Counter trade my tweets
Joined September 2009
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1/2 Thanks Gavin for an especially thoughtful exchange. I don't usually spend much time on social media but I wanted to engage here because it really brings out the heart of an important conversation.
First, on regulation, I think that “either concentrate it in the hands of a chosen few companies and politicians via regulation or distribute it widely” is a false choice. I know that there’s a sort of Silicon Valley shorthand where regulation = regulatory capture = concentration of power, but I’ve always found this to be an overly simplified picture of the world. Many people outside this bubble think of regulation as something that constrains corporate power and benefits ordinary people. I don’t necessarily agree with that perspective either, rather I think it’s complicated and really depends on what the “regulation” consists of. But in particular I think that those in the “regulation = regulatory capture = concentration of power” frame often underrate the decentralizing power of objective and fair institutional processes. A crude analogy is that the formal court system can sometimes feel stuffy and elitist, but it does a much better job of defending the rights of vulnerable individuals than the alternative, mob justice. At their best, institutions can vest power in ideas rather than people, and thereby decentralize that power.
This is why Anthropic has always made its policy proposals very carefully. We try very hard to make proposals that disadvantage (slow down) frontier AI companies while *advantaging* smaller competitors. California’s SB53 (which we supported), and even the much-maligned SB 1047 (which we were ambivalent on), completely exempt any company below a certain amount of revenue or model training costs from being covered at all (it was $500M for SB 53, lower for 1047 but we objected to that). More recently the testing process we’ve advocated for at CAISI and the White House involves more rigorous tests for frontier models than off-frontier models — something that differentially advantages challengers. Similarly, the “Pacing the Frontier” letter envisions (or at least Anthropic’s preferred implementation of it envisions) modulating the pace of the very best models while not constraining those who are catching up. This hurts the business interests of the frontier labs and helps challengers, including open-weights!
Overall my view is that AI is *structurally* a technology that tends to concentrate power, for reasons that have nothing to do with regulation (more to do with the extreme implications of the scaling laws). Open-weights do help some with this but are nowhere near a sufficient solution because they simply shift the concentration somewhat to those with the most compute and chips (which are roughly the frontier labs plus maybe hardware providers). By contrast I think the right “rules of the road” can simultaneously (a) address AI’s cyber/bio/alignment risks, (b) institutionally constrain the power of the frontier AI companies, and (c) leave room for open-weights models while also addressing the specific risks that they bring.
BTW I do not think that the events of the last few months have “failed to result in [my] preferred regulatory path”. The approach that the Trump administration is reported to be taking — pre-deployment testing for frontier models, and also testing of open-weights models when they get closer to the frontier — is one that I am very supportive of, though of course I have to see the details to be sure. I am also supportive of Demis Hassabis’ ideas around a FINRA-like entity. This contrasts with six months ago when most of the industry was still pushing for preemption of all state regulation and no apparent federal approach either.
what matters is “no one”’s behind it
This is sad!
You may or may not know, @TrustWallet faced this exact same bug years ago, a pseudo-random number generator, ie, not truly random, $12m in losses. They covered every user.
Software will always have bugs. What matters is who’s behind it.
i simultaneously think Anthropic would welcome reg capture but also believe themselves are doing the right thing.
I simultaneously think people who hate Anthropic can just not pay and use other models, no one’s fucking forcing you to yet they bitch endlessly and pay.
forced sell to fund dividend?
Strategy has sold 3,588 $BTC for $216 million to fund dividends on our Digital Credit securities. As of 7/5/2026, we hodl ₿843,775 in our BTC Reserves and $2.55 billion in our USD Reserves. strategy.com/press/strategy-…
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Claude Tag is a Trojan horse. Not because Anthropic is doing anything evil. Because the incentives are obvious.
Day one, this looks like a great feature: tag Claude in Slack, let it follow the thread, remember context, connect to tools, break down tasks, chase work, and act like a teammate.
But that is exactly the problem. The moment your AI vendor becomes a shared coworker, it stops being just a model provider. It starts becoming the place where work is interpreted, remembered, routed, and eventually executed.
That is not model lock-in. That is context lock-in. You are now renting your company back from them.
Models can be swapped. Agents can be copied. But the memory of how your company actually works is much harder, maybe impossible, to move: the Slack scar tissue, the exception paths, the customer promises, the unfinished threads, the weird workflows, the implicit owners, the “we tried that in Q2 and it failed” knowledge.
Once that lives inside one vendor’s agent layer, you are not renting intelligence anymore. You are renting your company’s operating memory.
And the pricing model makes it even more dangerous. A human coworker has a salary. Claude has unbounded tokenized activity. The more work moves through it, the more the vendor captures not just IT spend, but labor spend.
This is the enterprise bargain people will regret: Convenience now, and rapid decent into dependency.
The right architecture is simple: rent the best intelligence from whoever is best this month. OpenAI, Anthropic, Gemini, open source, whatever. But own the context layer.
Your company memory should be inspectable, permissioned, portable, and model-neutral. It should not be buried inside the same vendor that sells you the intelligence and the workflow surface.
Claude Tag is useful. That is why it is dangerous. Rent the intelligence, but own the context. Or, regret later.
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I think the challenge is that everyone can now build apps
But
1) almost nobody has distribution (like an audience), or
2) the money to pay for distribution (ads or UGC), or
3) the creative genius to get distribution for free (classically called guerilla marketing)
year 2030: software engineers are losing their jobs because 2021
Q: How are job postings for software engineers rising rapidly despite AI agents automating coding?
A: Because there’s far more code to manage than ever before. We’re already seeing a 14x YoY increase in GitHub commits, and it’s accelerating.
AI has dramatically lowered the cost of writing code, so it’s now being used across far more businesses, applications, and use cases.
We’re at the beginning of a massive productivity boom driven by the proliferation of bespoke software throughout the entire economy.
Coding has been AI’s breakout use case this year. The fact that it’s increased demand for software engineers — rather than decreased it — should call into question the entire “AI will cause mass job loss” narrative.
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He’s winding down the war and looking for an off-ramp but will blow up all their power plants unless they open the Strait which we don’t need and will open itself anyway which is why he might send ground troops to the country he already blew off the map.
hot take
while entire US celebrates Venezuela
if China or Russia did the exact same thing, we'd throw up in arms about communism and world invasion
what happened to Trump never enters war and US is not a world police?
republicans are just as bad as democrats
maybe just maybe, 24/7 kneel to trump, purchased a seat in the white house, high notoriety from a podcast have some impact on feeling safe?
it’s only biz
