AI Observability Readiness Checklist (2026)

Goal: In 10–14 days, get to a baseline where you can (1) reconstruct what the AI did, (2) measure quality changes, (3) attribute cost, and (4) prove policy compliance for key workflows.

1) Define your “critical paths” (Day 1)
- List the top 3 AI workflows tied to revenue or risk (e.g., support answers, invoice triage, account research).
- For each workflow, write 2–4 acceptance criteria (examples: citations present; no restricted sources; tool action matches user intent; response under 8s p95).
- Assign an owner for each workflow (product or engineering).

2) Instrument tracing end-to-end (Days 2–5)
- Choose a canonical trace ID and propagate it through gateway → orchestrator → retrieval → tools → model calls.
- Add structured span attributes: tenant_id, user_role, model, prompt_hash, tool_name, index_version, input/output tokens, cost_usd.
- Log retrieval evidence as doc IDs + similarity scores (avoid raw content by default).
- Implement redaction: remove PII/secrets from prompts and tool outputs before storage.

3) Build a replay set (Days 4–7)
- Sample 200–1,000 real traces (sanitized, permissioned) that represent normal usage.
- Store minimal “replay bundles”: user input, resolved prompt template version, doc IDs/index snapshot reference, and tool outputs.
- Tag bundles by tenant segment, language, and workflow type.

4) Stand up evaluations (Days 6–10)
- Offline eval: run the replay set nightly; track acceptance criteria pass rates.
- Online monitoring: score 1–5% of production traffic for faithfulness, tool success, and policy compliance.
- Define regression thresholds (e.g., faithfulness -2pp max; tool success <99%; cost per successful task +10% max).

5) Cost controls (Days 8–12)
- Attribute cost per tenant and per workflow (not just total tokens).
- Add alerts for anomalies: daily spend +20%, avg output tokens +30%, tool calls/session +25%.
- Add caching where safe (prompt/result caching; retrieval caching for stable docs).

6) Governance and audit readiness (Days 10–14)
- Record policy checks as events (PII redaction, tenant isolation, restricted-source filtering).
- Set retention: raw traces 7 days; derived metrics 30–90 days.
- Implement role-based access for observability data (treat it like production data).

Exit criteria (you’re “baseline ready”)
- You can pull a trace for any user request in <5 minutes.
- You can answer: what sources were used, what tools were called, what it cost, and which policy checks ran.
- You have a nightly regression report and a canary/rollback plan for prompt/model/routing changes.