Nick Fitz

+100 @demishassabis

Selina and myself on the China US race - we need to understand the critical importance of the arrival of reasoning by computer and make sure we get the right products to benefit everyone, not just a few nytimes.com/2026/07/11/opi…

+1

Some bittersweet news to announce today: I recently left @IFP to join @coeff_giving as Managing Director of Public Policy, where I'm building a new US AI policy team, overseeing the Abundance and Growth Fund alongside @mattsclancy, and managing CG's government affairs work. Building IFP has been the defining professional project of my life, and this was one of the hardest decisions I've ever made. In just four and a half years, our team became, pound-for-pound, the most effective think tank in DC. I feel insanely proud of the work we’ve done and the incredible team we’ve assembled. I sometimes joke that when @alecstapp and I launched IFP, we felt like two kids in a trench coat pretending to be a think tank. And now we're a proper institution! But it feels possible to step back now because they've hit escape velocity. The talent density at IFP is bonkers. And I have complete confidence they'll keep racking up counterfactual policy wins with Alec at the helm and our superstar directors. I'm staying on the IFP board and staying in DC. In some sense the new role is a continuation of the old one. All of IFP's policy issues are reflected in CG's portfolio, but now I'm working at a new layer of the stack. So why leave? Because AI is hitting Washington like a tsunami, and DC is still radically underprepared. I hold a lot of uncertainty about timelines, but it seems very plausible that the next 2–10 years will bring the fastest technological upheaval we've ever had to navigate. The new team I’m leading is a bet on how to prepare: proactively scanning the horizon, identifying gaps in the policy ecosystem, headhunting founders, and launching new organizations, while strengthening the democratic institutions that will have to steer through the transition to powerful AI systems. I've written an essay laying out the larger vision here: calebwatney.substack.com/p/a-long-seque… There is no master plan or silver bullet here. I suspect getting AI "right" is going to feel more like a chaotic, iterative process of institutions trying to make better decisions over time as the facts change underneath them. As John von Neumann wrote in 1955 about mastering an earlier technological revolution: “What safeguard remains? Apparently only day-to-day — or perhaps year-to-year — opportunistic measures, a long sequence of small, correct decisions.” Each of the small, correct decisions ahead will look small only in the sweep of the full historical picture. Up close, every one of them will require heroic levels of effort and coordination. Coefficient Giving is scaling rapidly to meet the moment, part of what Nan Ransohoff has called the “third wave of American philanthropy”, potentially large enough to fund thousands of new projects and organizations. The binding constraint is unlikely to be money. It will be people: grantmakers and policy entrepreneurs and others with the judgment to make a long sequence of small, correct decisions, and the ambition to build the institutions we wish we had. I'm hiring a team of exactly those people, starting with generalist grant makers and a chief of staff. If you share this vision, please apply! And if you are building something that we’ll need in the years ahead, reach out. jobs.ashbyhq.com/coefficientgiv…

some personal news: i'm thrilled to share that i’ll be joining @Miles_Brundage and the Al Verification and Evaluation Research Institute (@AVERIorg) team as Director of US Policy. i'll be working on frontier ai governance, with a focus on building the public institutions, standards, auditing systems, and evaluation regimes we need for meaningful oversight of advanced Al systems. i’m deeply grateful for my two years at Public Knowledge, where i’ve learned from exceptionally thoughtful and principled colleagues. more to come soon!

(!)

woot!

My bio says I work on AGI preparedness, so I want to clarify: We are not prepared. Over the last year, dangerous capability evaluations have moved into a state where it's difficult to find any Q&A benchmark that models don't saturate. Work has had to shift toward measures that are either much more finger-to-the-wind (quick surveys of researchers about real-world use) or much more capital- and time-intensive (randomized controlled "uplift studies"). Broadly, it's becoming a stretch to rule out any threat model using Q&A benchmarks as a proxy. Everyone is experimenting with new methods for detecting when meaningful capability thresholds are crossed, but the water might boil before we can get the thermometer in. The situation is similar for agent benchmarks: our ability to measure capability is rapidly falling behind the pace of capability itself (look at the confidence intervals on METR's time-horizon measurements), although these haven't yet saturated. And what happens if we concede that it's difficult to "rule out" these risks? Does society wait to take action until we can "rule them in" by showing they are end-to-end clearly realizable? Furthermore, what would "taking action" even mean if we decide the risk is imminent and real? Every American developer faces the problem that if it unilaterally halts development, or even simply implements costly mitigations, it has reason to believe that a less-cautious competitor will not take the same actions and instead benefit. From a private company's perspective, it isn't clear that taking drastic action to mitigate risk unilaterally (like fully halting development of more advanced models) accomplishes anything productive unless there's a decent chance the government steps in or the action is near-universal. And even if the US government helps solve the collective action problem (if indeed it *is* a collective action problem) in the US, what about Chinese companies? At minimum, I think developers need to keep collecting evidence about risky and destabilizing model properties (chem-bio, cyber, recursive self-improvement, sycophancy) and reporting this information publicly, so the rest of society can see what world we're heading into and can decide how it wants to react. The rest of society, and companies themselves, should also spend more effort thinking creatively about how to use technology to harden society against the risks AI might pose. This is hard, and I don't know the right answers. My impression is that the companies developing AI don't know the right answers either. While it's possible for an individual, or a species, to not understand how an experience will affect them and yet "be prepared" for the experience in the sense of having built the tools and experience to ensure they'll respond effectively, I'm not sure that's the position we're in. I hope we land on better answers soon.

