Teams that hadn’t touched AI in early 2024 now use it every day to generate ideas, write PRDs, analyze research, and build working prototypes. I see it in my own work: I went from using AI a few times a day to running three or four threads in parallel, all day long. Output is up. Velocity is up.
And yet, I keep seeing the same picture: clogged GitHub repos, stacks of unread AI-generated PRDs, and prototypes abandoned by ambitious individuals who never got the buy-in to get them across the finish line. AI has turned the most ambitious people on every team into 10x versions of themselves. But it has also made it harder than ever for them to play together. The future of AI-powered product work will be defined by who can turn shared context into shared progress.
What this essay explores
- Use a collaborative canvas as shared context instead of keeping AI work in individual silos.
- Understand how persistent, board-based agents can refine work as new team context arrives.
- Turn workshop notes, customer quotes, and rough ideas into structured next-stage product outputs.
- Review live prototypes together to resolve actual interactions rather than debating static mocks.
- Connect the canvas to coding tools so AI can read and eventually update shared context.
- Recognize why faster building shifts the bottleneck to shared understanding and harder choices.
AI’s next leap is collaborative: from individual sidekicks to multiplayer teams.
Key takeaway
The first wave of AI was single-player. The next wave is multiplayer.
