The pipeline was built entirely by Claude Opus as a coding agent, and the results were reviewed by Claude Sonnet. Both AI models had to subject their output to a three-step iterative self-correction process after each work batch. My job was to read every code comparison, verify that the ChEMBL fallback logic actually covered the edge cases it claimed to, and figure out at 1 a.m. why the Stripe webhook had been silently returning a 400 status for three hours without me noticing. It’s a truly unusual workflow. I spent most of my time asking Claude Sonnet whether what the Coding Agent had built actually worked the way I had planned—and the answer is surprisingly often: “Not quite.” If there are errors in the methodology, I’d like to know about them. The METHODOLOGY.md was created precisely for this purpose and is publicly accessible.