Last week @a_ramabadran, @tobiges, and I hooked up Codex (Astra) to a rented Toyota Corolla + a @comma_ai and had it drive us around a parking lot. We tried a few others (Fable, Grok) but Astra was the clear winner, and the only one to complete our course. Harness is open sourced for anyone else that wants to have codex drive them around ;)
I used Opus 5.5 to formally verify the Claude Agent SDK using Lean. A couple short prompts = 16 PRs fixing various bugs and race conditions. Video attached.
TLA+ also works well. I sometimes combine Lean and TLA+ to look for issues around data flow, concurrency, and state mgmt.
I don't know either language well, but Claude is excellent at both. This approach is super useful for formally modeling your code and finding bugs that a human probably wouldn't have spotted.
Is formal verification the future of coding (or at least, bug finding)?
Trying to evaluate Jev! But it’s not easy since Jev doesn’t natively take vision inputs (so the demos you’ve seen of it playing games etc required giving whole state… which we can’t do.) Trying to build out a pipeline that utilizes it and its speed well, pairing it with Luna for perception…
We gave ChatGPT, Claude, and Grok control of a real Toyota Corolla 🚗, steering/gas/brakes, no human driving (just a foot over the brake).
Only one model was able to complete our entire driving course. Introducing DrivingBench. 🔥⌛️🏁
Been thinking about the great sloppening and impending entropy blow up of scientific publishing. Feels like the only way to combat the scaling of sci-slop is by scaling automated reproducibility, centralizing it, and making it more of a first class aspect of the reviewing process... of course, someone's gonna have to pay for the tokens, but maybe theres data one could farm to subsidize the cost. who's building this?
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