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Discussion (23 Comments)Read Original on HackerNews
But everything your harness looks at could be this. So the skills in your code base, the commands that you've added, the memories that were auto created, they all work towards improving or completely destroying your productivity.
And most of it is hidden. You hear people talk about this all the time where they'll be like, Oh, I use GSD or I use Superpowers and my results have gotten worse.
Your results might have gotten worse precisely because you use them (along with your memories and other skills).
I start a whole lot of my sessions with "Run tests with 'uv run pytest'" and once they've done that they get the idea that they should write tests in a style that fits the existing ones.
For existing files, the agent will carry on a bad structure unless you specifically ask it to refactor and think about what's actually helpful.
In general, it should be a lean file that tells the agent how to work with the project (short description, table of commands, index of key docs, supporting infra, handful of high-level rules and conventions that apply to everything). Occasionally ask the agent to review and optimize the file, particularly after model upgrades.
Also curious how well LLMs can self-reflect in a loop, in terms of, here's how the previous iteration went, here's what didn't go well, here's feedback from the human, how do I modify the docs I use in a way that I know I'll do better next time.
I know you can somewhat hillclimb via DSPy but that's hard to generalize.
Notice that the harness is just unceremoniously dumping the AGENTS.md file into the exact same text stream as the system prompt, barely contextualizing that hey, starting now, this text is from AGENTS.md and not from the harness.
If you want AGENTS.md to work (likewise, if you want skills or anything else to work) you have to know how the harness is handling/feeding them to the LLM, because no LLM will reliably look on their own.
Bonus points if you can force them into context without needing the agent to make a tool call, based on touching the files or systems near them. (my homegrown agent has this feature)
the AGENTS.md pieces that pin specific tool-call shapes or force chain-of-thought before action are coping that ages out, same lifecycle as the retry-with-different-prompt loops or chains of thought prompt most stacks shipped in 2024 to compensate for brittle instruction-following.
not quite there yet, but it's nice to see them being shorter and shorter as model release until all the basic are peeled out by the march of progress and one day only the invariants will be left there
I feel like we've passed the point where an average-effort Claude Code / Cursor / Codex initialized (like basic docs, skills) project would produce a better product (not just code) than if you hired a median programmer to work on that project.
People really do think too highly of themselves.