → Your worst trades will come after your best trades. Stay humble or get humbled. → Confidence after a win streak is the most dangerous feeling in trading. → The moment you think you've "figured it out," the market will remind you. → Trading well and making money aren't always the same thing. Focus on the process. → Journaling feels pointless until you catch the same mistake for the fifth time. On Simplicity → One pattern mastered beats ten patterns understood. → The best systems fit on an index card. → If you can't explain your edge in two sentences, you don't have one. → Complexity is where traders hide from accountability. → More screens ≠ more profits. Usually the opposite. On Reality → Social media shows entries. It never shows the exits, the drawdowns, the doubt. → The traders who make it aren't smarter. They just survived long enough to get consistent. → Markets change. Your principles shouldn't. → You will miss 100x runners. Doesn't mean your process is broken. → Being early is the same as being wrong-until it isn't. Manage accordingly. Took me many trades, and days away from the screen to finally internalize these. The market taught me everything. I just had to stop fighting the lesson. #Trading

Market pricing is efficient but emotional. At $54, it priced in a miracle. At $45, it's pricing in failure. $INTC -15% This is a bill getting paid, not the sector breaking. Capital didn’t leave semis. It rotated to the share beneficiary $AMD Here’s the part most people miss: In manufacturing, “sold out” isn’t bullish. It’s a margin tax when you can’t deliver. Q1 GM guide (~34.5%) was the receipt. Hot demand, cold P&L. Narratives don’t pay bills. Manufacturing does. Full audit in the article. Link in reply.

This was recorded in 2015. Theil is always 10 steps ahead:

You wanna know the real difference between buyin' stocks and buyin' options? Lemme give it to ya straight, no sugar, no TED Talk polish. Buyin' stocks is like marryin' the broad you met at the church picnic. Looks safe, respectable, long-term vibes. Everyone tells ya "time in the market beats timin' the market," and they pat ya on the back while quietly prayin' ya don't notice the slow bleed when the whole damn thing decides to take a dirt nap for 18 months. You own the thing outright. No expiration date. No theta vampire suckin' your blood every night. But here's the punchline: your downside ain't capped at jack shit. One bad earnings, one Fed pivot, one tweet from some orange lunatic, and suddenly you're down 40–60% holdin' the bag like a schmuck who thought "this time it's different." And the upside? Linear. Boring. You make a buck when it goes up a buck. Congrats, you're basically a glorified savings account with more drama. Now options—buyin' calls, specifically, the way a degenerate like me does it? That's walkin' into the back room at the casino with a crisp Benjamin, slappin' it on black, and knowin' the most you can lose is the Benjamin. Defined risk, baby. Uncapped upside. You pay the premium, you get your ticket to the rocket if the stock decides to moonshot. The market even hands you the odds on a silver platter: delta tells ya roughly your shot at breathin' at expiration, vega tells ya if the implied vol is screamin' "expensive" or "on sale," theta reminds ya every mornin' that Father Time is a cold-hearted bastard who charges rent. It's honest. Brutal, but honest. No pretendin' you're a long-term investor when you're really just hopin' for a quick pop. Most retail clowns lose on options because they treat 'em like lottery tickets instead of surgical weapons. They buy far OTM weeklies on meme stonk hype, pray for 10x, and get theta'd into oblivion 9 times outta 10. That's not tradin', that's charity for market makers. But when you play it smart—low IV entry, decent delta, enough time so you're not racin' the clock like a junkie—you get convexity that stocks can only dream about. Lose small forever, win huge occasionally. That's the game. So yeah, stocks feel safer... until they ain't. Options look scary... until you realize the scary part (the premium) is the only thing you can actually lose. Me? I'll take the honest asymmetry every time. Stocks are for people who like feelin' responsible while gettin' slowly divorced from their capital. Options are for people who understand the market is a rigged casino—and decide to be the guy who brings his own loaded dice.

The more I FAFO in the market, the more I understand options. They portray them as evil while showing the real risk upfront. Buying stocks seems safe as long as you're fooled by randomness.

