Agentic AI Ops Readiness Checklist (2026)

Use this checklist before you scale any agentic workflow beyond a pilot. Goal: bound risk, cost, and failure modes while keeping velocity high.

1) Workflow definition (clarity)
- Name the workflow and owner (Product + Eng + Ops).
- Define “done” in measurable terms: success criteria, allowed partial completion, and escalation conditions.
- Identify system-of-record targets (e.g., Salesforce, ServiceNow, NetSuite) and whether writes are allowed.
- Establish baseline metrics without the agent (median handling time, error rate, labor cost).

2) Tool contracts (safety + correctness)
- Every tool call has a strict schema (typed inputs/outputs, required fields, enums).
- Implement idempotency keys for any write action (refunds, updates, ticket closures).
- Add rate-limit and timeout handling with bounded retries.
- Maintain a tool “allowlist” for the workflow; no open-ended tool discovery in production.

3) Verification (quality gates)
- Deterministic validators exist (schema validation, unit tests, policy checks, reconciliation checks).
- Model-based verifier is separate from planner (to reduce correlated failures).
- Define confidence thresholds and what happens below threshold (ask human, draft-only, or open a ticket).
- Log verifier outcomes as labels to build an eval set.

4) Governance (permissions + audit)
- Agent identity is explicit (service account/principal) and uses least privilege scopes.
- Approval gates defined for high-risk actions (e.g., refunds over $50, account deletions, vendor creation).
- Sensitive data redaction rules applied before model calls (PII/PHI/secrets).
- Audit bundle per run: actor identity, permissions, approvals, tool traces, model/version, timestamps.

5) Observability (operate like a service)
- End-to-end trace ID across model calls, tools, queues, and retries.
- Capture step latency, error codes, retry counts, and completion times (P50/P95).
- Record the plan and final actions in machine-readable form.
- Runbooks exist for top failure classes (tool outage, bad schema, low confidence loops).

6) Cost controls (predictable spend)
- Per-task budget set: max model calls, max steps, and max spend in USD.
- Model routing policy defined (cheap vs. high-reasoning; when to escalate).
- Caching strategy in place (artifacts like summaries/entities; retrieval caches where safe).
- Weekly cost report ties spend to business outcomes (cost per completion, cost per saved hour).

7) Rollout plan (safe scaling)
- Start in draft-only mode; then execute-with-approval; then automatic under thresholds.
- Canary deployment: 1–5% of traffic with monitoring before ramp.
- Backout plan: feature flag or kill switch that immediately stops writes.
- Postmortems for incidents; recurring failures treated as bugs with assigned owners.

Definition of “Scale-Ready”
- Verified success rate ≥99% on sampled runs.
- Duplicate/incorrect write actions <0.1% per 10,000 runs.
- P95 completion time stable for 4 consecutive weeks.
- Cost per completion within ±10% of target for 4 consecutive weeks.
- Audit bundle can be generated on demand in <5 minutes for any run.

If you cannot check these boxes, the right move is not “better prompts.” It’s tighter tool contracts, stronger verification, and clearer governance.