I use aider to work on the aider code base, which is approaching 30k lines of python. Aider writes about 70% of the new code in each release [0]. So it's doing

I use aider to work on the aider code base, which is approaching 30k lines of python. Aider writes about 70% of the new code in each release [0]. So it's doing some fairly heavy lifting in a non-trivial code base. Some pragmatic tips: - Work with AI like a junior developer, except with unlimited energy and no problem being corrected repeatedly. - Provide the AI with guidance about conventions you expect in your code base, overall architecture, etc [1]. You can often use AI tools to help write the first draft of such "conventions" documents. - Break the work down into self-contained bite sized steps. Don't ask AI to boil the ocean in one iteration. Ask it to make a sequence of changes that each move the code towards the goal. - Be willing to explore for a few steps with the AI. If it's going sideways, undo/revert. Hopefully your AI tool has good checkpoint/undo/git support [2]. - Lint and test the code after each AI change. Hopefully your AI tool can automatically do that, and fix problems [3]. - If the AI is stuck, just code yourself until you get past the tricky part. Then resume AI coding when the going is easier. - Build intuition for what AI tools are good at, use them when they're helpful. Code yourself when not. Some things AI coding is very helpful for: - Rough first draft of a change or feature. AI can often speed through a bunch of boilerplate. Then you can polish the final touches. - Writing tests. - Fixing fairly simple bugs. - Efficiently solving problems with packages/libraries you may not have known about. [0] https://aider.chat/HISTORY.html https://aider.chat/HISTORY.html [1] https://aider.chat/docs/usage/conventions.html https://aider.chat/docs/usage/conventions.html [2] https://aider.chat/docs/git.html https://aider.chat/docs/git.html [3] https://aider.chat/docs/usage/lint-test.html https://aider.chat/docs/usage/lint-test.html