AGENTIC WORKFLOW LAUNCH CHECKLIST (2026 EDITION)

Use this to move an AI workflow from prototype to production autonomy with measurable quality, controlled spend, and clear governance.

1) DEFINE THE WORKFLOW CONTRACT
- Name the workflow and assign a business owner (example: “Refund approvals — Support Ops”).
- Define the outcome in business terms (example: “Resolve refund requests within the support SLA”).
- Set explicit thresholds: max amounts, recipient limits, allowed systems, and clear escalation triggers.
- Write down what “incorrect” means (financial loss, compliance exposure, customer harm, data exposure).

2) DESIGN TOOLING + PERMISSIONS
- Split tools into READ vs WRITE operations.
- Implement least-privilege access by role/workspace; document who can enable auto-execution.
- Add idempotency keys for every write tool so retries are safe.
- Build an undo path for every write (revert diffs, cancel/void actions, remove created artifacts).

3) INSTRUMENTATION (REQUIRED FIELDS)
Log per run: run_id, workflow name, model/version, tokens in/out, latency, tool calls, retrieval docs, policy blocks, human-review flag, outcome label, estimated value ($) and measured cost ($).

4) EVALUATION PLAN
- Build a golden set (enough cases to cover normal traffic, edge cases, and known failure modes).
- Define three core metrics:
 a) Task success rate (end-to-end correctness)
 b) Cost per completed task (model + retrieval + tools + human review)
 c) Time to resolution (including retries and escalations)
- Add production sampling and review (fixed weekly volume or a fixed percentage of runs).
- Set an error budget in business terms (what failure types are acceptable, and what is not).

5) COST CONTROLS
- Enforce per-run token ceilings and per-workflow spend limits.
- Implement model routing (small/fast for triage and extraction; stronger models for hard or high-stakes cases).
- Add caching for retrieval and deterministic tool outputs; cache safe model outputs like templates and policy explanations.
- Define “budget request” behavior when limits are exceeded (reason + escalation path).

6) ROLLOUT STAGES
- Stage 1 (Draft): agent proposes; a human executes.
- Stage 2 (Assisted): agent executes low-risk writes with confirmation.
- Stage 3 (Auto, bounded): agent auto-executes within caps; strict policies; fast undo.
- Stage 4 (Auto, adaptive): continuous evals and drift alerts; kill switch always available.

7) GOVERNANCE + SECURITY
- Store prompts/tool traces securely with a retention policy.
- Document data boundaries (what leaves your environment, what is redacted, what is encrypted).
- Implement a kill switch that disables auto-execution immediately while keeping draft mode.
- Prepare procurement-ready answers: audit logs, role matrix, incident response plan, versioning and rollback strategy.

8) GO/NO-GO GATE
Enable autonomy only if: the golden set meets thresholds, production sampling is live, undo works, spend limits are enforced, and a business owner signs off on the error budget.