Translating ideas into code has always been messy. Specs, user stories, and endless discussions often leave developers guessing: “Is this what they meant?” Misunderstandings pile up, and the real work—writing great code—gets bogged down in back-and-forths.

What if there were a way to smooth that process? Imagine starting with a prompt, written in plain language, that describes what a feature should do. From there, the AI generates tests, turning the prompt into something concrete—something the whole team can align on. And when those tests look right, the AI writes the code to make them pass. It’s not about skipping steps but cutting through the noise, so developers can focus on solving problems and shipping great features.

Could this be how we close the gap between product intent and implementation? Could test-first workflows like this make quality implicit and productivity effortless? In this talk, we’ll explore these possibilities, from the way prompts reshape collaboration to the role of tests in bridging understanding, and how AI fits into it all.

Maybe building software doesn’t need to feel like a grind. What if it could feel... easier?