I’ve been hearing about AI copilots that can take a description like “flag high-value orders and escalate them to our sales team” and generate a working workflow from it. That sounds incredible on paper, but I’m trying to understand the real-world execution.
When I think about deployment cycles, we usually spend time on requirements gathering, workflow design, error handling, edge cases, and testing before anything goes live. Does an AI-generated workflow skip those phases, or does it just move them elsewhere in the project?
I’m particularly interested in whether the generated workflows actually handle the messy parts—exception cases, retry logic, integration failures—or if you’re rebuilding those manually after the initial generation.
For anyone who’s tried this, how much rework did you need to do before a generated workflow was actually production-ready?