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Machine-intelligence working framework

Pilot-to-Production Evidence Check

Use the check to distinguish a persuasive demonstration from a supportable production decision.

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Published Updated Reviewed By LongTermIntelligence.com

Direct answer

What evidence should an AI pilot have before production?

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A pilot should have a measurable baseline, representative work, controlled interfaces, explicit authority, tested failure and recovery behavior, predetermined acceptance thresholds, preserved run evidence, and named operating owners. The final output should be a go, conditional go, remediate, rebid, replace, or stop decision.

  • A demo is not production evidence.
  • Projected value is not realized value.
  • The delivery team should not be the only reviewer of its evidence.

Source basis: reviewed synthesis of the strategy corpus. Report-derived claims remain subject to the verification boundary in the source library.

Use this assessment when

A pilot has produced runs and a scale decision is due

This check is narrower than a general readiness assessment. It asks whether representative pilot evidence supports live operation, controlled side effects, acceptance thresholds, recovery, and named production ownership.

  • Use after a real pilot, not as a substitute for one.
  • Separate demonstrated results from projected value.
  • Require an explicit release disposition and unresolved-risk owner.

Local diagnostic

Check the pilot evidence

Score 0–4 for each statement. The result remains local to your browser.

Privacy: scoring happens locally in this browser. The theme does not submit or store responses.

Dimension 1

Outcome proof

Does the pilot prove a business outcome rather than a demonstration?

1. A baseline exists for time, cost, quality, risk, or service.
2. The pilot uses representative work and real operating constraints.
3. Benefits include human review, integration, model, and operating costs.

Dimension 2

System readiness

Is the workflow ready for bounded production execution?

4. Data and tool interfaces are controlled and supportable.
5. Identity, policy, state, memory, and authority are explicit.
6. Failure, retry, idempotency, compensation, and rollback are tested.

Dimension 3

Release evidence

Is there enough evidence for a go/no-go decision?

7. Acceptance thresholds and hard stops were established in advance.
8. Normal, edge, adversarial, and degraded scenarios were replayed.
9. The evidence pack can be reviewed independently of the delivery team.

Dimension 4

Operating ownership

Can the organization own the result after launch?

10. Business, technical, risk, and incident owners are named.
11. Monitoring, review cadence, change control, and cost attribution exist.
12. The next decision is go, conditional go, remediate, rebid, replace, or stop.

Answer all 12 questions to calculate a result.

Downloadable working files

Companion decision tools

CSV template

Agent Evaluation Scorecard

Record thresholds and release evidence.

Download CSV

CSV template

Production Agent Risk Register

Tie unresolved pilot gaps to owners and controls.

Download CSV

Templates are planning aids. They are not certifications, legal advice, security guarantees, or substitutes for client-specific validation.

Related intelligence

Continue through the knowledge system

Next decision

Make the scale decision explicit

Use the result to structure a decision memo rather than defaulting to another pilot extension.

Discuss the decisionEvaluate readiness

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