David Sacks

Some people are saying x.com/chetanp/status…

Mark Zuckerberg gets it right: “The defining question of our age isn’t whether superintelligence will exist, but who will have access to it. Will it be centralized and restricted to a few institutions, or will it be a tool that empowers everyone?” Concentration of power is the biggest risk of AI. When a small number of labs (working hand-in-glove with the administrative state) decide who has access to which model capabilities, they inevitably shape what can be said, known, and built. That’s not “safety.” It’s control. As Mark points out, the history of open source shows that broad access and transparency are usually the best path to actual security and resilience. Decentralization creates checks and balances on power. By contrast, centralized alternatives, like bureaucratic approval regimes and mandatory gatekeeping, typically produce regulatory capture and reinforce cartels. Personal superintelligence in everyone’s hands, with competing models and real data sovereignty, is a far better check on a dystopian future than self-appointed guardians who claim to be “aligned” with all of humanity.

Anthropic maintains that it is entitled to train for free on all the world’s output, even if the author objects. But if a competitor trains on Anthropic’s output after paying for it, that is IP theft. The hypocrisy is breathtaking. x.com/itsolelehmann/…

Narrative violation. WSJ today.

The entire tech industry (save for Anthropic) has come out in favor of open source AI. So what happens next? Will Anthropic change its lobbying efforts? Not likely. Now the gaslighting begins: “Nobody is trying to ban open source.” “We just want to limit who can use it.” “We just want to limit who can contribute to it.” “We just want to limit how powerful those models can be.” “We just want to make sure the guardrails (we lobbied for) can’t be removed.” The net effect will be the same. They won’t stop until they kneecap open source. The rest of the industry needs to watch these guys like a hawk.

Nobody is saying that all software has to be open source. What they’re saying is that open-weight AI should be allowed. By implication, they’re rejecting your company’s incessant machinations to kneecap the open model ecosystem. Read the room. x.com/mononofu/statu…

Strong first post! x.com/JensenHuang/st…

It’s true that Anthropic is the fastest growing company that Silicon Valley has ever seen. Which is all the more reason their incessant attempts at regulatory capture are not just unnecessary but frankly gross. x.com/benioff/status…

Secretary @howardlutnick is right. The Kimi Panic needs to stop. — American frontier models are still ahead. When you factor in what’s in the lab, the gap is even larger. As long as we keep releasing, we will stay ahead. Let our horses run. — As Ben Thompson showed, Kimi’s apparent cost advantage largely disappears once you account for higher token usage and the real cost of running a model this size. Open weights still require expensive infrastructure. — Anthropic and OpenAI are growing revenue at rates that Silicon Valley has never seen before at this scale. This remains the clearest test of who is winning the market. President Trump’s light-touch regulatory approach is working. We should remain confident in American innovation. As long as we don’t sabotage ourselves with unnecessary rules, the U.S. will continue to win.

Cernovich is right that AI + Big Tech could easily turn into Big Brother. But what’s the alternative to living off the grid or in the Panopticon? The third option is to run your own AI on your own hardware, retaining data sovereignty. That’s why open source matters. It’s software freedom.

Great news! @patrickjwitt will be staying to take Clarity across the finish line. x.com/patrickjwitt/s…

Thank you for all your hard work @HarryYJung! It’s been a pleasure working with you. x.com/harryyjung/sta…

Kimi K3 just fixed 15 critical security bugs that Codex and Fable refused because of “cyber guardrails.” There’s no reason to limit American models on tasks that Chinese models handle without issue. We’re only making ourselves less competitive. x.com/callebtc/statu…

Here’s another example: Hugging Face tried using American frontier models to analyze an AI-powered cyber attack. But the guardrails blocked requests containing real exploit payloads so they switched to GLM 5.2 running locally. The guardrails actually impaired defensive security. x.com/clementdelangu…

