Teams | Collaboration | Customer Service | Project Management

If agents write the evals, draft the specs, and run the loops, what work is left for a product manager? One answer I keep seeing online is that product writes the evals, approves the agents, orchestrates the loops, and picks one at the end. At ProductCon San Francisco, I made the case that product’s role is much bigger: deciding what’s worth building and bringing a team along, which is especially important as agents accelerate building.

In September, our community published around 100 new templates: stakeholder maps and OKR trackers sat alongside accessibility checklists, strategic roadmaps, and a wave of templates landing in Spanish, Portuguese, and French. The throughline for the month was AI finding its way into everyday workflows – Miro Flows and Sidekick-powered boards built for use case ideation, risk brainstorming, and keeping AI-assisted projects on track.

Most governance policies were written for defined records, such as a signed document, a sent email, or a file with one author and one date. That type of work still exists, but it now also takes place in team chats, AI conversations, and across canvases.

Debbie Levitt, CXO of Delta CX, refused to bring AI into her work for a long time. Three years ago she tested the tools, found they couldn’t think critically or get basic facts right, and kept them out of her process. A year later, despite her initial disappointment, she decided to run an experiment based on her real work, and was amazed by the results.

AI agents have made more than 19 million tool calls to Miro’s MCP server since February 2026, and the users behind them span product, design, marketing, operations, and project management. When we launched Miro’s MCP server in February, we had AI coding tools in mind.

Josh Guice, Field CTO at Liatrio, says he can usually tell within the first few conversations whether a client’s AI rollout is actually working. Two or three people are quietly doing something impressive with it. Everyone else is stuck, spending more time wrestling with the tools than they used to spend on the work those tools were supposed to replace. He compares it to dropping a new graphics card into an old motherboard. The card itself is fine.

Individual AI adoption has outpaced our ability to redesign how teams actually work together. The numbers back it up. In Forrester’s “The Visual Era of Collaborative Intelligence”, 89% of leaders say improving collaboration is key to hitting their organization’s goals – yet 75% agree most AI tools are built for individual, not team productivity, and 39% say that individual-first bias is actively hurting their AI ROI.

Pick an animal. Now pick the strengths you bring to your work. Combine the two, and you’ve built yourself a superhero. That was the warm-up exercise H&M Group used to open an AI Learning Day for its tech teams, and it set the tone for everything that followed: you come to the table with your superpowers, and AI handles the mundane.