Agentic Workflow Readiness Checklist (2026) Use this checklist to move from “AI feature” to a production-grade agent workflow in 30–60 days. 1) Workflow definition (Product) - Name the workflow and define “done” in one sentence (e.g., “Refund request is approved/denied and customer notified”). - Quantify baseline: current cycle time, error rate, and labor cost per task. - Choose a single primary KPI (e.g., +20% throughput, -25% handle time, -30% backlog). - Identify failure tolerance: what’s acceptable (typos) vs unacceptable (sending money to wrong account). 2) Scope and tool surface area (Engineering) - Limit v1 to 3–5 tools with stable, versioned interfaces. - Ensure each tool call is idempotent (retries don’t double-execute). - Add blast-radius limits (caps, quotas, rate limits) for any external side effects. - Define a “dry run” mode that produces a plan and preview without executing. 3) Context and data controls (Security + Data) - Create a context contract: exactly what data the agent can access and why. - Implement PII redaction and minimum-necessary context (avoid dumping whole records). - Decide routing rules for sensitive tasks (private endpoints, region controls). - Set retention defaults and allow customer-configurable retention if selling enterprise. 4) Guardrails and approvals (Product + Security) - Require structured outputs (schema validation) for every action proposal. - Add approval gates for high-risk steps (refunds, access provisioning, deletions). - Create a policy layer: allow/deny rules, thresholds, and escalation paths. - Provide a clean human handoff: the reviewer sees context, plan, and evidence. 5) Evaluation and regression testing (Engineering + PM) - Build a golden set: 200–1,000 representative tasks (redacted) with pass/fail rubrics. - Track metrics: workflow completion rate, policy violations, schema validity, avg/p95 latency. - Gate releases in CI: block deploy if worst-case workflow regresses >2 percentage points. - Maintain a failure taxonomy (retrieval, ambiguity, tool error, policy block) with owners. 6) Observability and auditability (SRE + Security) - Trace every run: inputs, retrieved references, tool calls, outputs, approvals. - Store an “agent ledger” (immutable event stream) for audit and customer disputes. - Add replay tooling: reproduce a past run with the same context and tool outputs. - Define incident playbooks: fail-closed mode, rollback steps, and communication templates. 7) Pricing and ROI instrumentation (GTM + Finance) - Pick a pricing unit aligned to value: per completion, per action, or hybrid with a base fee. - Add customer budget controls: monthly caps, quotas per team, and overage ceilings. - Report ROI in-product: time saved, tasks completed, reduction in escalations/rework. - Run a 30–90 day pilot with a written success criterion before scaling. Exit criteria (ship v1 when all are true) - Completion rate meets target on golden set (e.g., ≥90% for narrow workflows). - Policy violations are effectively zero for high-risk actions. - Latency is acceptable for the workflow (e.g., p95 < 5s for interactive, < 60s for batch). - Audit evidence can reconstruct “who/what/why” for any agent action. - Cost per completion supports target gross margin with a 20–30% buffer.