AI systems don’t just execute they decide. And that makes them harder to predict, test, and debug. This hands-on workshop helps developers move beyond treating AI as a black box by designing how these systems behave.

Participants will break down a real AI feature, map decision points, define constraints, and identify failure scenarios. Using accessibility-driven edge cases and ambiguous inputs, we’ll stress-test system behavior and redesign it for clarity, control, and reliability.

By the end, you’ll leave with a practical framework to make AI systems more understandable, testable, and easier to debug in production.