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anself • today at 1:24 AM • 2 replies • view on HN

Most of these issues are vastly improved or mitigated by adding clear instructions in AGENTS.md.

I follow a specific process with agents, and it works reasonably well: 1) describe my intended feature or change and then say “please recapitulate my intention and write an implementation plan” 2) read the plan carefully and refine it, make any corrections 3) tell the agent to go, but I check in frequently as it’s going. I watch the stream of thought and make course corrections or pull it out of rabbit holes 4) carefully review the result. Checking that tests actually fail, removing unnecessary changes 5) add instructions in AGENTS.md if I’ve found a new behavior that needs redirection


Replies

greenowl • today at 1:32 AM

Honest question: how much time are you saving versus ignoring that all of this exists and instead just jumping right in and coding yourself?

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fn-mote • today at 1:37 AM

Unlike the OP, this makes using an agent actually sound useful.

My summary of the article: I use a really cheap LLM, and suffer like everyone else using GPT 3.1. This is definitely a throwback to the days not so long ago when LLMs were completely incompetent.