I talk to engineers at other companies every day and hear the same thing: one person is 10x'ing their output with Claude but the rest of the org hasn't caught up. Watching teams adopt AI, I keep seeing the same 4 steps. I mapped them out here: Steps of AI Adoption claude.ai/code/artifact/bfdf…

I don't think people understand just how risky it is to try and use their Google Gemini subscriptions outside of Google's official surfaces. You can get your ENTIRE GOOGLE ACCOUNT BANNED. OpenAI or Anthropic ban? Annoying but whatever Google account ban? Legit life ruining.

Anthropic used to actually clarify the weekly limits for Claude Max back in July 2025: Max 5x: 140–280h/week Max 20x: 240–480h/week (~1.7x more weekly usage than 5x) then they removed the numbers and never published them again. so now there’s not even an official estimate for how much more weekly usage you’re actually getting.

Hi Tobi, thanks for the feedback! We are working on making Claude Code more hackable, which will include being able to easily use Agents.MD or make other system prompt modifications. I’ll share more here when it’s ready to roll out. Our reasoning for this was that we don't think that model families are interchangeable and the system prompt can have a big impact on performance. I wrote here: x.lingyaoai.com/trq212/status/20807109… on how Claude models like their skills, system prompt, Claude.MD, etc to be formatted. In Claude Code we have different system prompts per model. That said, I know this is a lot of upkeep and not worth the squeeze for everyone. Feedback heard and I'll keep you posted. In the immediate term, you can always @Agents.MD from your Claude.MD.

a wall of text and an army of sycophants to Thoughtfully Not Deny the original accusation of "Dario says Anthropic might be the only private company in the world at some point"... oh, and btw Dario is totally not spreading pdoom or massive human disempowerment fears, no no you all hallucinated that and misread it all on bad faith! shame on you, dear readers and users for all of your own skill issues!

I am doing my best to stop back from this subject as it should be obvious what we are seeing here. However the arrogance that us commoners are too dumb to catch his grift must be addressed. Receipts: Dario Amodei’s carefully worded reply is a masterclass in having it both ways. He frames regulation as a nuanced force for decentralization while his actual track record and recent actions scream regulatory capture designed to protect Anthropic’s closed, frontier position. The contradictions are not subtle; they are structural. He insists the “concentrate via regulation or distribute widely” framing is a “false choice,” and that Anthropic’s proposals deliberately disadvantage frontier labs while advantaging smaller competitors and open-weights. Look at the evidence. Anthropic was the glaring holdout from Jensen Huang’s open-weights letter—signed by Nvidia, OpenAI, Google, Meta, Microsoft, SpaceX and dozens of others. Amodei’s July 2026 clarification that “Anthropic has never advocated for a ban on open-weight models” arrived only after the absence drew accusations of protectionism. He still rejected the letter’s core claim that open-weights help defenders more than attackers, leaning hard into biology attacker-defender asymmetry instead. Incongruent at best. That is not “leaving room” for open-weights; it is carving out a privileged safety-testing regime for “sufficiently capable” models (open or closed) that inevitably raises the bar for anyone trying to catch up. Compute thresholds and mandatory third-party audits favor the labs that already have the capital, talent, and lobbying muscle—i.e., Anthropic. The same pattern appeared with SB 1047: Anthropic was “ambivalent,” pushed amendments that safety advocates said weakened preemptive accountability, and later celebrated exemptions that conveniently applied only below certain revenue/compute levels. Calling this “hurting the business interests of the frontier labs” while Anthropic is one of the largest frontier labs is pure theater. On messaging he claims balance—one major essay on benefits (Machines of Loving Grace), one on risks—and blames negative clips on media incentives. Reality is the opposite. Amodei’s public record is a steady drumbeat of catastrophic framing: AI that will “test us as a species,” bioweapons capable of millions of casualties, 50% entry-level white-collar job destruction, nation-state-level “country of geniuses in a datacenter,” and the explicit call in Policy on the AI Exponential(June 2026) for government power to block or reverse deployment of models that fail third-party tests. The positive essay exists; the dominant, repeated, high-salience output does not. Gavin Baker is right that this rhetoric is now ammunition for anti-datacenter campaigns. Amodei cannot simultaneously warn that the technology is so existentially dangerous it requires FAA-style pre-deployment veto power and act surprised when the public and local activists take him at his word. Dario is the poster boy for that Anti Clanker movement, just ask them. He further claims his preferred path is succeeding under the current administration’s reported testing regime. Yet the industry-wide rejection of broad open-weights restrictions (everyone but Anthropic signed the letter) and the rapid backlash when his own earlier risk language was turned against Anthropic’s models demonstrate the opposite. His own June essay handed policymakers the exact rhetorical and policy tools that later constrained his company. That is not strategic consistency; it is the predictable outcome of maximalist risk rhetoric from a player whose commercial model benefits from higher barriers. Yet plays the game like it’s not his fault like it is 2008. No one of thought buys it outside the Ends-Justifies-The-Means EA/LessWrong club house. The deeper contradiction is the one he never resolves: he admits scaling laws structurally concentrate power in the hands of those with the most compute and chips, then claims the right “rules of the road” can simultaneously constrain frontier labs and protect open-weights. Those two statements cannot both be true under the policies he actually advances. Mandatory testing for models “when they get closer to the frontier” is a moving gate that keeps the frontier club exclusive. Open-weights that lack “dangerous capabilities” are a public good—until they become competitive, at which point the testing regime kicks in. Even Claude points this out, go check. This is not good-faith institutionalism. It is a closed-lab CEO who has an almost Enron level crisis arguing that the institutions he prefers will benevolently constrain him while the evidence shows those same institutions raise rivals’ costs and keep the most capable systems behind closed APIs. The skepticism is earned. He will return to his ivory tower as he said, he has no time for us commoners on “social media”. as if X is “social media” seeing he brought this story to our real town square.

