From Demo to Production: The 6-Step Checklist for Shipping Multi-Agent Systems Safely

List hard rules, soft goals, authority limits, data restrictions, timing, capacity, evidence, and escalation. Give every hard rule a source, owner, affected decision, and verifier.

Separate rules from prompt wording. The rule survives when prompts and models change. Use the reliability pillars to check that enforcement has evidence and monitoring.

Map roles, tools, state, handoffs, and outcomes for normal workflows first. Add boundaries, missing information, delayed tools, long sessions, and high-impact decisions.

Track coverage by decision branch and risk, not raw scenario count. Assign stable IDs and version scenarios with the rules they exercise.

Check whether all hard constraints can hold together before running agents. Extract conflicting rules when no valid assignment exists.

Store a known feasible reference state. It becomes ground truth for evaluating whether the actual plan stayed inside the allowed region.

When a run misses an expectation, start from the violated constraint and trace its decision inputs backward. Separate symptoms, faults, mechanisms, and root causes.

Validate proposed fixes with single-change counterfactual replay. Keep the successful replay as a regression case rather than closing the incident with a prompt edit.

Establish reviewed baselines for critical constraints, quality, escalation, cost, latency, and stability. Set absolute minimums plus relative regression limits.

Define owners, alert routes, sample requirements, and override policy before launch. A threshold without a response procedure is only a dashboard number.

Run fast deterministic checks, contracts, targeted scenarios, and broader risk-based suites in CI. Preserve immutable artifacts for every release decision.

Block on critical rule violations and material regressions. Require documented human approval for authority or policy changes. The business case in the evaluation ROI guide connects these controls to avoided remediation and downtime.

The system is ready when the team can explain what was tested, what passed, what remains uncertain, who approved, and what production monitoring will watch.

Use the multi-agent evaluation guide as the acceptance model for the checklist. The trajectory, not just the final response, must satisfy release evidence.

Add ownership beside every checklist item. Name the person who can accept the evidence, the artifact they review, and the condition that returns the item to incomplete.

Rehearse the checklist with one representative workflow before scaling it across the portfolio. This exposes missing trace fields, unclear authority, and impractical gates while the scope is small.

Store the completed checklist with the release artifact. A live document that changes after approval cannot prove what reviewers saw when they authorized deployment.

Define rollback and containment before the gate opens. Include in-flight tasks, external side effects, user communication, and state compatibility, not only application deployment.

Repeat the checklist after material model, policy, tool, data, or authority changes. Production readiness expires when its supporting assumptions change.

Hold a short evidence review before launch. Walk one scenario from initial state through constraints, trace, verdict, gate, and monitoring. Missing connections become visible when the artifacts are reviewed as one chain.

Track incomplete items as owned risks with deadlines. Do not mark them complete because another control exists unless that control demonstrably covers the same consequence.

A named release owner confirms the six artifacts refer to the same workflow and version before approval.