John Cutler · 8 min read · Product Teams
TBM 418: Campfires, Trails, and Quests
Read the original on cutlefish.substack.com →
An exploration of how AI can support collaborative product development, emphasizing context-aware teamwork over polished but hollow outputs. The piece shares two 'multiplayer' experiments—Lane Coherence with Dotwork and Co-Prompting with a coworker—illustrating how co-design and shared context can raise leverage in team conversations, guided by the 4Es framework.
Key Takeaways
- AI should augment collaborative product work to speed up learning and higher-leverage conversations, not reinforce broken mental models or rigid PRD-based processes.
- Co-design and co-prompting, as shown with Dotwork and Cursor tests, help teams surface, test, and evolve guiding principles and context in real time.
- Real-world examples demonstrate AI acting as an imperfect but useful assistant that keeps mental models up to date while preserving human critique and conversation.
- The 4Es framework (Embedded, Enacted, etc) helps explain why these multiplayer AI sessions work: our thinking is shaped by context and action, not just output.
Excerpt
I guess I’m putting together an AI series of sorts. This is #7. Hope, Context, and Control Seeing Everything, Understanding Nothing (The Context Trap) Institutionalized Overload (Now With AI) Legibility and Legitimacy Before You Fire All Your Glue People Because of AI Simple-player to Mutliplayer: Context Through Collaboration At the day job, I’m deep in the question of how AI can help teams do more effective work, hence all the thinking below. It has highs and lows these days, with enough inspiring stories to keep me curious and hopeful. If you and your team ever want to chat about this,…