[mgaudin]

Author here. This is the first part of a series based on our experiences at MadKudu, where we've shifted to treating AI agents as full-time developers, not just assistants.

We found that traditional development practices break down completely under this model. I've distilled our learnings into 11 principles that have made AI-native development practical and significantly boosted our team's productivity (e.g., by focusing on mono-repos, strict typing, and redefining the engineer's role towards documentation and architecture).

Happy to discuss these principles and answer any questions.