The prototype works. What else did it prove?

A convincing demonstration can establish something valuable: that a concept can be made tangible, that a workflow is worth exploring, that a new approach may fit a particular case. It does not automatically establish how the system will behave at scale, what an unusual customer will encounter, how a hardware interface will respond, or which team will own a changed process. Those are not reasons to stop prototyping. They are reasons to use the prototype well.

AI can make prototypes cheap enough to compare ideas that never reached a meeting before. It can help a developer inspect an old system before suggesting a change; help a tester expose a weak assumption; help a product colleague ask a clearer question while the work is still changeable. The gain can be substantial. The trouble begins when one vivid answer is mistaken for a finished agreement among people who saw different things.

AI4DEV gives participants foundational knowledge, mental models, and deep insights into using AI coding tools effectively across that full journey. We will consider both the opportunity of a faster first pass and the later economics of evidence, integration, rework, and adoption. What can each role now notice, test, and discuss with the others before a prototype becomes a commitment?

Follow the people around the prototype or Howard's experience.