I’m not sure whether Dean Ball is confessing to a regulatory capture strategy or simply predicting this will happen (he now says the latter). Either way, the weaponization of regulatory uncertainty as a competitive tool should be completely unacceptable. He argues there’s no need to ban Chinese open-source models — just direct agencies to issue soft-law warnings that create enough FUD so regulated enterprises back off. “It needn’t be that well justified.” Wrong. Regulatory decisions should always be well justified and grounded in facts, logic, and evidence, not the deliberate exploitation of fear and uncertainty. Implementing a surreptitious policy through manufactured doubt — rather than strong and explicit justification — corrodes the rule of law and invites future abuse against anyone. We are at a critical inflection point in AI policy. The leading closed labs, already a duopoly in terms of AI model revenue, want the government to eliminate their open source competition. They have laid their cards on the table. It is time for the rest of Silicon Valley — the vast majority that still values open competition — to do the same.

OH: “i’ve switched to Kimi from claude for a bunch of work. it’s just so much more fun because it just does the thing instead of lecturing you” Woke lobotomized models are the enemy of American competitiveness.

This is *exactly* what I predicted would happen. I said Chinese models would have advanced cyber capabilities within a matter of months and the only thing to do about it was to use AI-powered cyberdefense to protect our systems. Trying to gatekeep models doesn’t work. x.com/scmallaby/stat…

This is concerning. For the first time, a Chinese model Kimi K3 has taken #1 on the Frontend Code Arena and is scoring at or near the frontier on other benchmarks. Meanwhile America is tying itself in knots: politicians and bureaucrats are banning new data centers, piling on state regulations, and pushing for new federal agencies to pre-approve frontier models. This is how you lose the AI race. The rest of the world won’t play by our rules if we bog ourselves down. Permissionless innovation is how America won the internet and became the technological envy of the world. We can do it again with AI -- while addressing risks in a targeted way -- or we’ll watch our lead evaporate.

UPDATE: “Artificial intelligence giant Anthropic is pursuing a strategy of one-upmanship that encourages states to impose increasingly tougher AI guardrails, rather than align around a single set of regulations.” Politico 7/15/2026 politico.com/news/2026/07/1…

Legacy Media types are calling this Alex Karp interview a “crash-out” so that’s your first clue that he is actually saying something extremely insightful. He is articulating what real “AI safety” looks like in the enterprise. Not abstract alignment research or certification by a government-run DMV for AI. Real AI safety for businesses is the ability to control their own data, model weights, and compute — so a frontier lab can’t hoover up their proprietary knowledge and turn it into their next product. As Karp explains, technical customers want “control over their compute, their models, their data stack, and their alpha. They want to know they own the means of production, and it’s not being transferred to someone else.” Don’t think that can happen? Just look at Figma. According to The Information, Anthropic “blindsided” its then-business partner with the launch of Claude Design. Figma’s founder said Anthropic had not been “consistently honest” with them. Anthropic’s chief product officer had even served on Figma’s board until three days before the launch of Claude Design. Figma’s stock has fallen sharply this year while Anthropic’s valuation has surged. This isn’t an isolated example. Anthropic has launched Claude Science, Claude Security, Claude Legal, and of course Claude Code — each expanding into categories previously served by companies building on top of their models. The pattern is consistent: watch where value is being created, then move in directly. Dominate the model layer, then use that position to capture the most lucrative verticals. Dario has argued that open source models powerful enough to compete with Anthropic are “dangerous.” But dangerous to whom? Not to enterprises that want to retain control over their data and workflows. Dangerous to a business model that benefits from customers having few real alternatives at the model layer. As Karp exposes, true enterprise safety isn’t trusting that a lab’s future roadmap won’t include your business. It’s retaining the ability to choose — at the model layer — who gets to see and use your alpha.

