Flattening the learning curve with agentic AI

OptiKPI is a customer intelligence platform for gaming operators. It started as an MVP and grew for years in the hands of good engineers who had never worked on user experience. Let me say this the way it deserves: it was not a bad product. It had worked for years, it had real customers, and it had reached the limit of the structure it was built on. Almost every product that starts this way gets to that point, usually at the worst moment, which is when the company begins selling to customers larger than the ones the product was designed for.

From there every new feature cost more than the last. Each one landed on a structure never meant to hold it, and the product kept talking to the first kind of customer while the company was chasing another.

With the founder we decided to rebuild rather than patch. Putting the existing structure in order would have made a wrong structure more bearable, not different, and every month spent on that was a month the problem came back bigger. It is a decision that costs, and it was possible because the person who had to approve it accepted stopping before starting again.

Version 2.0 was rebuilt from the information architecture up, with an AI agent inside the platform and a structure that takes the next feature without breaking the last one.