We want to find creative and strategic and oftentimes totally experimental ways to build power for the cause of AI safety. This is obviously hard… because we’re working against the clock. And oftentimes we sink a lot of resources into things that we don’t know aren’t going to work until after the fact.
But I think there is one philosophy that tends to work for profoundly uncertain situations like this, which is: “If you do everything, you will win.”
— Sneha Revanur
Six years ago, aged just 15, Sneha Revanur founded the AI advocacy nonprofit Encode — back when AI felt like a niche issue. Now the world’s caught up with her, and she’s ready to share everything she’s learned about the politics of AI.
Encode has grown from a grassroots youth organisation to spearheading an unlikely coalition of AI-exposed groups — family-first conservatives, grieving mothers, Hollywood actors, and AI safety researchers — with the strength to take on $125m-funded anti-regulation lobbyists.
So far, Encode’s strategy of taking many experimental swings has netted major victories (including California’s frontier AI safety bill, SB-53, and New York’s RAISE Act) as well as some disappointing setbacks.
Going up against Big Tech hasn’t been easy. In 2025, OpenAI subpoenaed Encode’s general counsel at his home, with a sheriff’s deputy arriving while he was having dinner with his wife. The fallout went viral, resulting in more attention than Encode had ever experienced — and Sneha was forced to decide how hard to push back against a company she’d need to negotiate with for years to come.
In today’s conversation, Zershaaneh Qureshi interrogates some of Encode’s strategic moves. The pair discuss all the above, plus:
How the AI industry’s crypto-inspired anti-regulation strategy is not “AGI-pilled”
Why AI advocacy doesn’t have to be held back by the slow pace of policy
How mutual trust can hold together the unlikeliest of political allies
Advice for aspiring AI advocates — including how to balance political persuasion with rigorous reasoning
Due to technical issues, this episode was recorded across two days (May 26 and 28, 2026) and spliced together.
Our production team includes:
Video editors: Josh Alward, Dominic Armstrong, Jasper Luithlen, Milo McGuire, Luke Monsour, Simon Monsour, and Andrés Escobar
Producer: Nick Stockton and Elizabeth Cox
Coordination and support: Katy Moore and Lou Moran
Sneha Revanur founded the AI advocacy nonprofit Encode at the age of 15. Six years, two landmarkstate laws, and an OpenAI subpoena later, she argues that political advocacy is among the most neglected ways to make AI go well.
She outlines her pragmatic approach to influencing AI policy from the outside, and makes the case that state-level bills don’t need to be individually transformative to matter. Each win raises the bar for the next, building the political power and leverage needed to help regulation keep pace with capabilities.
And the fact that an unlikely coalition of grieving mothers, family-first conservatives, Hollywood actors, and AI safety researchers can overcome anti-regulation lobbyists with $125 million in funding suggests that Big Tech’s playbook is backfiring.
Advocacy is about building political power, not just passing bills
Sneha distinguishes between “politics” in the narrow sense (the slow grind of bills and hearings) and in the broader sense (building power for the cause of AI safety). Encode strives for the latter.
“If you do everything, you will win” is Sneha’s philosophy for profoundly uncertain situations. Encode’s creative, strategic and often experimental approaches sometimes fail, but also net big successes — like California’s frontier AI safety bill, SB-53.
Sneha argues the real value of bills like SB-53 isn’t the first-order effect of requiring safety plans (many companies were already doing this voluntarily), but building regulatory capacity in nimble, well-resourced states. If the federal government doesn’t act, those states could activate quickly.
SB-1047 had to fail so SB-53 could succeed
While the more ambitious SB-1047 — which Encode also cosponsored — was ultimately vetoed, Sneha insists it still had positive downstream effects that made SB-53 possible:
SB-1047 primed the legislature, established Encode’s working relationship with Senator Wiener’s office, built diverse coalition muscle, and socialised the idea of frontier AI regulation in Sacramento.
The bill got on Governor Newsom’s radar — to the extent he said it “created its own weather system” — leading him to convene a high-level expert commission whose transparency and whistleblower protection recommendations became the core of SB-53.
Having additional high-context safety advocates in the room allowed Encode to negotiate the inclusion of internal model deployments — crucial now the most capable models aren’t public.
And the standards keep rising. California didn’t pass third-party audits, but Illinois did. Each state win makes the next easier, as governments feel more comfortable following established precedents.
Unlikely coalitions are Encode’s strategic advantage
Encode started as a grassroots network of uncompensated students. But translating volunteer energy into actual outcomes proved difficult, so Encode pivoted to uniting groups with existing stakes in AI policy:
Family-first conservatives, mothers who lost children to addictive AI companions, Hollywood actors and Nashville singers worried about voice cloning, and AI safety researchers — all these disparate groups banded together to fight federal preemption (Congress’s attempt to block states from regulating AI and override existing state laws).
The side in favour of preemption, by contrast, failed to align any coalition of their own — with massive infighting among industry groups and the White House about how much to yield.
Mutual trust built through these fights compounds over time. When stakeholders believe in Encode’s analysis and integrity, they tend to give the benefit of the doubt and be more open to negotiation on specific bill points.