UPDATE: This is a fascinating post by @satyanadella building on Alex Karp’s point about AI sovereignty. Satya names it the Reverse Information Paradox: enterprises don’t just pay for intelligence with money — they pay again by feeding frontier models their proprietary knowledge, corrections, traces, and evals. That institutional know-how then compounds inside the provider. Karp diagnosed what technical customers actually want: control over their compute, models, data stack, and alpha — to own the means of production rather than have it transferred. Satya explains why the current regime structurally does the opposite, and what enterprises must do about it: establish a real trust boundary with private evals, proprietary learning loops inside the tenant, decoupled orchestration, and the explicit right to fine-tune on their own outputs. That’s how your alpha compounds for you instead of leaking to the model layer. x.com/satyanadella/s…

Narrative violation: A new study of 21,559 firms in the U.S. finds that “companies that adopt AI tend to grow faster following adoption”. “Firms making the largest AI investments grow employment by roughly 10% following adoption, while low-intensity adopters see no statistically significant change.” “Entry-level headcount rises 12% for high-intensity adopters.” “Gains emerge gradually and are broad across roles, including engineering, sales, administration, and customer service.” “The results counter predictions that AI adoption will lead to broad job loss.” The study is based on observed AI spending from Ramp card and bill pay data linked to Revelio Labs workforce records.

Sources: Study: ramp.com/data/ai-jobs-i… Charts: ft.com/content/8026ea…

A year ago, President Trump declared that America was in a global AI race and that the way to win it was to be pro-innovation, pro-infrastructure, pro-energy, and pro-export. President Trump was exactly right; we deviate from that strategy at our peril.

Today was the day that Gavin Newsom was supposed to save the tech industry by cutting a deal to kill the Billionaire Tax Act. Instead he came out as DSA-adjacent, and BTA will be on the ballot in November. See y’all in Texas! x.com/gavinnewsom/st…

Claude psychoanalyzing Dario is the AI slop I didn’t know I needed.

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True. And this is exactly where an “FDA for AI” will lead. x.com/ns123abc/statu…

This brilliant lesson on communication by @rabois is why the AI leaders are failing. It’s not sufficient just to “speak your truth.” You have to communicate in a way that elucidates your audience. Convincing the public that your company is a menace obviously fails that test.

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Yes

Some recent articles have created a misleading narrative that I did not take Mythos seriously or tried to downplay the cyber threat. This is based on egregious cherry-picking of my comments and (since the real target is the Trump Administration) needs to be corrected. When Mythos Preview first launched, I pointed out that Anthropic has a history of scare tactics, but then immediately went on to say that “we have no choice but to take this seriously” and that every CISO and IT department should move quickly to harden systems against AI-powered cyberattacks. Here’s what I said on the April 10 All-In Podcast (3 days after launch of Mythos Preview): “Anytime Anthropic is scaring people, you have to ask, is this a tactic, is this part of their chicken little routine, or is it real? With cyber, I actually would give them credit in this case and say, this is more on the real side. “It just makes sense that as the coding models become more and more capable, they’re more capable of finding bugs. That means they’re more capable of finding vulnerabilities. That means they’re more capable of stringing together multiple vulnerabilities and creating an exploit. “I do think that every company, or IT department, or CISO that is managing code bases should take this seriously and use the next few months to detect any dormant bugs or vulnerabilities and roll out patches.” I posted similar framing on X: On April 10: “The world has no choice but to take the cyber threat associated with Mythos seriously. But it’s hard to ignore that Anthropic has a history of scare tactics.” (With examples attached). On April 12: I noted that a growing number of people were wondering if Anthropic was the AI industry’s “boy who cried wolf,” and that the company would face a serious credibility problem if the threats didn’t materialize. These are the lines the articles highlight. They emphasize the “scare tactics” / “boy who cried wolf” critique while omitting the parts where I said the cyber threat itself was real and required immediate action. It is entirely possible to question a messenger’s track record while still treating the underlying risk as serious — and that’s exactly what I did. By the way, this view isn’t unique to me or even particularly controversial; highly respected tech commentator Ben Thompson recently made a similar critique about Anthropic. On April 30 I posted a more technical thread after tests by the AI Security Institute showed that GPT-5.5-Cyber performed similarly to Mythos: “Mythos is not magic. It’s not a doomsday device. It’s the first of many models that can automate cyber tasks (just like coding). … these models do not create vulnerabilities; they discover them. The bugs are already in the code. Using AI to discover and patch them will actually harden these systems. “The leap from pre-AI cyber to post-AI cyber means that there will be a big upgrade cycle. … it’s important that cyber defenders get access before cyber attackers. That process is already underway but needs to happen quickly.” My position remains consistent: We are on a shot clock until Mythos-level capabilities diffuse widely, including to non-U.S. / Chinese models. We need defenders to find and patch vulnerabilities before that happens. This requires cooperation between government and industry. Unfortunately Anthropic’s needlessly confrontational posture toward the Administration has distracted from that mission. Policy debates have their time and place, but right now tangible defensive action is what matters most. I hope everyone moves forward on that basis.

