# Triple-Loop Debrief Review > Learning to learn from mistakes is a meta-skill, not an emergent nicety of > good process. Every debrief answers three questions, not one. ## The Three Loops 1. **Fix the mistake** (single-loop) — a validator FAILs a PR; the seat iterates; re-validation passes. Routine by design. 2. **Fix the system that produced it** (double-loop) — casualties become `candidate:` lines, which become policy; the debrief legislates so the class of mistake dies, not the instance. 3. **Fix how the fixing works** (triple-loop, the meta-skill) — did the learning machinery itself perform? What would have caught this sooner, cheaper, or without escalating to the maintainer? ## The Standing Question A debrief that only answers loop 1 is a log, not learning. Every debrief should name, even briefly: *what did the learning machinery itself do this session, and did it work?* ## Relationship to the Trust Kernel This is not a new value — it is `canon/values/trust-kernel` ("Trust Is Built by Managing Expectations") gaining a standing instrument. Declared expectations are promises with a shape; triple-loop review is the audit that keeps the promise about the *learning process itself* honest, not just the promise about any single outcome. ## Failure Mode Without This Triple-loop insight only surfaces when a human happens to notice it (e.g., a bridge-fix vs. architecture-fix distinction). The class of catch does not scale past the attention of whoever is watching that day.