Building World-Class Product Teams that Deliver Innovation and Impact in the Age of AI

“The magic doesn’t happen from the smartest person in the room. It happens when cross-functional teams make great music together.”

The Myth of the Solo Hero

Jeff Chow (Chief Product & Technology Officer at Miro) walks onto the stage and immediately does what great product leaders do: he lowers the temperature. He isn’t interested in yet another debate about whether AI is amazing or terrifying. He’s interested in the thing that decides whether any technology wave actually creates value: the way people work together.

Jeff has earned the right to talk about this. He’s led design teams, product teams, and tech teams. He’s been a founder. He’s worked in companies of different sizes and through different kinds of disruption. He jokes about being “Yoda” because he’s bald, but he’s quick to show the other side of the story: the leader who has “homered into the bushes” countless times, who has made mistakes in public, and who’s learned that the best outcomes rarely come from an individual hero. They come from teams.

That is Jeff’s anchor. The myth of the smartest person in the room, the romance of founder mode, the fantasy that a single brilliant operator can carry a product to greatness, it all collapses when you’ve actually built things at scale. Jeff’s lived experience has taught him that the magic is collective. It’s cross-functional. It’s messy. It’s human.

The Three Waves of Disruption

To explain why AI changes the stakes, Jeff maps the modern era into three waves. The first was the rise of digital and mobile, when many organisations adopted agile processes, design sprints, and faster loops between disciplines. The second was the pandemic wave, when remote work forced teams to relearn basic collaboration: how to combine asynchronous and synchronous working, how to maintain emotional connection while distributed, and how to build trust without hallway conversations.

Then comes the third wave, and Jeff doesn’t underplay it. AI is significant. It’s big enough to shift how work is done, how decisions are made, and how craft is expressed. But what’s most useful is that Jeff doesn’t insist the room should feel one way about it. He recognises the full spread of reactions. Some people are fatigued. Some are freaked out. Some are excited. Some are already building superhero fantasies with agents and copilots and posting online like they’ve unlocked a secret world. Jeff’s verdict is calm: all of those reactions are normal, and all of them can be true at once.

The part that matters is what disruption creates inside an organisation: appetite for change. When the world shifts, people become willing to question habits they’ve defended for years. Jeff’s core proposition is that AI is not only a productivity opportunity. It is a cultural opening. It’s a chance to fix the “tiny isms” that everyone complains about, and nobody has time to tackle.

The Problem with Tool-Centred Bureaucracy

He starts with a blunt critique of how most organisations work today. Our ways of working are centred around tools, not people. Each function has its own tools, and then operations have to stitch processes across them. Design here, roadmapping there, delivery somewhere else, knowledge scattered across systems that rarely meet. Jeff describes what that feels like in real life as a constant “record scratch” moment. You find momentum, then you have to update Jira. You want help, then you have to file a ticket. You get into flow, then you have to do admin to prove you’re working. The cost isn’t only time. The cost is energy. The cost is momentum. The cost is the feeling that you’re creating together rather than pushing artefacts through a machine.

Jeff’s alternative is deceptively simple. What if people were at the centre? What if teams could focus more on the work itself rather than the process around it? He isn’t saying teams shouldn’t be disciplined. He’s saying most organisations have over-rotated into tool-centred bureaucracy, and that bureaucracy is the enemy of innovation.

From there, Jeff describes what the best teams actually do. He says great teams share three attributes. They are constantly creative problem-solving together, not treating creativity as something one role owns and everyone else consumes. They are excellent at co-creation, building momentum through a genuine “yes, and” culture. And they are rapid decision makers, able to move without freezing each other with endless validation rituals. Jeff mocks the familiar blocker who turns every conversation into a demand for proof, as if even obvious reality needs research before anyone can act.

Then he says the uncomfortable part. These teams exist in most organisations, but they’re treated as the exception, not the rule. Our ways of working aren’t designed to unlock the best teams. They’re designed to manage the middle. That means process safety wins over speed, legibility wins over learning, and momentum becomes rare.

Three AI Shifts That Unlock Teams

This is where Jeff sees AI as the opportunity. Not because it replaces teams, but because it changes what teams can do. When there is disruption, and there is value, there is room to redesign the system. Jeff challenges the room to “skate to where the puck is going” and asks what happens when three AI-driven shifts become normal.

