So it answers with confidence — to a question you never asked.
See where this is costing you →A planner asks the enterprise AI a routine question. The model has the data. What it does not have is your rule for weighing it.
No one catches it. It was confident. It cited its sources. The decision moves forward on an answer that is mathematically correct and operationally wrong.
The reflex is a better prompt. But a prompt is not a control — it is a request. It has no version, no owner, no audit trail, and no guarantee that the same input produces the same output tomorrow.
That is not a strategy. That is hope.
Retrieval solved the data problem. It never touched the reasoning problem. Your rules are still being interpreted, not executed.
Logic is not content.
Logic is code.
Content can be retrieved. Logic must be executed. Your pricing rules, your risk weightings, your escalation thresholds, your compliance boundaries — these are not documents for a model to read and interpret. They are functions for a model to run.
Stop giving AI reading assignments. Start giving it runtime instructions.
ALP defines your organization's logic separately from its data. It versions authority, enforces territory, and removes inference from decisions that were never meant to be inferred.
The artifact it produces is a Canonical Logic Registry — a single, versioned, executable source of truth for how your organization actually decides. Not a document about your rules. Your rules, running.
ALP · the methodology | Canonical Logic Registry · the artifact
Built for organizations where a wrong answer is expensive — regulated operations, complex supply chains, financial and clinical and legal decisioning, high-stakes B2B.
If your AI is writing marketing copy, you do not need this.
Name the place it happens. That is where a Registry begins.