Episodes

  • 187 / AI Native: Reimagining Product Roles and Development Cycles, with Adam Creeger

    187 / AI Native: Reimagining Product Roles and Development Cycles, with Adam Creeger
    May 13 2026
    Adam Creeger is the CTO of Slate and creator of iLoom (pronounced “il-LOOM”). His leadership experience at Meta, Greenhouse, and Frame.io not only informs Slate’s transformation into an AI-native organization, but also shapes the way AI influences product strategy, engineering workflows, and operational models. Throughout his conversation with Sean and Dan, Adam argues that becoming AI native is not about layering AI features onto existing products. Instead, it requires companies to rethink how software is designed, built, and operated – from the ground up. His perspective offers a practical framework for product leaders navigating AI-driven transformation. Here’s what else we learned: ‘AI Native’ Requires Organizational Reinvention AI native organizations are willing to rethink every layer of their business, Adam says. Rather than adding AI features superficially, AI native organizations redesign workflows, team structures, and customer experiences around AI capabilities. He emphasized that AI transformation changes not only products, but also how people contribute inside organizations. “To be AI native requires this deep exercise in re-imagination and not just imagination,” Adam continues. “In an AI native company – from the day-to-day operations to the ‘who does what’ – the roles and the owners of things are going to look very different.” AI is expanding participation across teams, enabling designers, support teams, and non-engineers to contribute directly to product delivery. That shift signals a major change for modern software organizations. AI and the Future of the Software Development Life Cycle (SDLC) Our conversation then turned to an exploration of how AI is already changing the traditional software development lifecycle. Years ago, Agile development emerged because humans had historically struggled to fully reason through complex systems before implementation. “I’ve realized that Agile was really a mitigation of a few things, mostly that we humans are limited in our abilities to reason through abstract concepts,” Adam says. “So when we thought about a software project, we didn’t have the ability to see around corners and understand the problems we’d face – until it was real, until you really started playing with it. Turns out that many of those challenges are very solvable by AI, allowing us to go much deeper into the problem space without ever writing a line of code. In addition, AI-assisted planning allows teams to revisit some waterfall-style thinking, but with dramatically faster iteration and validation cycles. Product Managers’ New Role: Communicate Context Importantly, AI is actually elevating the role of product managers, Adam offers. Rather than acting primarily as tactical decision-makers, product leaders can (and should) focus on providing context that enables teams to make informed decisions independently. “More than ever, the product manager has become a role about providing context,” he adds. “PMs should be elevated to a much more strategic role, understanding the long-term vision and helping to translate that to engineers.” Adam also feels that PMs should be using AI to communicate ideas about the product vision much more effectively. That evolution creates a faster and more collaborative product environment. Teams can evaluate real implementations earlier, gather customer feedback sooner, and align around outcomes instead of specifications alone. [05:54] What it means to be ‘AI native’. Conceptually, it’s same as digital native from when the internet was born many years ago. In the abstract sense, I see AI native being about the folks and the companies that are either just starting in the age of AI where everything they do is shaped by the existence of AI and their ability to use AI. [15:08] Is waterfall making a comeback? Oh man, this is one of my favorite topics. Growing up in the industry, waterfall was always like the evil thing. But with AI-assisted coding or agentic coding, you can go really deep, create a much bigger scope, and deliver it much more quickly…and it resembles more of a waterfall mentality. [21:51] The PM’s primary role: providing context. The product manager more than ever has become a role about providing context. The most powerful thing PMs can do in an organization is provide context to other people. [25:49] Exploring Adam’s iloom tool, and how it can help. Hear a quick story from Adam about how he used his iloom tool to create — and demo — a new product feature during a call with his customer success team. [28:47] Swarms. What are they, and how do they work? A swarm is a number of AI agents working together in a very collaborative way with the potential of real-time communication between them. [35:03] Avoiding ‘AI slop’ to defend and elevate a brand’s quality bar. Slate is creating a tool that makes it very difficult to create AI slop. This is a valuable proposition to...
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    45 mins
  • 186 / TiPS: AI-Enabled First Principles + Core Product Skills Spark Adoption

    186 / TiPS: AI-Enabled First Principles + Core Product Skills Spark Adoption
    Apr 29 2026

    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.