Sneha is clear that Encode maintains “very clear internal bright lines” to avoid diluting its aims to appease the lowest common denominator.
Sneha’s strategic restraint after OpenAI’s subpoena
This went viral, giving Encode more visibility than it had ever had. But it was stressful too: with worries texts would be accessed and conversations with legislators leaked.
Sneha denounced the intimidation tactics, but her response was deliberately measured. She reasoned they would keep facing OpenAI’s lobbyists in every state, and being good-faith in their criticism would be healthier for the long-term relationship.
OpenAI’s attitude to regulation has since shown signs of shifting — Sneha attributes this partly to increasing internal dissent towards the company’s lobbying, as well as growing public anger around AI.
Anti-regulation lobbying on AI is backfiring
Sneha is strikingly unworried by the $125 million raised by Leading the Future (the anti-regulation super PAC). Her argument:
This approach misreads the political landscape; it’s “fundamentally not an AGI-pilled strategy” — it’s what you do if you haven’t internalised that AI is going to be a transformatively important political issue.
Anti-regulation efforts borrow from the crypto playbook of spending big to shape politics, but public concern about AI is already widespread enough that this strategy isn’t landing
Some candidates targeted by Leading the Future have actually seen boosts in name recognition and fundraising.
2028 could be the most important presidential election in history
Whoever wins the next election could end up being the first president to hold the keys to transformative superintelligence, or at least make major world-historic decisions about AI.
Sneha is increasingly concerned about power-concentration risks: it’s likely the executive branch will be the first to grasp how powerful AI is, leaving the judiciary and legislature in the dark and disrupting the balance of power. Which is why she’s excited about accelerating AI adoption in the latter two to counteract this asymmetry.
Advice to aspiring advocates: learn to toggle between soldier and scout
Sneha believes AI advocacy is “one of the most under-resourced and talent-constrained ways to make AI go well” and “literally the coolest job in the world” for the right type of person. But she has a warning:
Politics rewards fluency in persuasion: building relationships, distilling messages, managing coalitions. If overdeveloped, you risk mastering a message you’ve never stopped to question.
AI safety rewards sharp, unsparing analytical thinking. Careful epistemics mean the community has been right about many things. But this doesn’t automatically make things happen in the world.
Practicing one of these mindsets tends to erode the other. The challenge is shifting between the two: knowing when to take action, and when to step back and ask yourself if you could be wrong.
Sneha’s final tip for aspiring advocates is that the AI safety community is unusually approachable and nonhierarchical. Newcomers should take advantage of this: reach out to people you admire, pick their brains, ask questions. People are often willing to share what they know, regardless of seniority.
Highlights
Advocacy isn't just passing bills, it's building power for AI safety
Zershaaneh Qureshi: Now, the politics world moves notoriously slowly and unpredictably. So I want to know how confident you are that this legislative route that Encode is taking can actually be successful if we do get to AGI in just a few years, or if in fact your efforts are mostly targeting worlds where we have more time to act.
Sneha Revanur: The way that I think about this is there’s “politics” in the narrow sense of the word — the slow grind of bills and hearings, and sort of strictly thinking about things as like passing legislation — and there’s “politics” in the broader and maybe more ambitious sense of the word, where it’s about building power.
And I think we really strive for the latter. We want to find creative and strategic and oftentimes totally experimental ways to build power for the cause of AI safety. This is obviously hard, as you pointed out, because we’re working against the clock. And oftentimes we sink a lot of resources into things that we don’t know aren’t going to work until after the fact. But I think there is one philosophy that tends to work for profoundly uncertain situations like this, which is: if you do everything, you will win.
I think Encode takes a lot of swings. Some of them were successful. Others we, like I mentioned, didn’t know would fail until we tried. For example, I was really proud to see the California and New York laws passed with the leadership of our determined sponsors — Scott Wiener, Alex Bores, and Andrew Gounardes.
These laws are obviously first steps, and I can see how a sceptic could dismiss their impact on the margin. But the real win here is not the literal first-order effect of the fact we are now requiring companies to submit safety plans — because obviously many of the companies were already voluntarily doing so — it’s that we are building regulatory capacity in nimble and well-resourced states that are able to potentially activate on short timelines if the federal government doesn’t act.
The unlikely alliance fighting for AI regulation
Sneha Revanur: I think one thing that has been pretty surreal to see over the last year especially is just the sheer number of strange bedfellows that have banded together for the cause of AI safety — like extremely strange bedfellows. You have these forceful coalitions of family-first conservatives who think that we are gambling away the human spirit, and moms who have lost their children to addictive AI companions, and singers in Nashville and actors in Hollywood who want to protect their likeness from voice cloning.
It is exactly this team effort across people with very different terminal goals, very different political backgrounds, that has helped us stave off, so far, federal preemption of state AI laws — this attempt in Congress to block states from regulating AI, and also override existing laws like the ones that we helped pass in California and New York, whether or not the federal framework that’s replacing it is better than what we’ve already gotten.
