AGENTIC AI LAUNCH READINESS CHECKLIST (2026)

Use this checklist to move from a promising prototype to a production-grade agent that can safely execute workflows.

1) WORKFLOW DEFINITION (SCOPE)
- Define ONE workflow with a hard boundary (start event → end state).
- List systems touched (example: Zendesk, Salesforce, Stripe) and whether access is read or write.
- Define success in system terms: fields updated, messages sent, tickets closed, credits issued, records created.
- Identify the blast radius if wrong (how many users/records can be impacted per run).

2) AUTONOMY MODEL (GRADED AUTONOMY)
- Set autonomy levels:
 L0 Draft only (no tools)
 L1 Read-only tools (search, fetch status)
 L2 Safe writes (tags, drafts, PRs, non-financial updates)
 L3 High-impact writes (money movement, irreversible actions)
- For each tool/action, decide: allowed or blocked + approval required (Y/N).
- Default to least privilege: read-only until the workflow earns write access.

3) PERMISSIONS & GOVERNANCE
- Implement role-based access (user/admin) and per-connector scopes.
- Add cost controls: budgets, alerts, throttles, and model tier restrictions per workflow.
- Set data retention: logs and traces (example windows like 30/90 days) and deletion support.
- Handle PII: redact logs; define clear memory rules (what is stored, where, and for how long).

4) PROOFS, AUDITABILITY, AND ROLLBACK
- Every run gets a trace ID and a structured run record (prompt version, tool calls, outputs).
- Proof UI: show sources/evidence, actions taken, and a diff of record changes.
- Set a rollback coverage target: most write actions should be reversible.
- Incident workflow: how to pause the agent, revert changes, and notify affected users.

5) EVALUATION & LAUNCH GATES
- Build an offline eval set from real cases (enough to cover your core flows).
- Track trust metrics:
 - Task success rate (end state correct)
 - Intervention rate (runs needing human edits/retries)
 - Time-to-complete (median + tail latency)
 - Blast radius per failure (records/users impacted)
- Run shadow mode before enabling any writes.
- Don’t unlock higher autonomy without a measured improvement trend and a rollback plan.

6) OPERATIONAL READINESS
- Version prompts, policies, and tool schemas in git; use staged rollouts.
- Name an on-call owner, escalation path, and incident template.
- Monitor connectors for API errors, rate limits, and schema changes.
- Create a kill switch to disable writes immediately.

7) PRICING & PACKAGING
- Choose the economic unit: per ticket, per invoice, per lead, per batch of tasks.
- Bundle governance (SSO, audit logs, admin policies) into an enterprise tier.
- Don’t punish efficiency: align price with value delivered, not raw action count.

FINAL GO/NO-GO QUESTIONS
- If the agent is wrong once, can we prove what happened and undo it?
- Can admins restrict autonomy by workflow, role, and connector?
- Do we have clear gates that decide when to unlock higher autonomy?
- Can customers predict and cap spend?

If you can answer “yes” to all four, you’re ready to ship an agent people can delegate to.