fpf-problem-solving

First Principles Framework (FPF)

An "Operating System for Thought" — a transdisciplinary architecture for reasoning, written in human- and machine-readable pseudo-code. FPF turns raw intelligence (human or machine) into organisationally usable reasoning: explicit bounded contexts, auditable artefacts, multi-view descriptions, and disciplined hand-offs between specialised actors.

Use cases

Use FPF whenever you need to think more rigorously than the situation's default.

• Decompose a messy, cross-domain problem into parts that can be reasoned about independently
• Make a high-stakes decision with incomplete evidence — and know what evidence is still missing
• Get a mixed team to reason together without vocabulary collisions or hidden assumptions
• Audit whether a conclusion is well-founded or just plausible
• Transform or transfer an insight without losing its subject, precision, or stated limitations
• Structure a proposal that must survive scrutiny from multiple expert perspectives
• Generate alternatives systematically instead of anchoring on the first idea
• Define what "better" means before comparing options
• Classify what kind of problem you're facing before searching for solutions
• Plan how an AI agent should select and sequence its tools under budget and trust constraints
• Make a decision under uncertainty — identify options, weigh evidence, and commit with an auditable rationale
• Establish whether X causes Y — or just correlates — and determine what intervention would work
• Publish a stable multi-view artifact without changing the source semantics
• Assemble or check a public framework publication form while preserving product-specific bodies and references
• Develop a holder system's capability for a named Work family and verify transfer in representative Work
• Synthesize source ontologies for one bounded authoring decision without flattening their local meanings
• Refresh a SoTA pack, benchmark, or evidence trail when evidence decays or telemetry changes
• Synthesize architecture candidates, compare structural options, or repair modularity/reuse claims
• Detect an ontic candidate, decide its first-use disposition, and govern whether a new concept or U-kind should be introduced instead of just renamed
• Identify the exact system that acts or is intended to change, then trace a lost path from outside use to architecture, production, and recursive builders
• Discover other systems that may bear relevant consequences before a decision closes
• Recover a reusable method cautiously from several performances, logs, or observations without treating the evidence as the method itself
• Choose the next action during ongoing work when current facts, authority, and stop conditions matter
• Recover the actual performer/support configuration for Work and test what survives interruption, handoff, delay, or reconfiguration
• Compare what a finite addition, replacement, or intervention contributes relative to the current configuration
• Clarify what a claim about human, machine, organizational, or cultural “learning” actually says changed
• Apply one selected FPF pattern to a current question and stop at the first useful result