The AI gold rush is in full swing, and most of the prospectors are digging in the wrong places.
The Problem with "AI-First" Thinking
Every week, a new startup launches with the pitch: "We're using AI to revolutionize X." The technology is impressive. The demos are slick. And six months later, the product is dead.
Why? Because they started with the solution instead of the problem.
What Actually Matters
The products that win aren't the ones with the most sophisticated models. They're the ones that deeply understand a specific pain point and use AI as an invisible accelerator.
Here's the framework I use:
- Start with the workflow. Watch how people actually do the task today. Where do they waste time? Where do they make mistakes?
- Identify the bottleneck. Not every step needs AI. Find the one moment where intelligence — pattern recognition, generation, prediction — would remove the most friction.
- Make it invisible. The best AI features don't feel like AI. They feel like magic. The user shouldn't need to understand prompts or models.
The Litmus Test
Before building anything, ask: "Would someone pay for this if it wasn't AI?"
If the answer is yes, you have a real product. The AI just makes it better. If the answer is no, you have a demo — not a business.
Build for the problem. Let the technology serve the solution.