What Happens When Demo AI Meets Messy Reality

Why do our AI Agent pilots actually make it into production?
Open source. Built in public.
That's our philosophy, and today I'll share one of our "secrets."

This came up during a client meeting with Lyubomir today.
We do our final tests in production.
Not after the pilot... during the pilot.

Simple.

Yet almost nobody does it, and today it saved one of our AI Agents.

Everything had worked perfectly during the traditional testing phase.
Then we hit a bump in production.

The reason?
The production environment contained many more customer references than the test environment.
When the Agent searched for an existing customer before deciding whether to create a new record in the ERP, the dropdown list was suddenly several times larger.

It could no longer confidently identify the correct option.
Even better...
Instead of guessing, the Agent stopped and was going for human validation because something wasn't right. (True story.)

That's exactly how we designed it.

The client was surprised we had tested the pilot at that level.
Even better, because we were testing in production, we solved it immediately on the call.

It's one of the reasons our clients are seeing results in few months.

Building AI Agents isn't just about making them work in a demo.
It's about making them reliable when reality gets messy.

Have you ever had something work perfectly in testing... only to discover the real challenge once it met production?

Have a great week,
Alexis

P.S. And if you're building an AI employee internally, feel free to borrow our methods and experience, contact me even with questions. We genuinely share them because our goal is also to help the people who aren't in a position to work with Capto.

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Originally posted on LinkedIn:

https://lnkd.in/p/dRHDQ5mM