And it seems to me that without some degree of active coordination, without a lot of mutual trust building, not all of these different preemption stakeholders would have found their way to each other. So I’m really proud that we’ve been able to contribute to this alongside allied orgs…
And if you want to know how hard coalition building is, you can take a look at the fact that the side in favour of preemption has clearly failed at aligning any coalition of their own. There are these massive disagreements among industry groups and the White House and all these trade associations, all this infighting about exactly how much to yield and what affirmative position to actually take besides “preempt everything we don’t like” — which is why they haven’t been able to come forward with any sort of framework that would satisfy any key parts of our coalition or get anyone to peel.
The next US election could be the most important in history
Sneha Revanur: Looking ahead to 2028, it’s no doubt that this very well could be the most important presidential election year in history, right? There are a lot of reasons for this. Whether or not AI timelines are shorter or longer, there’s a whole range of outcomes where this could either be the person who will be in charge of the intelligence explosion, or, in any case, this will be a person who is making some very major world-historic decisions about AI, and we want this to be a person that we trust to have a lot of context and to be a person we would really trust with the keys.
One thing I’m also thinking quite a bit about is power-concentration risk: what will it mean to empower this person with superintelligence, potentially? And who would we trust to hold the keys in that moment?
One thing I’m really concerned about is it’s very likely, based on what we’re seeing so far, that the executive branch is going to be the first to wake up to just how powerful AI is, and is really going to leave the judicial branch and the legislative branch in the dark, which will just really mess up the balance of power. I think there’s already been some concern about this, and I think this will potentially get substantially worse once we actually have much more powerful models and much more national-security-relevant models.
So one intervention that I’m really excited about is speeding up AI adoption among the judicial branch and the legislative branch, to kind of counteract some of that balance-of-power issue and make sure that we don’t have all of this power singularly concentrated in the hands of the executive.
The crypto playbook won't work for AI
Sneha Revanur: There is this interesting misapprehension in Silicon Valley that capital eats the world and is fully fungible into political outcomes. Like there’s some market where you can just go buy your preferred reality, right? Like when all you have is a hammer, everything looks like a nail. It is definitely true that money can influence elections, but you either want to have the tailwinds of public support for you to amplify, or be spending on an issue where no one is paying attention.
This is part of why the pro-crypto PAC Fairshake has been so successful. I think they had like a 90% candidate success rate in 2024, which is absurd and honestly very impressive. But crypto is a low-salience issue that is not driving people to the polls anytime soon. So in that case, the spending actually does make a huge difference on the margin and can reliably spook candidates into submission.
And a16z is one of the top funders of Fairshake. OpenAI’s Chris Lehane, who runs the Global Affairs team, literally helped set up Fairshake after his time at Airbnb. Josh Vlasto, who runs Leading the Future, was an advisor to Fairshake. So it’s the exact same architects who seem to think that they can just get the gang back together and run the same playbook and get the same results.
This is fundamentally not an AGI-pilled strategy. Honestly, it’s funny how often you can completely demystify why some person is acting a certain way if you just model them as not being sufficiently AGI-pilled. Because the stuff that LTF is doing is not what you would do if you saw the writing on the wall that AI is going to be a big deal politically; if you saw the writing on the wall, from the fact that the public is souring on AI already and wants more regulation.
The two conflicting skillsets for effective AI advocacy
Sneha Revanur: I think the first [piece of advice] is a very specific challenge that comes with AI advocacy: you are signing up to practice two opposite habits of mind at essentially the same time, and getting good at one really tends to erode the other.
On the one hand, politics rewards fluency in persuasion: you’re building relationships and managing coalitions, you are learning how to distil messages and make different audiences tick. And there is one overdeveloped version of this skill where you can be the master of some message that you never actually stopped to ask yourself if you genuinely believe.
On the other hand, what’s normally rewarded in AI safety circles is very different: it’s sharp, unsparing analytical thinking; very careful, sometimes even fastidious epistemics. You’ll sit down and you’ll make an offhand comment, and someone will be like, “I don’t see why that would be true,” and proceed to really carefully interrogate what you said as if it were some very important substantive claim. And this is good, because it’s why the community has been so right about so many things when everyone else was wrong. But it doesn’t automatically make things happen in the world.
This is a crosspost from the new Animal Welfare Alignment Newsletter by Anima International. You can subscribe on Substack if you are interested in following these efforts. Audio reading also available on Substack.
The goals of this post are to:
1. Raise a question I see as crucially important to the goal of aligning AI to animal welfare...
I used AI to fix transcription errors, rerrarange the ideas, and suggest tweaks to the title and some sentences.
Three of the most exciting projects to come out of EA in recent years are, in a vague sense, CEA spinouts:
* Kairos is directly a spinout of CEA and now handles most support for university AI safety groups. Basically everyone I've found who knows them is really excited about what they do
* NEST is an opinionated ideas-fi...
Hello! I'm Justin Portela. I got hired by GWWC to make YouTube videos after AI in Context did such a kickass job.
My channel is using that same cinematic, high-production value beauty to talk about everything in the EA universe that isn't AI.
...