@luke_drago_ lol

I’m no longer going to try to explain the vibe in SF to DC people. I’m just going to send them this.

@BenGoldhaber this is hilarious

I'm already tired of the phrase foothills of the singularity. how about we're in the piedmont region of the intelligence explosion

@leonardtang_ woot!

moving to sf start of august looking for housing / roommates plz reach out if down to hunt together in this capricious sf housing market

We’ve received notice that the Department of Commerce has lifted export controls on Claude Fable 5 and Mythos 5. We'll begin restoring access tomorrow, and will share an update soon. We’re grateful to our users for their patience, and to everyone who worked with us on redeploying the models.

As engineering, product, design, DS, etc. melt into a new kind of role, I was reflecting on what roles might look like in the future. For example, when I look at the Claude Code team I see what I think is five archetypes: 1. Prototyper: comes up with brand new ideas; churns out many ideas, most of which don't ship 2. Builder: quickly turns a prototype/idea into production-grade product/infra 3. Sweeper: cleans up the UI, simplifies the code and system, unships, optimizes performance 4. Grower: takes a product that has been built and iterates on it to improve Product-Market Fit 5. Maintainer: owns a mature system to make it secure, reliable, fast, and efficient as it scales Many people span across 2 roles, and sometimes 3 roles. I also notice that these roles are not really tied to job function -- eg. across Anthropic, some designers match category 1, some 2, some 3; same for engineers, PM, DS. A healthy team needs a mix of these, depending on the product: - A product that is new and pre-PMF needs people that are strong at 1+2+3 - A product that is growing and has found PMF needs 2+3+4 and some 5 - A product that has strong PMF needs 3+4+5 and some 2 Maybe product roles of the future will look more like this, and less like the domain-specific roles of today?

the inimitable @Kristian_Ronn in @billyperrigo’s piece in @TIME, “Can the Cold War Teach Us How to Slow Down AI?” “I would hate it if we had to choose between the extremes of a global pandemic [designed by AI] killing us, or a totalitarian state monitoring our every move…Both of these extremes seem really, really bad… What we're saying is that you can actually, through cryptography, maintain privacy and have security at the same time.” “We want [verification technology] to exist, we want it to be red-teamed with nation-state actors and the labs, and ready to go…We don't want to be too late. Being too late here has real world consequences.” cc @Will4Planet @DarioAmodei @reidhoffman @tristanharris @aza @JasonGMatheny @RepLoriTrahan @JayObernolte @soundboy @EileenDonahoe @ericschmidt @ghadfield @hendrycks @moskov @VitalikButerin @Gregory_C_Allen @crmiller1 @Miles_Brundage @albrgr @woj_zaremba @jackclarkSF Bri Treece Jeff Alstott Conrad Stosz

lol @griff_bohm

sam altman: we are a few 1000 days away from building god. we will build suns on earth, unify physics and resurrect the worthy dead garry tan: sounds like this will be really impactful for startups sam altman: definitely. no better time to be a startup

interpretability can help you do targeted and more efficient training - this is a cool preview of the future

I joined @Stripe in January to build a new philanthropic initiative with @nanransohoff. Today we’re announcing Intercept, a $500m innovation fund focused on radically reducing the burden of respiratory viruses. I’ve spent the past decade investing in vaccines and drugs for infectious disease, and this is the most exciting thing I’ve ever been a part of. Thrilled to be working with @Stripe, @AnthropicAI, @TheFluLab, @FoundationOAI, @coeff_giving and individuals from Jane Street. We've raised the capital and now it’s time to get to work.

we're hiring for a bunch of technical GTM roles at @GoodfireAI across forward deployed engineering, sales, and growth come help us understand every model across biology, materials, robotics, language, and more apply here or DM me: goodfire.ai/careers