The first shift is omnipresent knowledge. Jeff points to copilots, knowledge retrieval systems, and agents that surface insights instantly. If information is available at your fingertips, teams can form faster, better hypotheses. They can move without waiting for someone to locate the data. Jeff calls out a pain that many researchers and product leaders recognise: the kickoff meeting where someone suggests a study that’s already been done. In an AI-enabled workflow, the work people already did shows up where it matters. The team can spend less time hunting and more time interpreting. Jeff sees this as a cross-functional upgrade because it raises the bar on how everyone engages with evidence. Instead of asking, “Where do I find the data?”, people learn to ask, “What does it mean, and what should we do next?”

The second shift is democratised craft. Jeff is realistic about the tension. Product managers will start concepting. Designers will start coding. Engineers will contribute across boundaries. It can trigger defensiveness and “not invented here” syndrome. Jeff’s answer is cultural: teams need to build the muscle to yes-and each other. Many people have rolled their eyes when a PM arrives with wireframes. Jeff names that reflex and challenges it. In an AI-shaped future, the first draft will often come from a robot. The competitive advantage is not who can produce the first artefact. It’s who can collaborate on the second and third. Jeff believes this can accelerate concept cycles and make discovery more energising, because visual communication makes conversations more concrete. When people can see and click an early idea, debate becomes collaboration.

The third shift is faster automation. Agents and automated workflows collapse long processes into a handful of steps. Jeff argues this will increase the amount of time teams spend in the most valuable state: creatively working the problem together. He imagines workshops, design jams, and hackathon energy becoming less of a special event and more of a normal rhythm, because the friction that forces those events has been reduced.

Designing the Collaborative System

Jeff then shares what he’s trying at Miro, with a clear caveat: they don’t have it solved. The first focus is consistent rhythms across teams, where every product team is responsible for core collaborative skills: problem solving, pace setting, and empathetic communication. Jeff’s point is that pace without empathy becomes micromanagement. Communication without clarity becomes noise. Naming these as shared responsibilities, not job titles, gives teams a language for how they work, not just what they ship.

He also describes a simple organisational framework to navigate discovery, definition, and delivery. It uses shared milestones like kickoffs, solutions reviews, pre-release reviews, and impact reviews. Jeff stresses these are not stage gates. They are alignment points with clear next dates, which makes cross-team collaboration smoother and reduces executive thrash.

Inclusivity is another deliberate practice. Jeff talks about “bad version” as a way to lower the heat when sharing early ideas. If you label something as rough, people contribute more freely, and the team is less likely to litigate the first draft. He also shares an approach that cuts through corporate contortions: the “open for beers” version of a project. Instead of forcing an elevator pitch, Jeff asks teams to explain their work casually, the way they would to a colleague. Often, that phrasing is instantly clearer than the language teams have tortured themselves into for OKRs and strategy documents.

Jeff also embraces imperfection through practices like “inertia busting,” a straightforward way to ask for help unblocking stuck work, and “fail nights,” where teams share mistakes to normalise risk-taking. Finally, he talks about dogfooding. Miro is using Miro to transform Miro. They’re collapsing the stack by accelerating synthesis from unstructured brainstorming to structured documents, using AI sidekicks to challenge groupthink, pulling insights into the workspace instead of forcing context-switching, and connecting end-to-end work across tools like Figma so teams feel less fragmented.

The Real Promise of AI

Jeff summarises the experience with honesty: some days it feels like the team is jamming, and some days it feels like chaos. There’s no perfection, and no finish line. But he believes the organisation is moving in the right direction, with faster shipping and improved engagement.

He ends by returning to the heart of his argument. Engineering, product, and design are the heart and soul of organisations that build real things. AI is here, and it will keep evolving. The choice is whether we evolve our human systems alongside it. Jeff’s version of hope is not wishful thinking. It’s practical. Find the teams in your organisation that already work this way, with transparency, momentum, and co-creation, and stop treating them like an anomaly. Use this AI moment to make those behaviours the norm.

Because the real promise of AI is not that it makes individuals superhuman. It gives teams the chance to spend less time on record-scratch process pushing and more time making great music together.

Want to watch the full talk?

You can find it here on UXDX: https://uxdx.com/session/ways-of-working-building-world-class-product-teams-that-deliver-innovation-and-impact-in-the-age-of-ai/

Or explore all the insights in the UXDX USA 2025 Post Show Report: https://uxdx.com/post-show-report