Okay guys, I feel I need to address some things about the HBM market again, because the interpretation of the thesis is wrong. To make that very clear: people keep talking about HBM supply as if it’s constrained simply because memory is scarce. That’s only a small part of the story. HBM supply is constrained because each generation is tied to product timelines. This is something you need to imprint in your head. HBM, by default, is a platform-bound supply chain. What matters in a platform-bound supply chain is not how much memory exists, but when it’s available, where it fits, and which product generation it’s actually qualified for. HBM doesn’t move as one continuous market. It moves through product cycles from HBM3, to HBM3E, and eventually to HBM4. So again, to make it very clear: you can have strong demand and rising wafer output, with new fabs being built, and still end up with a very tight effective supply. And that’s not because wafers are scarce, or because you can just throw capex at the problem and make the constraint disappear. You can’t. HBM has to be qualified to a specific accelerator, with very specific specs, inside a very narrow window. And you have to do that over and over again, with every new product line. That’s the real HBM thesis. A company needs to show execution through successive qualification cycles. And this is really, really hard. Touching on that forward, HBM therefore does not scale in a straight line. It moves in waves, from product cycle to product cycle. • The first wave is the initial qualification window, when for example NVIDIA ramps up a new platform and only a small number of suppliers can ship at scale. • The second wave comes later in the cycle, as yields stabilize, packaging expands within the specs the customer wants, and additional suppliers are able to qualify. But this process is very uneven and highly timing-dependent. After that, the cycle resets with the next platform. You have to go through the full qualification process again: new specs, new designs, often new packaging techniques, and effective supply tightens all over again. And as an HBM supplier, you have no certainty that you will be qualified for the customer’s next product line. So now, relating this back to Micron and the 2027 projections: Micron’s strength today is real, but it’s very specific. It’s fully tied to being qualified on HBM3E into NVIDIA’s Blackwell ramp, which is currently at peak ramp. As explained above, when you are in that wave, supply is still constrained across yields, packaging, and depth of qualification. That’s what creates the powerful near-term earnings leverage you’re seeing right now. But projecting that straight into a permanent re-rating or assuming a clean path to $1.5T by 2027 treats a windowed platform ramp as a full baseline. That is not how HBM works. Not by default. Not by mechanics. Not by structure. If you recap everything above, even if HBM scarcity persists for all the reasons listed, future earnings still depend on staying qualified through successive platform transitions and absorbing volume without margin erosion. And all three players SK hynix, Samsung, and Micron are approaching this very differently. Micron’s strategy, specifically, is to be very strong in supplying the second wave. SK hynix focuses on deep platform integration and being qualified as early as possible. Samsung focuses primarily on scale. Will adress that later. But projecting a $1.5T valuation by 2027 without explicitly addressing all the execution risks tied to HBM as a product is, in my opinion, completely wrong. Right now, the memory market is being driven by a narrative that’s far too basic. I’m well over 200 hours deep into HBM research from supplier dynamics, to Jensen’s commentary, to management commentary from the major HBM players etc. And what you see today is a narrative being pushed that does not reflect the reality of how this product actually works.

Serenity @aleabitoreddit

5 months ago

$MU forward P/E is still ~11.6 It's projecting: - 133% Y/Y Revenue Increase - 319% Y/Y EPS Increase This is called the memory supercycle for a reason. Even after a 40%+ this month, it's still hasn't even been fully re-rated yet. At current prices, it would still be valued

57 87 998 887K 444

Drawdowns Oracle $ORCL -50% Netflix $NFLX -39% Facebook $META -24% Palentir $PLTR -22% Broadcom $AVGO -21% Microsoft $MSFT -20% Apple $AAPL -15% Nvidia $NVDA -15% Google $GOOGL -4% Hello, where did the $4T go?

$TSM is the AI factory that builds the chips that power every AI model on earth. Here’s how TSMC’s capex flows through the supply chain: • $ASML gates leading-edge AI output by controlling access to EUV lithography at each node transition • $AMAT benefits as AI chips add more layers and materials, increasing deposition intensity • $LRCX captures higher etch intensity as transistor density rises at advanced nodes • $KLAC enables yield & defect control so AI volumes can scale without margin erosion

The rare earth king, $MP, dreams of endless supply, Yet Trump's Greenland pact hits like a cruel supply-side high. More ore on the way? Cheers from the mine! But markets whisper: "Dilution, darling—prices decline!" So the play gets slapped with its own precious material, Crushed by the bounty it begged for—oh, ironical! Abundance is curse when you're priced for the drought, Welcome to paradox $MP, where winning means getting knocked out Fat Tony did it again

Once upon a time in early 2025, the SaaS kingdom sparked with fresh hope. After a tough stretch, $SNOW, $CRM, $HUBS, and others rebounded on AI dreams—"Just bolt on AI features, and valuations will soar again!" Stocks perked up as investors bet big on AI-powered tools reigniting growth. It felt like rebound magic! 🚀But the twist hit hard: the AI meant to save them became a dragon devouring their empires. Top line pain first—AI agents started automating workflows, slashing the need for multiple seats and subscriptions. Why pay for 10 $CRM or $HUBS licenses when one smart agent handles sales/marketing? Churn spiked, growth stalled, and legacy revenues got cannibalized by the very AI add-ons meant to boost them. Then the bottom line bled: datacenter frenzy gobbled GPUs, power, and capacity. Hyperscalers hoarded resources, driving up costs for SaaS players racing to run AI features. Capex ballooned, margins shrank, and many watched profits evaporate while infra giants feasted. By late 2025 into 2026, the "AI rebound" flipped to slump city. Traditional SaaS like $HUBS (-51% in '25), $CRM (-30%+), and others cratered as AI-native winners ($PLTR up huge) pulled ahead. The divide was brutal—horizontal plays drained B2B accounts slowly, dying of thirst as customers consolidated or switched to cheaper/faster AI alternatives. Now at the crossroads in 2026: Keep draining legacy B2B wallets and fade slowly... or find the new magic formula—shift to agentic/value-based pricing, go vertical/AI-native, or defend niches ruthlessly? Survivors adapt fast; the rest risk becoming relics. The tale's not over—what's your bet, traders?