Why AI Agent Demos Break in Production

An AI agent demo only has to work once, on a clean input, with you watching. In production it runs again and again on messy real inputs, and nobody's watching.

I've built AI into real products, from a repricing engine that runs 24/7 for a US Amazon seller to a voice automation platform for a company in Germany. These are the three things I put in place before any agent goes live:

1. Scoped tools, not open access

Give the agent a short list of actions it's allowed to take, each with its own limits, instead of raw access to your database or APIs. Anything that touches money, customers or deleting data needs a human to approve it.

2. A plan for when the model fails

Model calls are slow, they time out, and sometimes they return something that makes no sense. Run agent work in background jobs with timeouts and retries, check the output before acting on it, and hand the task to a person when it still can't be trusted.

3. A log of every decision

Store every input, tool call and output. When the agent does something strange (and at some point it will), you can see exactly why and fix it instead of guessing.

None of this shows up in a demo. All of it decides whether the agent is still running a month later.

Planning an AI agent for your product? I offer a free build audit: calendly.com/roshaanali-business

"Works once with you watching" is the best way I've heard it put. Timeouts and a human fallback are the parts most demos skip.

Which one you guys prefer.

A or B

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