Lukewarm recommendations for improving AI agents' interactions with your projects

Over the last week I've been chatting with some folks who are looking at integrating AI more into their development work. I shared a couple of things that we've found have worked well for Renovate, as a codebase that takes a lot of human (and since mid-last year, AI) contributions. Although I've written about this a bit in my reflection on the last year, this naturally deserves its own blogumentation. Before we did anything to explicitly optimise the codebase for AI agents, we ended up finding that we'd - for the most part - receive fairly technically correct code, although it wouldn't necessarily fit in the areas that it was added for, or wouldn't completely fit our code style, but would handle a lot of file-directory architecture choices. We credit this down to the fact that we've structured our codebase in a predictable and - in my opinion, reasonable - structure, which has been optimised for the humans who are interacting with it. As well as this, we've also had documentation for…