When building customer-facing AI advisors, one of the biggest challenges is ensuring ideal and compliant performance across a wide range of situations. There are several measures to support this goal—ideally, you combine all of them. One powerful method is simulating conversations between a customer persona and the AI advisor.

Vibe coding is here to stay. It lowers the barrier to software development, empowering non-engineers to spin up prototypes — even production-ready apps — in a matter of days. Sure, there are limits to what’s possible today. But these tools are just getting started.

Personally, I care less about the “vibe” — and more about the raw productivity boost they unlock for experienced engineers like me.

This framework is not only at the core of human thinking. It is also the foundation of machine learning. I find that applying terminology and abstraction from machine learning to this human framework is really helpful in becoming more aware of it and in applying it more effectively.

… So yes, having use case relevant data can create a competitive advantage. However, the above incomplete perspective is dangerous because it overlooks three equally important success factors for AI value creation and competitive advantage: product discovery, product design, and solution architecture.