Building Tools No One Needs
You can spend months building an AI tool, ship it, and watch nobody use it. And the really painful part is that you might have genuinely believed it would work. Because it had the word AI in the name, and AI is exciting, and surely people will want it. That logic is wrong, and a lot of people are learning it the hard way right now.
The core issue is that AI engineering skill doesn’t automatically come with domain knowledge. An engineer can build something technically sophisticated while being completely wrong about what a specific industry actually needs day-to-day. They imagine the problems based on secondhand information, they build for their mental model, and they end up with something that real practitioners look at and say “that’s not how this works.” This isn’t a failure of intelligence. It’s a failure of grounding. The solution isn’t more technical sophistication. It’s more time spent with real people in the field before a single line of code is written.
This is exactly why the n=1 approach matters so much. If you’re building something for an industry you’re in, you don’t have this problem. You know what’s actually annoying. You know where the time goes. You know what a field supervisor actually needs versus what looks good in a slide deck. The people who build tools that get used are almost always building tools they themselves needed, or tools they built in close collaboration with someone who needed them badly. The outsider who tries to imagine their way into a niche is almost always wrong about the details that make the difference between something people use and something they ignore.
The practical check is simple: before you build, can you point to a specific person who has told you they would pay for this? Not “I think people would want this,” but a real conversation with a real person who has a real problem and has said some version of “yes, if that existed, I’d use it.” If you can’t do that, you’re not building a product yet. You’re building a hypothesis. Those are very different things to invest months of your life in.
Key Takeaway
Build for real people with real problems you’ve actually witnessed, not for an imagined user who would presumably want something because it uses AI.