There will be no AI jobpocalypse. The story that AI will lead to massive unemployment is stoking unnecessary fear. AI — like any other technology — does affect jobs, but telling overblown stories of large-scale unemployment is irresponsible and damaging. Let’s put a stop to it. I’ve expressed skepticism about the jobpocalypse in previous posts. I’m glad to see that the popular press is now pushing back on this narrative. The image below features some recent headlines. Software engineering is the sector most affected by AI tools, as coding agents race ahead. Yet hiring of software engineers remains strong! So while there are examples of AI taking away jobs, the trends strongly suggest the net job creation is vastly greater than the job destruction — just like earlier waves of technology. Further, despite all the exciting progress in AI, the U.S. unemployment rate remains a healthy 4.3%. Why is the AI jobpocalypse narrative so popular? For one thing, frontier AI labs have a strong incentive to tell stories that make AI technology sound more powerful. At their most extreme, they promote science-fiction scenarios of AI “taking over” and causing human extinction. If a technology can replace many employees, surely that technology must be very valuable! Also, a lot of SaaS software companies charge around $100-$1000 per user/year. But if an AI company can replace an employee who makes $100,000 — or make them 50% more productive — then charging even $10,000 starts to look reasonable. By anchoring not to typical SaaS prices but to salaries of employees, AI companies can charge a lot more. Additionally, businesses have a strong incentive to talk about layoffs as if they were caused by AI. After all, talking about how they’re using AI to be far more productive with fewer staff makes them look smart. This is a better message than admitting they overhired during the pandemic when capital was abundant due to low interest rates and a massive government financial stimulus. To be clear, I recognize that AI is causing a lot of people’s work to change. This is hard. This is stressful. (And to some, it can be fun.) I empathize with everyone affected. At the same time, this is very different from predicting a collapse of the job market. Societies are capable of telling themselves stories for years that have little basis in reality and lead to poor society-wide decision making. For example, fears over nuclear plant safety led to under-investment in nuclear power. Fears of the “population bomb” in the 1960s led countries to implement harsh policies to reduce their populations. And worries about dietary fat led governments to promote unhealthy high-sugar diets for decades. Now that mainstream media is openly skeptical about the jobpocalypse, I hope these stories will start to lose their teeth (much like fears of AI-driven human extinction have). Contrary to the predictions of an AI jobpocalypse, I predict the opposite: There will be an AI jobapalooza! AI will lead to a lot more good AI engineering jobs, and I’m also optimistic about the future of the overall job market. What AI engineers do will be different from traditional software engineering, and many of these jobs will be in businesses other than traditional large employers of developers. In non-AI roles, too, the skills needed will change because of AI. That makes this a good time to encourage more people to become proficient in AI, and make sure they’re ready for the different but plentiful jobs of the future! [Original text in The Batch newsletter.]

We have left-leaning and right-leaning AI labs. But who's building a southern-leaning lab? Call it country intelligence. Trained to focus on beers, trucks, getting your boots dirty. Dario invokes a country of geniuses in a data center. We want country geniuses in data centers.

Visiting most of the leading Chinese AI labs, I'm struck by a culture that's extremely well suited to building LLMs with fewer resources, but one happening in a very different ecosystem, more companies at play, almost no data industry, etc. Full report:

Anthropic and OpenAI slammed the this week on secondary transactions of their shares as both AI labs race to list. To help @jason and @alex unpack the market-moving news, investors @jefielding @davemcclure and @lessin joined our venture capital panel to make plain which Anthropic investing vehicles are legit, and which may be fake. The group also dug into software moats, large venture funds pressuring smaller firms, the future of LP capital, and the IPO market! 0:00 Guest introductions 1:30 Guest introductions 2:36 Anthropic voids unauthorized SPV trades 9:23 Accredited investor reform & the SEC sophisticated investor test 9:40 Quo (formerly OpenPhone) - Quo gives you a clean, modern way to handle every customer call, text, and thread all in one place. Try it free at 12:25 Naval's USVC closed-end fund as a workaround 17:23 Plaud: If your work depends on conversations — interviews, meetings, calls — you need a Plaud NotePin. You can check it out at and use code TWIST for 10% off! 18:30 Pro-rata rights battles: when Series A investors push seed investors out 20:18 Grasshopper Bank: Time is money. Don't waste either. Go to and get an exclusive $500 cash bonus just for opening an account. 29:55 Pilot: Focus on your product, let Pilot handle your bookkeeping. Pilot provides the most reliable accounting, CFO, and tax services for startups and small businesses. Head to and get $1,200 off your first year. 31:05 Storing wealth in stories vs. cash flows 35:01 Cerebras and Fervo Energy IPOs — meaningful liquidity? 38:36 Will SpaceX, Anthropic, OpenAI IPOs redistribute capital or compound it? 46:40 The $15M Series A founder who returned the money because of Claude 50:43 Should founders pivot or return capital when the world changes? 57:25 OpenAI's $6.6B tender and Shruti Gandhi's viral SF cost-of-living tweet 1:01:07 Intercom rebrands to Fin: the AI-first late-stage pivot 🎥 Watch the full episode here 👇

𝐅𝐮𝐥𝐥-𝐏𝐚𝐫𝐚𝐦 𝐑𝐋 𝐧𝐨𝐰 𝐚𝐯𝐚𝐢𝐥𝐚𝐛𝐥𝐞 𝐟𝐨𝐫 𝐊𝐢𝐦𝐢 𝐊𝟐.𝟔 You've been told only 3 AI labs matter. The best AI apps never believed that. @cursor_ai, @vercel, @genspark_ai don't run only off-the-shelf models. They train on open-source bases with their own data and run continuous RL to pull ahead. LoRA gets you in the door. Full-param RL is true model ownership for the maximum data moat. Today, Kimi K2.6 full param tuning is now available on Fireworks Training. 256K context. Train the whole thing. Ready to get started?

Diamond partner Bright Data is what 70%+ of the world's leading AI labs use to train their models. From large-scale video data for robotics training to reliable agentic web access in production - it's the web data infrastructure the AI industry runs on. SuperAI Singapore, 10-11 June.