Mural CPO on How to Put AI in Multi-Player Mode So Teams Collaborate with Shared Context Instead of Working Solo | Elaina O'Mahoney | E309

Visual collaboration is missing from the AI era. That's the provocation Elaina O'Mahoney, Chief Product Officer at Mural, brings to this episode of The Product Podcast with Carlos González de Villaumbrosia, CEO at Product School. We spend all day alone in our tools, typing or talking to an LLM, and when it's time to collaborate we drop words into a doc instead of thinking together visually. Elaina makes the case that AI has quietly turned work into "solo-player mode," and that the teams who win next will be the ones who rebuild shared context and multiplayer collaboration on top of it.

Elaina and Carlos González de Villaumbrosia get into why ideas are now cheap (you can go from a thought to a working prototype in hours) and why that makes shared context, not idea generation, the real bottleneck. She argues that everyone is a designer at heart, that product leaders should replace the five-page strategy doc with a fast prototype that conveys the North Star, and that "shipping" can mean a workflow or an agent, not just a production release. They also dig into the crowded "where work happens" landscape (Slack, Teams, Jira, Linear, Notion) and the blank-canvas gap around how and why decisions actually get made, how to create safe spaces for people to try AI and fail inside large enterprises, and the pricing tension between legacy seat-based SaaS and AI-native usage models.

What you'll learn

• Why Elaina says visual collaboration is "absent" in the AI era, and why that matters

• The "solo-player mode" problem: how AI made work lonely, and what multiplayer should look like

• Why ideas are now cheap, and how that shifts the bottleneck to shared context and faster decisions

• Why the real blank space isn't planning or chat, but how and why decisions get made

• The case that everyone is a designer, and how visual thinking speeds up decisions

• How a CPO ships to demo a direction (a prototype instead of a strategy doc)

• What's still scarce in an AI world: data science, taste, and synthesizing analytics

• How to create safe, low-risk spaces for teams to try AI and fail inside big enterprises

• Why smaller "champion" teams beat top-down rollouts, and how internal builders spread practices

• The pricing dilemma: seat-based SaaS vs. AI-native usage models

Credits
Host: Carlos González de Villaumbrosia
Guest: Elaina O'Mahoney

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