Blame Isn’t a Bug: Turning Agent ‘Whodunits’ into Fixable Systems
TL;DR As AI agents spread into real workflows, incidents are inevitable—from prompt-injected data leaks to misfired tool actions. A recent framework by Ezell, Roberts‑Gaal, and Chan offers a clean way to reason about why failures happen and what evidence you need to prove it. The trick is to stop treating incidents as one-off mysteries and start running a disciplined, forensic pipeline: capture the right artifacts, map causes across system, context, and cognition, then ship targeted fixes. ...