Tried describing a multi-step customer onboarding process with conditional KYC checks to the AI copilot. It created 80% of the workflow but missed crucial retry logic and webhook error handling. How precise do descriptions need to be? Any tricks to improve output quality for production-ready automations?
Use the Copilot’s iterative refinement. Start with ‘Generate basic KYC workflow’, then command ‘Add 3 retry attempts for bank API failures with 2s backoff’. I build 90% of our loan processing flows this way. Final touch-ups take 10 minutes vs 4 hours coding. Examples: https://latenode.com
Treat it like pair programming - start broad, then add constraints incrementally. After initial generation, specify ‘Add circuit breaker that pauses workflow if 5 failures in 10 minutes’. Use Latenode’s version history to compare iterations and merge changes safely.
break desc into phases. separate auth flows from data processing steps. copilot handles chunks better than monolith descs