five-whys

Standardized Claude Code bootstrap — drop-in .claude/ tree with a 19-agent adversarial review team, Ralph Loop, dev-flow skills, and an init script. Agnostic, project-ready.

AI Agent Root Cause Analysis Protocol — A systematic five-question methodology adapted from Toyota's 5 Whys for diagnosing failures in AI agent systems. Battle-tested over 60+ production incidents.

Multi-agent system preventing solution-jumping in LLM-assisted architecture decisions through Five Whys requirements elicitation and deterministic evaluation. 100% accuracy, $0.01/session. Accompanies IEEE Software 2025 paper.

Correction-of-Errors retrospective plugin for self-improving Claude after medium-to-big sessions

Hose — challenge ta problématique avec la méthode des 5 pourquoi

WSQ - Generative AI for Problem Solving (TGS-2023036653) — 2-day SkillsFuture-funded courseware: 160-slide deck, Lesson Plan, Learner Guide and 10 real-life case-study activities with GenAI prompts and problem-solving ed-tools.

Taiichi Ohno's Five Whys run in both directions: backward from a failure to a systemic root cause, and forward from a claim to the intermediate steps required to reach it.

Six Sigma Green Belt project using the DMAIC methodology to reduce unnecessary technician dispatches, improve remote resolution effectiveness and increase first-call resolution through data-driven process improvement.

Six Sigma Yellow Belt project applying the DMAIC methodology to optimize customer interaction handling time by eliminating process inefficiencies, standardizing workflows and improving operational efficiency.