Chaos Engineering in the Age of AI: Surfacing Hidden Complexity

“The complexity of things — the things within things — just seems to be endless. I mean nothing is easy, nothing is simple.” — Alice Munro

The rise of AI in software development presents a fascinating paradox. While AI tools make it easier than ever to generate complex systems rapidly, they also make it harder to understand how these systems actually work.

This challenge isn’t entirely new — forty years ago, Lisanne Bainbridge warned us about it in her paper “Ironies of Automation.” She argued that the more we automate systems, the more we need human expertise to handle their inevitable failures. AI is now accelerating this irony to unprecedented levels.

Consider this recent case where a developer built a Python project entirely using AI tools. The project quickly grew to over 30 files, but as complexity increased, things started to break down. The AI couldn’t effectively optimize the code or fix bugs because it had lost track of the system’s underlying structure.