fpf-problem-solving

First principles thinking decomposes complex system architecture problems by routing your intent to the correct specification section, then loading only the narrowest relevant subsection for context-driven, evidence-anchored synthesis. This prevents anchoring on initial ideas and systematically resolves gaps.

Evaluating alternatives under uncertainty requires a reasoning framework that maps your intent to evaluate, loads targeted evidence subsections, and synthesizes cross-section data. This approach resolves gaps and conflicts while avoiding the pitfalls of loading entire documents into context.

Agentic RAG for decision making navigates section indexes and loads only the narrowest relevant subsection into context without external embeddings. The agent uses a thinking-verb router to map intent, retrieves targeted evidence, and synthesizes outputs in plain language for high-stakes choices.

Yes, first principles problem solving supports planning tool and tool-use sequencing under budget and trust constraints. It evaluates alternatives, decomposes cross-domain problems, and resolves conflicts by retrieving only the necessary specification subsections for evidence-driven planning.

Use first principles reasoning when architecting systems, evaluating alternatives under uncertainty, or resolving conflicts where standard decision making might anchor on the first idea. It systematically decomposes problems and synthesizes evidence from targeted subsections rather than relying on broad context loading.