How It Works

The product workflow remains grounded in observation and conversation:

1. Talk to potential or current customers.
2. Determine what they actually need.
3. Build a prototype that resembles the needed solution.
4. Test whether it solves the real problem.
5. Refine the product based on what is learned.

AI creates a major advantage after the problem has been understood. The team can build prototypes faster, delegate implementation tasks, and encode repeated product or engineering procedures into skills.

The danger appears when faster implementation is mistaken for better product selection. If the agent is asked what major feature should be added next without customer context, it may generate plausible scope rather than the right scope. The human must choose the features because the human is responsible for the mission and has access to the real-world feedback.

Agents can be used constructively to reduce scope. Useful questions include: What can be removed?

How can this workflow be simpler? Which feature distracts from the user's central goal? How can the experience focus more directly on what customers are trying to do?