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Product SchoolMural CPO on How To Put AI in Multi-Player Mode for Your Team | Elaina O'Mahoney
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At a glance
WHAT IT’S REALLY ABOUT
AI made ideas cheap; shared context now drives team decisions
- Elaina O’Mahoney says visual collaboration has gone missing as AI work shifts into isolated chat experiences that don’t naturally create shared team context.
- She argues that because AI makes ideas and artifacts fast to produce, the real constraint is connecting those artifacts so teams can make high-quality decisions quickly with the same context.
- She describes a converging tool landscape where many products claim to be “where work happens,” yet the “why” behind decisions remains poorly captured in the moment.
- She emphasizes building prototypes and workflows (often in safe environments) as a faster alternative to lengthy strategy documents, while encouraging broader “everyone can design” participation.
- She highlights enterprise challenges around adoption, champions, measurement, and pricing—warning that token limits and mandates can create perverse incentives unless outcomes and predictability are prioritized.
IDEAS WORTH REMEMBERING
5 ideasAI has pushed collaboration back into solo-player mode.
Elaina O’Mahoney argues that most AI work today happens in a “lonely” chat-based experience, which makes it harder to build shared context with coworkers when it’s time to align and decide.
Ideas are cheap; shared context and decision-making are the bottleneck.
She says AI makes it easy to generate compelling docs, slides, and even working prototypes quickly, but teams still get stuck when those artifacts live in disconnected places and people lack a common starting point.
The most valuable space is capturing decision context, not just outcomes.
Elaina describes a “blank canvas” problem across the modern work stack: tools handle communication, planning, and reporting, but they often miss the in-the-moment context for why a decision was made.
Replace strategy docs with prototypes to speed up alignment.
She emphasizes that “shipping” can mean building workflows, agents, or prototypes in safer environments—not always deploying to production—and suggests prototypes can replace slow-moving multi-page strategy documents to accelerate alignment.
Enterprise AI adoption needs safe spaces and visible learning.
In large enterprises, she says adoption requires lowering risk and creating forums where employees can try, fail, and learn from others’ work, since AI experimentation is otherwise hard to observe and copy.
WORDS WORTH SAVING
5 quotesWhat's interesting is visual collaboration is actually absent in the AI era.
— Elaina O'Mahoney
We are all in our tools, all by ourself, with words or voice.
— Elaina O'Mahoney
Just because you can with AI, and I'm probably gonna say the controversial thing, doesn't mean you need to do with AI.
— Elaina O'Mahoney
The space that really is still ambiguous is how are decisions getting made and the context of why that decision is made.
— Elaina O'Mahoney
We, our CTO and myself, are meeting with the teams to say, "What did we learn?" We're not just saying, "What did you ship?" It's, "What did you learn?"
— Elaina O'Mahoney
SPEAKERS
Elaina O'Mahoney
guestChief Product Officer at Mural, focused on product strategy and AI-enabled visual collaboration.
Carlos González de Villaumbrosia
hostCEO at Product School and host of the Product Podcast.
High quality AI-generated summary created from speaker-labeled transcript.
