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@poteto

grok @bot at @SpaceXSI. react compiler core team, prev cursor, meta, netflix
OC x.ai/bot/plugin/971… Joined September 2014
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lauren Verified account @poteto
here's how i shipped 2,500 PRs last month to production

this was originally supposed to be for Cursor Compile in London. i couldn't make it since i was livestreaming for Grok @Bot Galaxy so i'm making it available for free here on X! watch it on 2x speed, i talk slowly
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lauren Verified account @poteto
hot take: you don't need a software factory, and i don't love the term. it's just marketing

all you need is good software engineering and investing your tokens in the right places. the more deterministic the better (and token efficient)
dax Verified account @thdxr 2d
all the companies selling you a software factory produce a shockingly tiny amount of software
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lauren Verified account @poteto
while i'm quite bullish on formal methods, i think it's worth tempering expectations and doing your own research on it (disclaimer: i am not an expert in it). it cannot guarantee your code is bug free, only that it matches the spec under certain assumptions, and the specs come from what people want, not math. as long as we build software for humans, nothing can prove that your spec is right, only you can judge.

i created the /statechart skill in pstack primarily because it helps make the state machines implicit in your code more obvious and legible to you, so you can shrink the review surface and review the work at a higher level: does it actually match your intent and goal? i used this skill a ton while building my game tibo.dog, below you can see the statechart for story mode where i was able to find many bugs with it.

in that sense, i think model checking (eg TLA+ with TLC) is quite useful for understanding and checking properties of your system e2e, and you don't have to write tons of new verification code for it. the spec isn't your actual code so there's always a risk of drift, but so far i've had good experiences finding actual bugs with it. i tend to pair it with empirical verification (running the code) also to confirm it's real

other types of formal verification like proving theorems (eg Lean, Dafny), bounded model checking (eg CBMC, Kani) etc have their own tradeoffs. proofs cover every possible input, but only for the properties specified, and it takes a lot more code/work. bounded model checking can run on your actual code, which avoids drift, but it only checks up to a certain number of steps, so it's better at finding bugs than proving there aren't any

so i think in the near-medium term you'll still need to layer your codebase: constraints and guardrails (types, lint rules, api design, refactoring), empirical verification (tests, evals, real usage), and formal verification for the parts that really need it. none of these catch everything on their own, but layered together, they catch a lot more and shrink what's left for you to review

but also maybe in the limit, the bitter lesson will prevail and flawless code will just be printed out perfectly every time with no bugs. even in that scenario, /statechart still seems very helpful in confirming that the agent understood your intent correctly. give it a try if you haven't already!

github.com/cursor/plugins…
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lauren Verified account @poteto
some fun slides from my upcoming talk @aiDotEngineer

very excited to share how we ship crazy amounts of code (30x'd) without reading it, yet perf is as good if not better then when we launched

there's a lot more to improve of course, and the ceiling is far from being reached, but given the relentless shipping speed and our high bar for polish, i think that our agent friendly architecture bets are paying off at taming the slop

fun fact: ~230 people landed at least 1 PR to grok bot in october!
First AIE Code Summit speakers:

@poteto, Principal Engineer @ SpaceX
@steve_yegge, Engineer, Writer, Advisor
@zachbruggeman, Principal Software Engineer @ Ramp

Nov 10-12, SF. Come hang out with us. Apply at ai.engineer/code
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