When Alex Duffy and his team set out to adapt the strategy game Diplomacy for AI, the goal was simple: create a benchmark that was both rigorous for researchers and entertaining for the public. What started as a fragile demo quickly evolved into a global event, streamed live to tens of thousands on Twitch. The secret? Treating context not as data, but as storytelling.

Early prototypes failed because models choked on raw tables of territories and moves. The breakthrough came with a shift in perspective: instead of feeding LLMs endless lists, the team framed the game in human terms—summaries of goals, alliances, betrayals, and outcomes. This “context engineering” allowed the AIs to strategize realistically and even develop personalities that viewers could follow.

Equally important was the interface. Rather than a research tool hidden in labs, AI Diplomacy was designed to be accessible: a polished 3D map, synthetic narration, and even an original AI-composed soundtrack made the experience engaging enough for anyone to watch. The game wasn’t just a test of AI performance—it became a story people wanted to tune into.

Behind the fun was a set of serious lessons for AI builders: inference speed shapes design choices, structured outputs can stifle creativity, and step-by-step reasoning dramatically reduces hallucinations. Most of all, the quality of context determines whether AI behaves like a random generator or like a believable player with intent.

The success of AI Diplomacy proves that benchmarks don’t need to be abstract or boring. By combining technical rigor with narrative and design, the team showed that AI research can be both insightful and widely appealing—a blueprint for future projects at the intersection of science, storytelling, and public engagement.