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Comment by nayroclade | Hacker News Reader

I suspect AGENTS.md files will prove to be a short-lived relic of an era when we had to treat coding agents like junior devs, who often need explicit instructions and guardrails about testing, architecture, repo structure, etc. But when agents have the equivalent (or better) judgement ability as a senior engineer, they can make their own calls about these aspects, and trying to "program" their behaviour via an AGENTS.md file becomes as unhelpful as one engineer trying to micro-manage another's approach to solving a problem.

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It's a best practice to document things about the code base, so that other devs (even senior devs) don't start to do things differently. This will probably not change

What I think is short lived is this insistence in separating LLM instructions from general documentation for both humans and AI. LLMs can read human docs, and concerns about context window size will probably disappear

But maybe future docs will be LLM-first, but people won't read them directly. They will ask a LLM questions about it

I think AGENTS.md will still have a place regardless. There are conventions, design philosophies, and project-specific constraints that can't be inferred from code alone, no matter how good the judgment

Eh, even for a senior engineer, dropping into a new codebase is greatly helped by an orientation from someone who works on the code. What's where, common gotchas, which tests really matter, and so on. The agents file serves a similar role.

Yup, readmes exist for a reason even for meat bags

Except that most READMEs are seemingly written more for end-users than for developers; and even CONTRIBUTING files often mostly just document the social contribution process + guidelines rather than providing any guidance targeted toward those who would contribute. There’s a lot of “top-level architectural assumptions” detail in particular that is left on the floor, documented nowhere. Which “works” when you expect human devs to “stare really hard and ask questions” until they figure out what’s being done differently in this codebase; but doesn’t work at all when an LLM with zero permanent learning capability gets involved.

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