The AI-Native Engineer: From Business Problem to Prototype

How well you scope a problem determines how well AI can help you solve it. This workshop makes that claim testable, not just believable.

Bring your laptop and the AI tools you already use. Teams take on a real, messy business challenge — a live-service gaming company caught between an AI feature its CEO already announced and the fragile data foundation that feature would actually run on. Before building anything, each team is randomly assigned exactly one stakeholder to interview. What they hear — and how well they turn it into a scoped, defensible approach — is the variable we’re testing.

From there, teams use their own tools and AI to build a working solution slice with AI as a genuine collaborator throughout. We instrument the build: prompts submitted, iterations to a working version, time to first pass. At the reveal, we show the correlation directly: teams that scoped tightly from partial information moved faster and cleaner with AI than teams that tried to build before they’d committed to an approach.

Every participant leaves with a personal build card — their own scoping-to-efficiency numbers next to the room’s benchmark — and a sharper instinct for a skill AI hasn’t replaced: knowing what problem you’re actually solving, from an incomplete picture, before you start.