I’ve watched too many AI agent implementations fail this year. Same reason every time.
We build impressive agents. The tech works, the demos shine, it’s amazing. But adoption? Zero.
Here is why. We start building agents when we should start by deeply understanding the work. It’s the same lesson every successful startup learns: fall in love with the problem, not your solution. Somehow, when AI enters the picture, we forget the basics. We jump straight to building and skip the most important step.
What actually works: spend time with domain experts. Map how things really get done today. Redesign the workflow. Then, and only then, build agents into that new process.
When you know the domain deeply, you automate the right things. You preserve human judgment where it matters, and adoption happens naturally. Skip this and you’re just hoping technology fits somewhere.
Agentic workflows that succeed aren’t the most sophisticated. They are the ones grounded in real expertise.
First published on LinkedIn.