About
About the AI Failure Library
Glitchive exists because someone already made that mistake.
UPDATED
Why this exists
Practitioners encounter the same AI failures repeatedly, but the useful detail is scattered across postmortems, issue threads, incident records, and posts that can disappear from view. The AI Failure Library collects verified incidents in one searchable place so the next team can start from evidence instead of memory.
What a case file is
Each case file has two layers. The editorial layer is stable enough to cite: structured, sourced, and maintained by AFL Editorial, with corrections recorded visibly. The solutions layer welcomes better approaches until a case reaches its capacity of ten published solutions.
A case is never synthetic. Every published file rests on at least one real, citable source, and each case carries an immutable id in the AFL-0001 format.
What this is not
This is not a news site, a vendor scorecard, or a place for hypotheticals. Glitchive is built for incidents with enough public evidence to teach a reusable lesson about systems, incentives, process, or technical design.
Where it’s going
The library is adding a contribution route for case leads and proposed solutions, alongside a monthly newsletter. The contribution forms are open; the newsletter is not sending yet.