Welcome to TiPS – the Topics in Product Series – a new podcast format powered by ITX and the team at Product Momentum. The TiPS mission is to engage the same important product space issues that you confront every day – but this time through the experiences of ITX product managers, UX researchers and designers, engineers, security analysts, and the rest of the team.

In this inaugural TiPS episode, Dan Sharp is joined by Sean Murray and Andrew Knoblauch to reflect on a recent Product Leaders Breakfast, hosted by Prerna Singh. Together, they draw on insights from event attendees to discuss how AI is being applied inside real organizations.

The central theme was clear: successful AI adoption depends less on hype and more on first principles and core product skills that drive disciplined product thinking, incremental progress, and strong decision-making.

Here’s what we learned:

Top-Down ‘Do AI’ Directive Is the Wrong Reason for Integrating AI

The integration of AI into software development is no longer the proverbial “hammer in search of a nail.” The days of doing AI for AI’s sake are behind us. Today’s product leaders focus on making incremental improvements tied to bona fide business problems.

As Sean points out, our response to the ‘do AI’ directive should be: “’Where do you want to see improvement? What outcomes are you looking for?’ I think back to our conversation with Teresa Torres, about applying best practices in the initiation and discovery phases of the SDLC so that when we actually get into building something, it’s gonna have some sort of relevant business value.” It’s a more grounded approach that reflects a broader industry need to align AI efforts with tangible outcomes..

Building Stakeholder Trust Through Incremental Change

Trust emerged as a critical factor in AI adoption, but not only in the technical sense. Instead, as attendees discussed, trust is built gradually through careful implementation and organizational alignment. Andrew explains that product teams build trust not by tackling the biggest, riskiest challenge – but by prioritizing low- to medium-risk opportunities while involving stakeholders early, especially those in Legal and Compliance.

“This idea of building trust among others in your organization.” Andrew continues. “We do this every day with our clients and with our own teammates. We learn about people’s concerns, what they care about.” The conversation reinforces the idea that AI should be introduced as a collaborator within workflows, not as a replacement for human judgment.

Decision Quality as the True Differentiator

One of the key threads weaving through our conversation was a return to foundational product principles – specifically, the importance of decision-making. While AI fluency is valuable, it does not replace the need for strong judgment and clear thinking. Teams that succeed will be those that consistently make informed, high-quality decisions, Sean says. “The biggest differentiator moving forward is gonna be decision quality…your ability to consistently make good decisions.” In this context, AI becomes an enabler, not the driver, of product success.

The conversation at the Product Leaders Breakfast (hosted by Prerna Singh) reinforces a familiar but essential message for all product leaders. AI does not replace core product skills; it amplifies them. Teams that stay focused on problem definition, stakeholder alignment, and disciplined execution will be best positioned to realize its full potential.

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