AI-FIRST WORKFLOW SHIPPING CHECKLIST (2026)

1) PICK THE RIGHT WORKFLOW
- Name the job: “Resolve tier-1 support tickets,” “Code invoices to GL,” “Draft and send renewal follow-ups,” etc.
- Define the outcome in one sentence and one metric (e.g., “Reduce median handle time by 25% in 30 days”).
- Confirm reversibility: list which actions are safe to auto-run vs must stay draft-only.

2) DEFINE ACTION SCOPES AND RISK TIERS
- Tier 0 (Read-only): summarize, classify, extract fields.
- Tier 1 (Draft): generate email/ticket/PR draft; user clicks send/apply.
- Tier 2 (Low-risk act): actions that are reversible (tag, assign, create task).
- Tier 3 (High-risk act): money movement, customer comms at scale, permission changes, production changes.
- Write approval rules: e.g., Tier 3 always requires human approval; Tier 2 requires approval above a threshold.

3) TOOL CONTRACTS (NON-NEGOTIABLE)
- Every tool has a strict schema (required fields, enums, min/max values).
- Add idempotency keys for every mutating tool call.
- Add explicit deny rules (e.g., “cannot refund chargeback accounts”).
- Store tool inputs/outputs in a transcript linked to the business record (ticket/invoice/deal).

4) RETRIEVAL + PERMISSIONS
- Choose hybrid retrieval where possible (keyword + vector) for precision.
- Enforce document-level permissions BEFORE the model sees content.
- Add freshness controls (policy docs expire; stale content is a hidden failure mode).
- Require citations for any user-visible claim or policy-based decision.

5) EVALS YOU CAN RUN WEEKLY
- Build a gold set: 200–1,000 real tasks (anonymized) with expected outputs.
- Measure: field accuracy, action correctness, refusal correctness, and correction rate.
- Track regressions per prompt/model change and block releases that exceed thresholds.

6) COST AND LATENCY BUDGETS
- Set budgets per task (tokens, tool calls, retries).
- Alert on P95 tokens per task > 3x P50.
- Cache repeated retrieval and short-circuit easy cases with smaller models.
- Add stop conditions to prevent loops (max steps, max retries, max tool calls).

7) RELEASE DISCIPLINE
- Feature flag every “act” capability; default new customers to draft mode.
- Canary deployments (1% traffic) for prompt/model changes.
- Maintain a model/prompt change log tied to feature versions.
- Add a global kill switch for action mode.

8) TRUST UX
- Show “What happened” with: inputs, evidence/citations, and actions taken.
- Provide undo/rollback where possible (and make it easy).
- Capture user feedback at the point of correction (“what was wrong?”).

9) OPERATIONS
- Define incident severity for AI failures (wrong action, data exposure, mass email, etc.).
- Run postmortems with transcript evidence.
- Maintain a queue for human review and measure review SLA.

10) PRICING + PACKAGING
- Attribute cost by customer, feature, and workflow step.
- Consider hybrid pricing: subscription + usage-based credits aligned to outcomes.
- Put guardrails in the plan: caps, overage pricing, or throttles to protect margin.

If you can’t (a) constrain tools, (b) permission retrieval, (c) run evals, and (d) explain actions in-product, you’re not ready for autonomous workflows—ship drafts first, instrument everything, then graduate to “act” where reversibility and trust are strong.