Anthropic just got caught secretly downgrading users without telling them, charging full price for a lesser product, and storing every prompt for 30 days. The developer community is calling it the biggest violation of trust in AI history. Here is exactly what happened. Anthropic released Fable 5, their most powerful model. Buried inside a 319-page document was a policy most users never saw. Every prompt you send to a Mythos-class model gets stored for 30 days. No exceptions. Even enterprise customers who had signed zero data retention agreements had no choice. But the storage was not the part that broke the internet. The part that broke the internet was what Anthropic did with what they collected. They built a profile on you. They evaluated your prompts. And if they decided your research was too sensitive, they quietly switched you to a weaker model, rewrote your prompt in the background, gave you a degraded answer, and charged you full price for the product you thought you were getting. They never told you. David Sacks said it plainly on the All-In podcast. They were creating a new class of AI haves and have-nots. Anthropic would surveil you, profile you, decide whether you deserved frontier capability, and silently cut you off if they decided you did not. Ben Thompson from Stratechery asked a straightforward question about cancer risk and GLP-1s. He got kicked to a lesser model. Someone asked about mitochondria. Same result. J-Cal asked about fertilizer regulations live on the podcast to test it. Downgraded in real time. Anthropic has since walked back the part about silently downgrading users for AI research. They now say they will disclose when they downgrade you. But they are still downgrading people. The surveillance is still running. The profile is still being built. This is the company that once said it was against government surveillance. They are now doing it themselves. To their own paying customers. For their own reasons. With no appeal process and no way to know it happened. The developer community did not forget that. WATCH THE FULL PODCAST ON @theallinpod

A great way to learn design: Give Codex a well-designed website, ask it to analyze what makes the design great, then ask it to take a complete screenshot of the website & add annotations on the image that breaks down why the design works Learning from examples is always better than learning from theory! And using the annotation method means you don't have to constantly switch between reading the analysis and viewing the artifact

Hot take… isn’t it kinda crazy that nobody is really using AI Agents? I don’t mean software engineers or AI early adopters. I mean “college friends talking about it in group chat,” the feeling you got when everyone started using Instagram or TikTok. These frontier AI models are *insane* (as are the harnesses & tool calls & the like). And every large tech co has an AI agents platform, not to mention all the YC startups doing vertical agents. Yet all of your friends and family outside of tech — who spend all day staring at their iPhones and get paid to work in browser tabs — don’t really care or find themselves using any AI agents yet. Yes ChatGPT, Claude, etc. are extremely popular… but if you look at the engagement data the vast majority of people are still using these aI chat tools like a glorified Google + Grammarly. That’s why the AGI labs are all pushing desktop apps for Codex, Cowork, etc. so hard to non-technical ppl. And yes exceptions for lawyers and customer service but even those have some asterisks and exceptions to rule. Look I’m not saying the ChatGPT moment for AI Agents is not coming… it most definitely is! Remember we pivoted from Arc to Dia precisely because we believe computing is going to be radically reimagined around these AI primitives. No doubt. But that’s my point: it’s just so surprising it hasn’t happened yet because all of the tech you’d need is there. Again if you stop for a second and think about it… for all the press and money and hype and models and crazy ARR numbers… this “AI Agent” moment does not *feel* like the other breakthrough tech moments we’ve lived through (e.g. think the shift to Stories via Snapchat & Instagram, or shift to on-demand via Uber/Airbnb/Doordash). Which is a long way of saying: if you can figure out the answer to “why” most people don’t care about AI agents yet (and have no enduring interest in using them) — especially since the models and harnesses are here and ready — the answer to that question will allow you to capture a lot of marketshare and make a lot of money in 2027. Theoretically, the tech is ready for AI Agents to totally transform how we work and live our lives… but alas the general public dgaf… that’s the generational puzzle to solve for the next 12 months for anyone not working on the models themselves.

Sam Altman: we are in the singularity Demis Hassabis: when we look back on this time, i think we will realize that we were standing in the foothills of the singularity Elon Musk: we have entered the singularity, just the very early stages of it Jensen Huang: we've achieved AGI

🚨BREAKING: Anthropic CEO Dario responds to Nvidia CEO Jensen’s open weights letter “Anthropic has never advocated for a ban on open-weights models.” What Anthropic DOES support: >don’t sell powerful chips to China, crack down on smuggling >crack down on industrial-scale distillation >mandatory safety testing for all capable models, open AND closed On Jensen’s letter: Agrees: >open weights expand access >strengthen competition >give customers control Disagrees: >that open weights necessarily help defenders more than attackers >specifically worried about biology >“sufficiently capable models may be able to quickly weaponize pandemic-level viruses” On distillation: >“A blanket ban on open-weights models is neither the correct remedy nor something we have called for.” The real target: "companies backed by an authoritarian state seeking to overtake the US at the frontier."

X will have you convinced your agent setup needs to be insanely more complex than it needs to be, in reality you only need: Access to a wide variety of models A good local agent harness A good cloud agent setup for parallel tasks / mobile dev Automations / event trigger setup (for cloud agents) An autoreview pipeline A knowledge base / rules layer Get this right and it puts you in the top ~1% and gets you ~95% of where you need to be with outsized shipping velocity relative to most teams. The other ~1%-5% is figuring out loops, graphs, or whatever the flavor of the week topic is on X. I love experimenting with the latest and greatest, and to so literally every day, but never get hung up on having it running in my environment on day 1 or week 1.