Production Patterns
Crews fail loudly (loops, bad tools) and quietly (plausible wrong reports). Production patterns separate a notebook from a service.
A kitchen with tickets, a pass, and a manager who can kill a dish. Not a potluck.
Visual Workflows
Start here — scroll inside each diagram frame to explore, then use + / − to zoom up to 200% if needed.
Scroll inside the frame to explore · use + / − to zoom up to 200%
Key Takeaways
- 1.A demo crew is not an engineered application. Production adds guardrails, retries, HITL, cost, and eval. Guardrail: validate output → yes continue / no retry. Policy lives in code.
- 2.Tool failures need recovery. Sensitive actions need human approval before execute. Log, trace, and evaluate task success — not just the crew returned text.
- 3.Validate structured output and retry. Cap iterations and timeouts.
- 4.Budget tokens per kickoff. Pause for a human on irreversible work.
- 5.Trace each task. Eval: did the report match the expected sections, not did it look good.
Learn elsewhere
- →Eval Engineering — Phase 19
- →Security — Phase 20
- →Production — Phase 21
Real Example
Scenario
Research crew: expected sections must exist, timeout 120s, log cost per topic, human review before publishing.
What you would do
In CrewAI, apply Production Patterns to this scenario: Research crew: expected sections must exist, timeout 120s, log cost per topic, human review before publishing. Identify the inputs, run the technique, validate the output, and note one thing you would monitor in production.
Commands
Commands to Remember
Validate then retryHITL on irreversibleTimeout + max iterationsEval task success
Cheat Sheet
Quick recap
quick ref- •Guardrail in code
- •HITL for publishes
- •Budget the run
- •Eval like a product
Common Mistakes
- ✕Skipping evaluation for Production Patterns before production
- ✕No logging or tracing around crewai production steps
- ✕Ignoring cost and latency implications