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> High performers have built infrastructure that makes AI effective And yet these "high performers" ship nothing but thousands of words of how AI makes them pe
by troupo 6mo ago
> High performers have built infrastructure that makes AI effective
And yet these "high performers" ship nothing but thousands of words of how AI makes them performant, or hundreds of thousands of the worst quality slop you can imagine (see Garry Tan's GStack, Steve Yegge's Gastown etc.)
> 650 work arcs clustered into distinct types.
And the result of these arcs are?
At this point I lost all interest in the navel-gazing, AI-generated or AI-corrected verbiage that can rival Yegge's, and no idea what he spent all these 543 autonomous hours actually doing.
- mrothroc 6mo agoI addressed this in my reply to kelseyfrog above. The short version: the production work is proprietary, the tooling I used to do the analysis is open source.
- troupo 6mo agoYeah, it's "my code is lives in another (gas) town, you wouldn't know her". Same for some undisclosed opensource projects. I can't imagine letting any LLMs do 500+ hours of autonomous work on any code at my company, or even for my own project (hundreds of thousands of lines of unreviewable slop? no thank you). Especially for the amount of features you claim they implement from scratch. I also don't believe anything about "2 agents running for 12 hours" given how fast they exhaust context, become extremely stupid, and completely ignore most of previous work on subsequent runs, and will happily ignore any explicit instructions. Despite any "guardrails". Funnily enough literally right now in my current session Claude has "forgotten" most instructions from its global memory *and* its local CLAUDE.md