Your codebase is NOT ready for AI (here's how to fix it)

Most codebases are poorly structured for AI coding tools because they consist of many small, shallow, interconnected modules that are hard to navigate without prior context. AI agents lack memory and treat every session as a fresh start, so they struggle with tangled dependency graphs. The solution is to adopt 'deep modules' — large chunks of functionality behind simple, well-documented interfaces — organized clearly in the file system. This approach enables progressive disclosure of complexity, reduces cognitive burnout, and gives AI a clear map to navigate. Tests are critical to lock down module behavior so AI changes can be verified quickly. These are established software engineering principles that matter even more in the AI-assisted development era.