    The post 186 / TiPS: AI-Enabled First Principles + Core Product Skills Spark Adoption appeared first on ITX Corp..
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    24 mins
  • 185 / Confronting Cognitive Bias in AI Models, with John Haggerty

    185 / Confronting Cognitive Bias in AI Models, with John Haggerty
    Apr 23 2026
    John Haggerty brings more than 25 years of product leadership experience at companies like Datasite, Prodege, and Highway.ai. As co-founder and CEO of BiasHawk, John leverages his expertise in product management, behavioral psychology, and AI to develop an AI-powered platform that acts like a behavioral clinical psychologist to diagnose cognitive bias and heuristics in other AI models. In this episode of Product Momentum, John joins Sean and Dan to explore how AI is reshaping product work while also introducing new risks. John’s message is clear: as AI accelerates execution, product leaders must confront the invisible risks that come with AI and double down on critical thinking, context, and judgment to deliver quality decisionmaking. AI as an Accelerator, Not a Replacement AI is dramatically compressing the time required to execute product work. Tasks that once took months can now be completed in hours. As we discover every day, speed does not eliminate the need for thoughtful product management. John argues that it merely shifts where product managers can and should focus their energy. “As AI expedites the execution process,” John says, “it also allows us to automate the areas of our work where we really need to be involved in cognitive thinking, reasoning, and creativity.” The Hidden Risk: Bias in AI Decision-Making Large language models inherit the same cognitive biases found in human thinking, John adds. These biases influence not just outputs, but the reasoning behind decisions we make. “It’s not what the decision is or what the output is, it’s more about how the AI model arrived at it.” This distinction is critical for product teams. Without understanding how AI arrives at conclusions, teams risk introducing flawed logic into their products, especially in high-stakes areas like hiring, healthcare, and financial management. Monitoring AI: A New Responsibility for Product Teams To address these challenges, John launched BiasHawk – an AI platform designed to monitor and evaluate AI systems for cognitive bias. The goal is not just testing outputs, but continuously assessing decision quality over time. “We all understand that these systems are designed to evolve. They’re designed to change. They’re designed to drift. But who’s monitoring that to make sure that decision quality stays where it’s supposed to be.” As AI continues to evolve, the role of the product manager becomes even more critical — not less so. Execution may be faster, but judgment, context, and ethical responsibility remain firmly within our human domain. John Haggerty, in his own words: [06:50] AI is compressing execution time, allowing us to automate some of the tasks that we do as product professionals: cognitive thinking, reasoning, creativity. [10:22] There’re lots of really good AI tools out there right now, but what there isn’t out there is anything that tests the fairness of our decisionmaking. [16:04] Great. You’ve used AI to improve productivity by 20%. But what happens when that breaks? What if there’s bias and heuristics in these LLMs. Who’s catching that? [17:55] Critical AI systems have the same blind spots, the same bad habits, that we as humans have. And why not? They’re built off of the flawed content we created. [21:41] I don’t think a LLM could ever get depressed. But we have standard behavioral assessments that we could administer to an LLM — to find out where it falls with these biases and with the decision-making process it’s using. [27:40] As humans, we’re make mistakes. Because AIs are built on what we know, those same mistakes are being repeated. Now we have AI learning from AI, and those mistakes are being amplified. [30:59] The ‘why’ will always need to come from a human. At the end of it all, that’s what Product is. The post 185 / Confronting Cognitive Bias in AI Models, with John Haggerty appeared first on ITX Corp..
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    34 mins
  • 184 / Connecting Product Teams with Go-To-Market Outcomes, with Margie Agin

