fpf-problem-solving

name

fpf-problem-solving

description

First Principles Framework (FPF) — thinking amplifier. Use when user wants to think through a complex problem, architect a system, evaluate alternatives, decompose complexity, classify problems, define quality attributes, plan rigorously, decide under uncertainty, establish causality, reason about time and trends, describe architecture or structural views, check mathematical model fit, publish multi-view artifacts, refresh SoTA packs, trace provenance, or improve pattern quality. Also triggers on: FPF, bounded contexts, SoTA packs, assurance calculus, decision theory, causal reasoning, temporal reasoning, architecture description, quality gates, lexical debt, FPF Parts A-K. Not for simple task planning, general philosophy, or Agile unrelated to FPF. Use when this capability is needed.

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
• Transfer an insight across domains without losing precision or introducing category errors
• 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
• Refresh a SoTA pack, benchmark, or evidence trail when evidence decays or telemetry changes

How to navigate

The use cases above help decide WHETHER to invoke FPF. The router below decides WHERE to go once invoked.

Step 1 — Match the thinking need to a starting point

What you need to do	Start here
Decompose a complex whole into bounded parts	04 Kernel → A.1 Holons, A.1.1 Bounded Contexts, A.14 Mereology
Assign roles and responsibilities	04 Kernel → A.2 Roles, A.15 Role-Method-Work Alignment
Set boundaries on what statements mean	05 Signature Stack → classify as definitions, gates, duties, or evidence
Prevent category errors (role vs. function, method vs. work)	06 Constitutional Principles → A.7 Strict Distinction
Evaluate confidence in a claim or artifact — including formality, scope, and reliability of the underlying knowledge	07 Part B → B.3 Trust & Assurance; 08 Part C → C.2 KD-CAL / F-G-R scoring, C.2.2 Reliability, C.2.3 Formality
Compose parts into wholes preserving properties	07 Part B → B.1 Gamma algebra; 08 Part C → C.13 Compose-CAL, C.20 Discipline-CAL
Reason through a problem systematically	07 Part B → B.5 Reasoning Cycle, B.5.2 Abductive Loop
Generate alternatives / explore solution space	08 Part C → C.18 NQD Open-Ended Search, C.19 Explore-Exploit
Measure and compare options rigorously	06 A.V → A.17-A.19 Characteristics, CSLC & SelectorMechanism; 08 Part C → C.16 MM-CHR; 16 Part G → G.9 Parity / Benchmark Harness
Resolve conflicts across stakeholders or values	09 Part D → Ethics & Conflict
Unify vocabulary across teams or domains	13 F.I Context of Meaning → 14-15 UTS tables → 20 Lexical Debt
Document for multiple audiences or stabilize a publication unit	11 E-I Constitution → E.17 Multi-View Publication Kit, E.17.EFP Explanation Faithfulness, E.17.AUD PublicationUnit Stability
Sharpen expression — repair vague wording, surface ambiguity, restore precision of epistemic / measurement / architecture terms	11 E-I → E.10.ARCH Wording-Use Ontological Precision Restoration, E.17.EFP Explanation Faithfulness; 08 Part C → C.2.P Epistemic Precision Restoration, C.16.P Characteristic and Scale Precision Restoration, C.30.P Architecture and Structure Precision Restoration; 05 A.IV.A → A.6.H Wholeness Unpacking

For complex problems, follow paths across multiple sections — the router shows where to start, not where to stop.

Step 2 — Read the _index.md, then the sub-section

1. Open the _index.md of the target section folder — it lists all sub-sections with line counts and descriptions.
2. Read only the specific sub-section file you need.
3. Do NOT load entire sections. Pick the narrowest file that serves the user's question.

Step 3 — Apply in plain language

Use plain language for the user. Introduce FPF-internal names (U.Holon, Gamma, F-G-R) only when they add precision the user needs.

Step 4 — Compose findings across sections

When a problem draws from multiple sections:

1. State each pattern's contribution in one line (e.g., "Bounded Contexts gives us the parts; Trust Calculus scores our confidence in each").
2. If patterns from different sections appear to conflict, check for category errors via A.7 Strict Distinction — the conflict is usually a level confusion (role vs. function, method vs. work), not a real contradiction.
3. Synthesize in natural order: decomposition first (what are the parts?), then evaluation (how confident are we?), then resolution (what do we do about gaps?).
4. Do not just list FPF patterns — weave them into a coherent answer to the user's actual question.

Starter prompt (example — adapt to the user's actual role and need)

You have the FPF specification loaded. Help me structure my project / problem / programme. Use plain language for an engineer-manager. Propose: (1) bounded contexts / specialisations, (2) decision criteria, (3) key alternatives, (4) hand-offs, and (5) missing evidence or tests before commitment. Introduce internal FPF names only when they add precision.

Section INDEX

Structural reference. Each entry is a folder — read its _index.md first, then pick the sub-section.

#	Section	Sub	When to use
01	Title page	0	Identify: authorship, version date, top-level identity.
02	Table of Content	1	Navigate: locate a pattern, trace inter-section dependencies.
03	Preface	17	Onboard: reading paths by role, FPF philosophy, purpose and non-goals.
04	Part A — Kernel	19	Decompose and assign: holons, bounded contexts, roles, transformers, method/work separation.
05	A.IV.A — Signatures	22	Set boundaries: classify statements as definitions, gates, duties, or evidence.
06	A.V — Principles	33	Prevent confusion: category errors, measuring, comparing, evidence graphs, mechanism suite, flow constraints, gate profiles.
07	Part B — Reasoning	25	Compose and evaluate: structure and structural views (STRUCT-CAL), aggregation (Gamma), trust scores, emergence, reasoning cycles.

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Source: CodeAlive-AI/ai-driven-development — distributed by TomeVault.