๐ ๐ฎ๐ธ๐ฒ ๐ฌ๐ผ๐๐ฟ ๐๐ผ๐ฑ๐ฒ๐ฏ๐ฎ๐๐ฒ ๐ช๐ผ๐ฟ๐ธ ๐๐ผ๐ฟ ๐๐ ๐๐ด๐ฒ๐ป๐๐
Your AI agent writes valid code. It still fails. Wrong package manager. Wrong test flags. Business logic in the wrong folder. This is not a prompt problem. This is a repo problem.
AI agents do not have tribal knowledge. They do not ask your team for help. They match patterns in your files. Your repository is the interface.
Try this litmus test:
- Delete chat history.
- Start a fresh session.
- Give one real task.
- Do not paste architecture essays.
- Check if it finishes using only committed files.
If it fails, you carry the load. The agent is only typing.
Fix this with an AGENTS.md file. Put it at the root of your project. It is a plain text map for all agents.
Include these sections:
- Project overview.
- Exact commands for install and test.
- Key directory structure.
- Coding conventions.
- Files to never modify.
Follow these steps:
- Match local scripts with CI scripts.
- Use llms.txt for document pointers.
- Add short READMEs in confusing folders.
Treat agents like new senior engineers. They need clear rules. They do not attend onboarding.
Stop blaming the model. Fix the infrastructure.
Source: https://dev.to/devansh365/how-to-make-your-codebase-work-for-ai-coding-agents-without-better-prompts-kcb Optional learning community: https://t.me/GyaanSetuAi