Pilot-to-Production Decision Loop

By Juan Beltrán — personal website on AI and digital growth for complex B2B industries.

Is this AI pilot ready for production, or should we redesign or stop it? Use this before extending a pilot, buying more licenses, asking for budget, or celebrating a demo as if it were business value. Pilot-to-Production Decision Loop Task: Is this AI pilot ready for production, or should we redesign or stop it? Context: [Paste your notes, excerpts, draft, meeting transcript, CRM fields, proposal text, public research, or examples here.] Context I should provide: - Pilot objective - User group - Measured usage - Measured outcome - Failure logs - Security review - Production cost estimate Useful setup: Paste the pilot objective, user group, measured usage, measured outcome, failure examples, risks, costs, and open questions. Why this matters: Use this before extending a pilot, buying more licenses, asking for budget, or celebrating a demo as if it were business value. Business problem: Pilots get celebrated for demos while production readiness, operating ownership, and value capture remain unresolved. Instructions: Act as an AI product governance board. Evaluate this pilot for production readiness. Separate demo success from workflow success, list missing evidence, estimate operating risk, and recommend scale, redesign, hold, or stop. Finish with a one-page decision memo for the sponsor. Workflow: 1. Restate the original bet: Capture the business problem, baseline, promised outcome, and user group. 2. Separate demo success from workflow success: Compare demo quality with usage, completion, error, and handoff data. 3. Price production honestly: Include integrations, monitoring, access control, support, training, and change cost. 4. Run the risk gate: Check data exposure, model failure modes, compliance, auditability, and human override. 5. Make the decision: Choose scale, redesign, hold, or stop and write the exact evidence threshold for the next gate. Quality bar: - Use only the context in this chat. - If important information is missing, ask for the minimum missing context before giving a final recommendation. - Separate facts from assumptions. - Do not invent customer facts, benchmarks, financial numbers, policy approvals, or system access. - Keep the answer useful for AI Product Owner. Output: A sponsor-ready decision memo: scale, redesign, hold, or stop. - BLUF recommendation or draft. - Evidence from my context. - Assumptions and missing information. - Risks, objections, or failure modes. - Recommended next action, owner, and stop condition. Evidence checklist: - Baseline metric - Post-pilot metric - Active usage - Failure examples - Risk review - Support model - Production cost Stopping condition: Stop when the pilot has a clear decision and nobody is allowed to continue spending under the word experiment.

Canonical URL: https://juanbeltran.ch/operating-loops/pilot-to-production-decision-loop