From Prompt to Production: Building Custom AI Agents That Actually Ship
A working demo and a production agent are not the same thing. Here is the gap most teams underestimate, and how to close it.
By Greenmint Labs · Engineering
It takes an afternoon to get an AI agent to do something impressive in a demo. It takes considerably longer to get that same agent to run reliably in production, inside real systems, with real consequences for getting it wrong.
What a demo skips
A demo doesn't need error handling for a system that's down, a fallback for an ambiguous request, or a log of what the agent actually did. Production does — and that work is most of what separates a prototype from something you can trust.
Ship in stages
Start the agent in a read-only or human-approved mode, watch how it behaves on real requests, then expand its authority as it earns it. Shipping in stages is slower on day one and considerably faster than the alternative, which is relaunching after a failure erodes trust in the whole project.