Use Trust and Smart Tuning

Use these views to decide whether automation quality is improving enough to justify broader scope.

Fast Path

Look for consistency across measured outcomes, shadow-vs-manual agreement, and safety events. Increase automation only when the signals line up, not when one chart happens to look good.

How To Use This

Trust is a pattern question. You are looking for evidence that:

1. the system reaches similar conclusions to your reviewers
2. the outcomes are not degrading when it acts
3. safety interventions are understandable and not constantly firing

Smart Tuning matters only after those basics are stable. If the underlying behavior is not trustworthy, calibrated thresholds just make the wrong behavior more precise.

How To Decide

Increase automation when trust signals are stable, reversions are low, and recent outcomes support the current logic.

Hold your current setting when the system is mostly aligned but you still need more measured outcomes.

Pull back when trust signals are noisy, shadow disagreement is high, or circuit-breaker events keep clustering around the same patterns.

FAQ

Is Smart Tuning required before live automation?

No. It is a maturity tool, not a prerequisite for basic automation.

What is the biggest mistake teams make here?

Treating one recent good run as proof that automation is ready for more scope.

Next Steps

Go back to Turn On Auto-Apply if you need to change automation scope now, or use Advance Through Autonomy to decide what the next maturity level should look like.