Most AI agencies are solving the wrong problem. They're obsessed with building the perfect workflow when they should be obsessed with adoption. I see this pattern everywhere: Someone builds an incredible AI system. It works flawlessly. It saves hours of manual work. And then... nobody uses it. Why? Because there's a massive gap between "this works" and "this gets used." The best AI implementations I've seen aren't the most technically sophisticated. They're the ones that feel inevitable once you see them. Amazon's recommendation engine isn't impressive because of its ML complexity. It's impressive because it shows up exactly where you're already shopping. The winning approach isn't about making AI smarter. It's about making AI feel like it belongs in the workflow people already have. This means starting with behavior, not technology. Instead of asking "what can AI do?" start with "what do people already do, and where does friction exist?" The future belongs to builders who design AI around human patterns, not the other way around. Most people are building AI solutions and then trying to convince users to adapt. The winners are studying user behavior first, then building AI that fits seamlessly into what already works.

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