Five-Stage Complex Problem Solving Framework

Problem Context

Complex issues are often shaped by surface symptoms, inherited assumptions, and cross-team ambiguity. Jumping straight to recommendations can miss root causes, hidden feedback loops, or low-leverage actions. This skill organizes 12 thinking models into a five-stage closed loop, helping the agent define the problem, analyze system behavior, rank options, design execution, and review outcomes before giving advice.

How It Works

The workflow uses explicit inputs, outputs, and confirmation gates to avoid vague one-pass answers.

• Problem definition: uses SCQA, 5Why, Socratic questioning, and first-principles analysis to separate assumptions, identify root causes, and expose information gaps.
• System analysis: applies systems thinking, causal loops, and force-field analysis to surface second-order effects, risks, and leverage points.
• Prioritization: uses Pareto logic, an impact-effort matrix, and Occam's razor to focus on high-leverage items and calibrate the capability boundary.
• Execution design: combines analogy transfer, thought experiments, and structured execution plans to turn ideas into verifiable steps.
• Feedback iteration: uses metacognitive review and system-loop monitoring to detect drift, test assumptions, and retain reusable rules.

It fits operations diagnosis, process optimization, strategy decomposition, and complex decision support. If the boundary is unclear, data is thin, or only a rapid check is needed, it can start from one stage instead of forcing the full process.