AI isn’t magic—it just needs the same things a good teammate does: clear tasks, relevant context, and thoughtful feedback. In this post, I explore how breaking complex problems into smaller “Atoms,” layering in the right information at the right time, and asking for explanations—not just answers—can turn AI from a mediocre generalist into a reliable specialist.

AI hasn’t yet transformed businesses as promised because it’s often treated as just another tool. In reality, it functions more like a new kind of user—one that must be embedded across workflows, systems, and data. Unlocking its potential requires implementation consisting of four key ingredients: Intent, Information, Integrations, and Iterations.