Operator Intent Mapping™.
The definitive protocol for aligning Large Language Model execution with professional human persona and authority. This framework eliminates the "Intent Gap" in enterprise AI.
Persona Extraction
Identifying the professional identity and technical authority of the operator to align system tone.
Intent Decomposition
Breaking down unstructured human goals into discrete, actionable logic nodes.
Structural Alignment
Mapping the extracted intent to a specific Execution Chain pattern (EC-01 to EC-04).
Fidelity Verification
Automated audit of the AI output against the original human intent schema.
Technical Moat Analysis
The OIM Protocol creates a "Technical Moat" by encoding your unique professional reasoning into the system's logic loop. AI-generated assets still require subject-matter review, factual checks and clear disclosure.
Persona Integrity
System Security Layer
"Intent Mapping is the difference between a tool that 'chats' and a tool that 'executes' on your behalf."
Internal reference · Illustrative example
Translate an ambiguous request into a checkable contract
Consider “make our weekly report better.” Ask which reader uses it, what decision it supports, which source is authoritative, and what freshness is acceptable. A concrete contract could require revenue by region, a visible reporting period, the source refresh timestamp, and an explicit warning when data is incomplete.
Verification checklist
- Restate the decision the report should support.
- Record source permissions and unresolved definitions.
- Confirm the expected output with the requester.
- Check a sample output against every agreed requirement.
A persona is writing context, not evidence of professional competence or a permission grant. When requirements conflict, request a decision instead of letting the model silently choose. Keep the agreed contract next to the implementation so future changes remain reviewable.
Explain decisions using an evidence ledger