AI-rule safety

LLMs are great at drafting JSON business rules — and that's exactly the risk. A plausible-looking rule can still encode the wrong field, the wrong threshold, or the wrong action. Neuron-JS exists so AI-drafted rules become safe to run: schema-validated, constrained to a developer-owned vocabulary, reviewable like code, and explainable after the fact.

AI drafts. Neuron-JS verifies.

1. AI can draft rules

A plausible JSON rule can still encode the wrong assumption, field, or action — it is not production-ready on its own.

2. Validate before runtime

Schema-first checks (validateScript) reject malformed scripts before they ever execute, and return the exact JSON path to fix.

3. Constrain what can run

A developer-owned registry defines the approved actions, conditions, parameters, and rules. Anything outside that vocabulary simply cannot execute — no arbitrary code.

4. Review like code

Generated rules are serializable data, so they go through the same governance as code: tests, owner approval, and rollback — never automatic AI approval.

5. Then execute deterministically

Synapse runs the approved rule path deterministically, and the explanation trace shows why the decision matched or failed — ready for audit, logs, or a support ticket.

In short

Validate → constrain → test → approve → execute → explain. Deterministic workflow logic with auditability is the guardrail that makes AI-assisted business rules safe to ship.