How we AI-updated 1,138 Error-code Docs Pages
Twilio built a two‑phase pipeline that first scores each error‑code doc with a deterministic script, then feeds only low‑scoring pages to an LLM (gpt‑5.4) using a strict prompt. The model’s diff is applied via git, linted, and opened as a PR for a reviewer. In 12 weeks they updated 1,138 pages (≈34.6 s/page) with a human reviewing every change, cutting manual effort from an estimated 18 k hours a…

