What AI is actually good for

The first thing you learn when you build AI agents yourself (not just use them, but actually build them), is what they still can’t do. The second thing you learn is how few executives know the difference. I run Syndio, a 140-person pay-decision intelligence company serving nearly 400 enterprise customers, including half the Fortune 100. Two years ago, I was using AI the way most executives do: organizing information, drafting emails. It helped at the margins and missed what mattered. The drafts were polished. They sounded nothing like me. More importantly, the AI reasoned nothing like me. In my early innings with AI, I made all the rookie mistakes. And unfortunately, my mistakes became magnified because I was also modeling for my team. I used AI to create the agendas for my executive-leadership meetings. Without context and direction, those agendas became word salads and AI slop. I knew it could do better. So I enrolled in a six-week course for executives taught by Nufar Gaspar, a former Intel executive. It didn’t teach us to use AI. It taught us to build systems that could reason alongside us, that remember context, challenge assumptions, and adapt to how we think, not how a product manager imagined we might. I took the class on the weekends and in the evenings. This is the part that most executives miss. You can’t get good at AI in between meetings. It truly requires the kind of unstructured thinking that most of us wish we had more of. When I was early in my CEO journey at Syndio, a seasoned Microsoft executive named Dean Hachamovitch gave me sage advice. “Protect your thinking time,” he said. I’ve returned to those words often over the years, but they feel especially relevant today. In an era of AI, the scarcest resource isn’t information, it’s the uninterrupted space to think. The agent build process taught me that most executives are solving the wrong problem. The assumption is that AI’s value is productivity: go faster, del