AI Product Roadmap: From Problem to Useful MVP

Start with a decision the product should make easier

I start a roadmap with the work someone needs to do. Describe the person, their current process and the point where it becomes difficult. An AI feature is only useful if it changes something meaningful in that process; a list of model capabilities does not establish the reason to build.

Write down the next useful outcome in ordinary language. A support team might need to review an incoming request with its context in one place. That description gives you something to discuss with the intended user before choosing a model, an interface or a long feature list.

Make the first version smaller than the ambition

Separate the essential workflow from the ideas that can wait. Identify its inputs, the result a user should be able to review and the decisions that still belong to a person. I want a roadmap to expose those boundaries instead of hiding uncertainty behind a launch date.

For each item, name the assumption it depends on and the person who owns the decision. If the audience or source information is unclear, resolving that question belongs in the plan. Building around an unanswered question usually makes the later review harder to interpret.

• Validate the idea before expanding the roadmap →

Give the MVP a review point

A working version should help you examine the original problem. Decide who will try it, which task they will attempt and what evidence you will discuss afterward. Review whether the workflow makes sense, where the output needs correction and what the business would need to operate it.

I treat the roadmap as a sequence of decisions rather than a promise that every initial feature will survive. Keep what the evidence supports, refine what is unclear and remove work that no longer serves the audience. That is the starting point I bring to a practical Build conversation.

• Apply to Build with a clear starting point →