2/2 Second, on the messaging around AI.  I do not agree that my messaging has been disproportionately negative.  In fact it has been about equally balanced between risks and benefits: I’ve written one major essay about each, and even in interviews where I discuss the risks, I make sure to frequently mention the incredible benefits as well as proposing possible solutions to the risks (short clips from my interviews that end up on social media tend to be disproportionately negative, as that gets clicks).  In fact, I wrote Machines of Loving Grace because I didn’t feel the AI industry was painting an inspiring enough picture of how the technology could radically transform the world for the better.  The bulk of the essay is devoted to refuting skepticism of AI’s potential in health and biology, and showing why I think it will actually be possible to cure most human disease in ~5-10 years, as crazy as it may sound to ordinary people and frankly to biologists as well (I used to be one!).  And, if you read my most recent essay (Policy on the AI Exponential), I discuss concrete proposals for how to streamline the FDA process to make sure the deluge of AI-accelerated drugs isn’t slowed down by the regulatory process.  I feel the urgency here: I lost my father to Hepatitis C only a few years before the development of direct-acting antivirals (sofosbuvir), which cure 95% of patients and probably would have cured him. I do agree that the public has a negative view of AI (and that this is a big problem), but I don’t think it is primarily caused by me or any other AI leader warning about AI’s risks.  I think it is fundamentally a crisis of trust.  I think that ordinary people don’t trust companies, governments, or the tech industry and always suspect that we are cooking up some new way to screw them over.  The causes of this go back decades and AI is just the latest iteration of it.  I don’t think that a glitzy marketing campaign with a positive spin (which some have advocated that Anthropic do) is the way to win back that trust — at this point, saying that AI will cure cancer is more a cliche than it is inspiring, and most people think it is deceptive.  The thing that will work is *actually curing cancer*.  I think by far the most accurate criticism of AI companies including Anthropic is that we haven’t yet delivered on our big promises to benefit the world.  That is totally on us, and I think it’s the criticism you should be making, instead of all this stuff about messaging and marketing. We are however doing our best to fix this: Anthropic is ramping up its efforts very quickly in biology and medicine, and we hope to have incredible results in the coming years and some early glimmers in the coming months.  When we’ve actually accomplished something real, the whole world will hear about it, as loudly as possible, you have my word on that.  But until then I don’t want to make empty promises, and in the meantime I feel compelled to speak honestly about the very real risks of AI and how to address them.  Honesty is the right thing on the merits, and in terms of public credibility and trust it is no worse than, and may in fact be better than, an approach that ignores or distracts from risks which people instinctively understand are real.