The Owl, The Scientific Method, and Claude Code: A Debugging Story (vsevolod.net)

A developer trying to upgrade a dependency that repeatedly broke nested-transaction test isolation bisected the failure to a single 1,595-line rewrite commit (helpfully titled "draw the rest of the owl"). They used Claude Code to automate tests against the good and bad commits, but the model started chasing bad ideas until the author forced a scientific method: record goals, all hypotheses, and supporting/conflicting evidence in a wip.md and run minimal experiments to falsify them. That structured approach produced five hypotheses; iterative tests and Method Resolution Order (MRO) analysis revealed the actual bug: multiple inheritance and a conditionally-created wrapper class unintentionally overrode a method, changing behavior only under certain parameter flows. The pragmatic fix was a short test-only helper that configures the problematic path, bypassing the OOP indirection. For the AI/ML community this is a clear workflow lesson for LLM-assisted debugging: use bisecting to isolate commits, force the model to enumerate explicit hypotheses and evidence, and run minimal falsifying experiments rather than letting the LLM bulldoze toward a single favored solution. LLMs can speed triage but are prone to fixation and hallucination; treat them as hypothesis generators and automatable test-runners, not final arbiters. Practically, be ready to apply small test-scoped shims or configuration fixes when complex OOP/MRO interactions make deep refactors costly.