Human correction
A user or approver explicitly changes an output, action, field, or value.
Growth Loop / Governed Learning
NexusClaw turns human corrections, tool failures, knowledge gaps, and outcome variance from real work into reviewable improvement candidates, then routes them through evaluation, approval, versioned release, and rollback.
The learning inbox is a recommendation layer. It cannot silently change prompts, SOPs, guardrails, or model routing. Every production behavior change needs test evidence, a release owner, and a rollback path.

01 / Learning Signal Intake
The system extracts structured signals from real execution and retains source, risk, affected employee, and usage scope. Only explainable, traceable evidence enters clustering and candidate generation.
A user or approver explicitly changes an output, action, field, or value.
A call fails, access is denied, parameters are wrong, or the workflow misses its goal.
An answer lacks evidence, a step is missing, or an existing procedure drifts.
A real business outcome differs from expectation and needs review.
Hard boundary of the recommendation layer
The inbox collects, explains, and ranks. No signal can directly modify production employee behavior.
02 / Distillation & Asset Candidates
Similar signals are grouped into patterns, their impact and risk are assessed, and specific candidates are generated. Candidates are reviewable asset drafts, not hidden model memory.
Adjust instruction structure, boundaries, or output requirements.
Add or revise a standard operating procedure.
Add blocking, approval, or sensitive-action control.
Change model selection, fallback, or budget strategy.
Turn a failure or correction into a regression test.

03 / Evaluation & Release Gate
The test center turns real failures into evaluation cases and compares candidate behavior with the production baseline. Safety, access, quality, and outcome checks must pass before human approval.
Failures, corrections, and exceptions become repeatable tests.
Measure quality, unauthorized access, tool calls, and outcomes.
Validate sensitive actions, approval points, and exception fallback.
A release owner reviews evidence, scope, and rollback plan.

04 / Versioned Release & Rollback
After the gate, prompts, SOPs, guardrails, model routing, or eval suites publish as new versions. The system records who approved, when it took effect, which employees changed, and who owns rollback.
Asset version, diff, and impact scope are fixed.
Observe a controlled scope before full activation.
Configuration delivery and release ownership are recorded together.
Restore the last stable version without rebuilding settings manually.

The system records which audit event became a signal, what candidate it created, its risk, required approval, and whether it entered production.

Customer Evaluation Checklist
Trace a recommendation back to its execution, correction, tool call, or business outcome.
Verify it becomes a diffable prompt, SOP, guardrail, route, or eval version.
Fail an evaluation or remove approval and confirm production cannot change.
Inspect the release version, approver, affected employees, and rollback owner.
The growth loop does not scan audit tables and self-modify production. It cannot bypass asset owners or the release gate. It is an evidence-driven, human-gated, versioned, rollback-able governance pipeline.
We will show how it becomes a signal, improvement candidate, evaluation case, and release audit — without hiding behind a generic “gets smarter over time” claim.