    184 / Connecting Product Teams with Go-To-Market Outcomes, with Margie Agin
    Mar 31 2026
    Margie Agin is a seasoned go-to-market advisor for B2B technology scale-ups. She brings deep expertise across digital marketing, IT, and cybersecurity. As Founder and Chief Strategist of Centerboard Marketing as well as a former leader at companies like Cisco and Blackboard, she has built a career translating complex technical products into effective market strategies. In this episode (which marks her second visit to Product Momentum), Margie’s message is clear: go-to-market (GTM) is not a one-time event or a siloed function – it is an ongoing, cross-functional system that must connect product teams and broader business goals. GTM: A Shared, Continuous Responsibility It’s time to redefine go-to-market as a shared, continuous responsibility across teams, Margie says. Product managers in particular often feel disconnected because their fellow stakeholders in the organization misunderstand go-to-market as either a launch event or solely a sales function. Margie reframes GTM as “a coordinated cross-functional engine that spans product, marketing, sales, customer success, and even finance.” It’s a perspective that challenges product teams to actively engage in downstream outcomes and collaborate beyond traditional boundaries. Business Context Drives Product Contribution Fundamental to making this critical connection between product team and business outcomes is embracing the product’s fit within the broader business and portfolio strategy. Margie reiterates a message shared by recent guests that product managers need to look beyond their individual product scope and consider how their work contributes to company-wide goals like growth, positioning, and revenue. “Think about your product within the context of the business and how it fits into the whole portfolio,” Margie urges. Know Your Targets: Clarity of Audience and Signals Improves Outcomes Rather than trying to boil the ocean by targeting broad customer segments, teams should focus on specific attributes and behaviors that indicate a strong fit. Defining a precise ideal customer profile and identifying meaningful signals of readiness bring a level of clarity to your message that enables more effective messaging, prioritization, and sales efficiency. “It [your target] can’t just be like, everybody that has money,” Margie says. “It has to be somebody with a defined problem and defined attributes – beyond just industry or size of company.” For product leaders, this reinforces the need to deeply understand customer context and bring that insight into go-to-market planning. In the Age of AI, a Strong Point of View Still Matters Finally, even as AI accelerates execution, it does not – indeed, can not – replace the original thinking and nuanced messaging. Teams must still define what makes their product unique and why it matters. AI can enhance delivery, Margie adds, but it cannot generate true insight or perspective. “The difficult part is always what the difficult part has always been, which is figuring out what you have to contribute to the conversation that is unique.” Margie Agin, in her own words: [04:23] When I think of go-to-market, I think one of the most important aspects is that it is connected across different teams. [08:22] Go-to-market is all about connecting the strategy to the execution to make sure everyone is on point with the strategy. [08:53] Product teams need to think about how their product fits into the context of the organization’s whole portfolio. [11:30] As a company matures, its go-to-market strategy lands in one of three buckets: problem-market fit, product-market fit, and platform-market fit. [19:29] We can’t try to boil the ocean and sell to everybody, right? Target customers can’t be ‘everybody who has money.’ Customers have to have a defined problem and some defined attributes, beyond just industry or size of company. [23:58] That type of deep, nuanced thinking…that human work…I don’t think at this point, is something that is solved by AI. [26:40] AI can execute a lot of work on your behalf, but only you know what ultimately you want the result to be. Andrew Knoblauch leads Sales, Partnerships, and Acquisitions at ITX. He believes the best technology partnerships start with genuine relationships, and that understanding a business deeply is what turns a software engagement into lasting value. Andrew connects organizations with technologists and product leaders while remaining invested in delivering strong business outcomes. The post 184 / Connecting Product Teams with Go-To-Market Outcomes, with Margie Agin appeared first on ITX Corp..
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    33 mins
  • 183 / Rich Mironov: Using ‘Money Stories’ To Communicate Real Business Impact

    183 / Rich Mironov: Using ‘Money Stories’ To Communicate Real Business Impact
    Mar 17 2026

    Product Momentum welcomes Rich Mironov back to the pod to help us drill down to the bottom line – literally. Rich is a Silicon Valley veteran and longtime product management advisor. He’s spent decades helping C-suite executives and product leaders connect their work to business outcomes. In this episode, Rich reinforces a single, powerful theme: product managers must translate their ideas into clear financial impact. It’s not enough to build great features – success comes from telling compelling “money stories” that resonate with executives and drive decisions.