Narrative violation.

Full article: wsj.com/tech/ai/the-jo…

Happy Birthday President Trump! It’s been an honor to work for you. Thank you for your extraordinary leadership in Making America Great Again. Wishing you a wonderful 80th birthday filled with health, happiness, and continued success ahead!

I’ve had a number of conversations with folks inside and outside government about the current situation with Anthropic, and here is what I believe to be true: — As we know, Anthropic publicly released its Mythos class models earlier this week under the commercial name Fable. — Fable is Mythos with guardrails. But if those guardrails fail, then you’ve exposed Mythos and its advanced cyber capabilities to people who shouldn’t have them. (Keep in mind that Anthropic itself widely promoted the idea that Mythos was a cyberweapon and needed to be regulated as such. They asked for government regulation of Mythos and championed the guardrails on Fable. If there is a vulnerability — big or small — it is Anthropic’s responsibility to patch.) — A highly credible trusted partner of both Anthropic and the USG who was testing Fable came forward with a jailbreak of those guardrails. The Admin asked Dario to fix the jailbreak or de-deploy the model. Dario refused. — In their blog post, Anthropic defended its decision by saying the jailbreak isn’t serious. That is not what the trusted partner and the USG believe; nor is that kind of minimizing language consistent with Anthropic’s brand as the AI safety company. It’s difficult to fathom how they could claim a jailbreak allowing operability of a cyber weapon could be defined as not “serious.” — In the past, Anthropic has always said that safety must be top priority and taken super seriously. In this case, Anthropic prioritized the continued offering of the consumer model over safety. — In reaction, the Admin issued the export control. The Admin did this reluctantly. It’s been very surprised that Anthropic hasn’t wanted to cooperate with a reasonable safety request (ie fixing the jailbreak issue). Anthropic’s reaction is very much at odds with their branding and ethos as a safe AI research community. — The Admin’s hope now is that Anthropic remediates the safety issue, the export control is lifted, and Fable goes back into general release. The Admin wants all of this to happen as soon as possible. It is frankly bewildered that Anthropic hasn’t wanted to comply with safety requests that it previously said were its highest priority. — Those trying to misdirect and tie this action to the prior DoW/Anthropic issues are wrong. The Admin values Anthropic’s technical capabilities and feels that this issue, while serious, should be easily resolved. The ball is in Anthropic’s court.

If you were wondering what the "pause" was all about, Ben Thompson @stratechery has an interesting theory: "Late last week the Anthropic Institute released a new safety report warning about the danger of recursive self-improvement... I don’t think the timing is a coincidence. This is a company and leadership that has been honing safety-and-scaremongering-as-marketing-tactic ever since Amodei led the charge to close source OpenAI models because GPT-2 was too dangerous; it’s always fun to see the evolution of tactics, capabilities, and goals, and in this case publishing a widely-discussed report the week before you cite it to silently degrade your offering for potential competitors is impressive."

Worth reading. x.com/tony_davis_x/s…

About 8 months ago, I warned that “Anthropic is running a sophisticated regulatory capture strategy based on fear-mongering.” This take was controversial at the time; now look how many people are saying it. x.com/davidsacks/sta…

Thanks to Legendary Larry Kudlow for having me on the show today to talk about the dangers of over-regulating AI. @larry_kudlow @FoxBusiness foxbusiness.com/media/ex-white…