Mathematical Autopsy

Every AI decision dissected through mathematical proof. From ambiguous intent to deterministic execution.

Intent → Conversation → Calculus → Trace → Map → Code

What is a Mathematical Autopsy?

A Mathematical Autopsy is a framework for decomposing complex natural language instructions into a deterministic, inspectable, and replayable series of logical transformations.

Instead of treating AI as a black box, the Mathematical Autopsy builds a complete symbolic trace from human intent to executable code, proving why it works and how it was derived.

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Explainability

Every output grounded in an intermediate symbolic step.

Testability

Each transformation validated independently.

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Replayability

Any result regenerated identically from original intent.

The Autopsy Pipeline

1. intent.md

The original human vision or instruction in natural language.

2. conversation.md

Simulated dialog exploring edge cases and clarifications.

3. calculus.md

Formal symbolic logic describing the mathematical solution.

4. calculus_trace.md

Validation trace proving behavior correctness.

5. calculus_map.md

Mapping of mathematical symbols to code artifacts.

6. code.py

Final executable code derived from proven mathematics.

Perfect For

Regulated Industries

Complete audit trail from requirement to implementation. Every decision traceable and provable.

Critical Systems

Mathematical proof before deployment. No ambiguity in safety-critical implementations.

AI Engineering

Transform complex AI workflows into deterministic pipelines with guaranteed behavior.

Prove Your AI's Reasoning

Mathematical Autopsy transforms black-box AI into transparent, provable systems. Every decision traced, every output verified.