This is the AI workflow automation checklist I’d use if I had to ship a reliable workflow today — without building a fragile mess.
If you want the full theory + architecture, read the pillar: AI workflow automation (complete guide).
This post is the operational version.
Phase 1 — Map (30 minutes)
1) Define the workflow in one sentence
Template
When [trigger] happens, the system should [output], unless [stop condition].
Example:
When a lead submits the form, create a CRM record and send a 3-question qualifier, unless the email is disposable.
2) Lock the inputs
List the inputs you require (keep it short):
- name
- one context field (e.g., “goal” or “problem”)
If you need 14 fields, you’re overbuilding.
3) Lock the output
Outputs must be observable:
- record created
- message sent
- task created
- file generated
Phase 2 — Model (2–3 hours)
4) Write decision rules (deterministic)
You need at least 3:
- If input missing → request required fields
- If confidence < threshold → route to manual review
- If retry count exceeded → stop + alert
Pair this with: Decision rules for builders
5) Add a minimal retry policy
Only retry transient failures.
Retry allowed
- timeouts
- rate limits
- temporary 5xx
Retry NOT allowed
- invalid data
- missing required field
- auth failures (fix the root cause)
6) Add logging (the difference maker)
Log these fields every run:
- run_id (timestamp + random)
- workflow_name
- trigger
- status (success/fail)
- error_code (if fail)
- latency_ms
- output_id (ticket/record id)
This is how you debug in minutes, not days.
Phase 3 — Move (ship + stabilise)
7) Define “healthy” thresholds
Pick 3 metrics:
- Success rate (target: ≥ 98% weekly)
- Median latency (target: < 30s)
- Manual review rate (target: < 10%)
8) Set alert rules (only when meaningful)
Alert when:
- success rate drops below threshold
- errors spike above baseline
- queue/backlog exceeds limit
No alerts for single failures unless it’s revenue-impacting.
9) Create a 5-minute runbook
Runbook must answer
- What broke?
- Where is the log?
- How do I replay a run?
- What is the safe fallback?
The one-day build plan
Hour 0–1
- Map the workflow (sentence + inputs + outputs)
- Write 3 decision rules
Hour 1–3
- Build the workflow
- Add logging
- Add retries
Hour 3–4
- Test 10 runs
- Break it on purpose (bad input, timeouts)
Hour 4–5
- Add alerts + thresholds
- Write the runbook
Then ship.
If you only do one thing: add observability
Most builders lose months because workflows fail silently.
If your workflow logs nothing, you don’t own a system — you own a mystery.
For the full architecture, use: AI workflow automation (complete guide).