Yamil retweeted
i've seen a lot of posts like this lately, where people bemoan the death of their hobbies, and it seems to boil down to one exact thing: they derive joy not from being able to do something themselves, but from others being unable to do it. if a random stranger failing to answer your quiz is enough to ruin your enjoyment of the hobby or the community, maybe you don't love it as much as you think you do.
Recently attended an in-person handheld game console hackathon. I wrote a raycaster by hand. Someone wearing a “I ❤️ slop” tshirt saw mine and said “oh I wrote a ray caster too!”. They showed me. It was a ray *tracer* and claude did all the work. The person didn’t know basic graphics terms. They couldn’t answer basic questions about how it worked, could only talk about their prompting harness. Sad how AI is ruining the craft and community for people that actually like to program and have spent their lives getting good at it.
Yamil retweeted
I regret letting Codex ever run with a /goal prompt or launch sub-agents.
It doesn't matter what model it is at this point. The Sol and Astra lineage are completely RL fried.
It doesn't matter how tight the prompt is or the agent instructions are. I've even had prompts and instructions externally reviewed and rewritten, but it doesn't change the behavior.
The model always goes off track, ignores scope, and finds a way to digress into scaffolding, certification machinery, evidence gathering or audits. Even with the literal words barring it from doing so are right there in the prompt, plan, or instruction file.
And it always ends in an absolute mess of junk files, slop code, and an account drained of limits.
Codex can only be used effectively through the tightest of handholding. Keep one-shotting whatever you want if it's working for you. But real work on an existing system is excruciating and nearly impossible.
They are shipping models they know don't follow directions and are nearly useless for real long-horizon work.
So, i found the best way to have good quality, while also saving a ton in codex usage. basically, have Sol Xhigh create plans, and orchestrate Luna Max threads to implement it, and review their output and ship it. if when reviewing found something bad, it just tells it to fix it.
GPT-5.6 Pro may have just solved a COLT 2026 open problem.
Under my prompting and direction, it produced a claimed proof that interaction is unnecessary for order-optimal 1-bit mean estimation—matching the adaptive rate for every k>1.
Preprint: zenodo.org/records/21515740
Yamil retweeted
Replying to @technorodrigo




