    Here’s what we learned:

    Why Product Leaders Must Speak the Language of Money

    Rich makes no bones about the yawning communication gap between product teams and executives. Product managers focus on features, processes, and operating models – while executives focus on revenue and outcomes. As he explains, “Any sentence that comes out of the mouth of a product leader that doesn’t have a currency symbol in it is one that the rest of the executive team can’t hear and doesn’t care about.”

    As he reframes the role of product leadership, Rich explains that it’s not just about building the right thing – it’s about articulating how that thing makes money.

    The Power of Simple, Structured “Money Stories”

    At the core of Rich’s approach lies simplicity. He advocates for building “money stories” using just three numbers – two we know, one we estimate – to quantify potential impact. “A money story has no more than three numbers in it…two of the numbers you know, and one of them you’re going to reach into the air and make up or estimate.”

    This framework isn’t about precision, Rich explains. It’s about enabling better conversations. By introducing even rough estimates, product leaders can engage sales, marketing, and executives in meaningful dialogue. The goal is to create alignment around opportunity size and business value, and shift the focus from abstract ideas to tangible outcomes.

    From Features to Impact: Driving Better Product Decisions

    On the pod, we’ve been talking a lot lately about “impact.” Rich’s approach, covered concisely in his recent book Money Stories, also highlights a critical shift in mindset: product managers must own the financial performance of their products. Without that, they risk being sidelined from strategic decisions. “If you can’t vaguely explain how the thing you do makes money, you’re just a cog in the process.”

    This means knowing basics about your product – core metrics like units sold, pricing, and revenue – and using them to guide decisions. It also means prioritizing revenue-generating opportunities over less impactful work and being cautious with cost-saving narratives that may have real human consequences.

    Bottom line: product leaders who connect their work to measurable outcomes are the ones who influence strategy, secure investment, and drive meaningful results.

    Rich Mironov, in his own words:

    • [06:07] “Any sentence that comes out of the mouth of a CPO that doesn’t have a currency symbol in it is one that the rest of the executive team doesn’t care about.”
    • [06:48] “A money story has no more than three numbers in it… two of the numbers you know, and one of them you’re going to reach into the air and make up.”
    • [11:01] “It’s not important whether we get it accurate. It’s important that we build some consensus.”
    • [11:40] “If you can’t vaguely explain how the thing you do makes money, you’re just a cog in the process.”
    • [12:09] “PMs should socialize their plans with peers; say something like, ‘I know this is wrong, but let me walk you through my logic…’ and then sit back and listen.”
    • [24:18] “One thing I always recommend when socializing ideas: Bring a bucket of humility with you.”
    • [29:29] “AI is real. It’s gotten investments like we’ve never seen. But it’s all going to come crashing down soon. There’s no way to avoid it. There’s nowhere to hide.”

    The post 183 / Rich Mironov: Using ‘Money Stories’ To Communicate Real Business Impact appeared first on ITX Corp..
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    41 mins
  • 182 / How ‘Sense Shape Steer’ Helps UXers Design AI Solutions, with Bansi Mehta

    182 / How ‘Sense Shape Steer’ Helps UXers Design AI Solutions, with Bansi Mehta
    Mar 3 2026
    In this episode of Product Momentum, we’re joined by Bansi Mehta, founder and CEO of Koru UX Design, an enterprise healthcare UX agency supporting some of the US’s largest healthcare technology companies. We discussed the busy intersection of artificial intelligence, product management, and UX Design. Bansi’s Sense – Shape – Steer framework helps guide UX design teams as they integrate AI into their products – and avoid the trap of AI’s drive toward mediocrity that limits individual creativity and expertise. Here’s what we learned: Avoiding the Trap: AI Solutions’ Race to Mediocrity AI’s ability to rapidly generate hi-fi prototypes and voluminous content brings great benefit, but also significant risk. The risk manifests in mediocrity – i.e., solutions that drive to the mean. This sense of “good enough” stifles designer creativity and diminishes the quality – the Delight – of the final product. “The speed of AI makes it easier than ever to churn screens,” Bansi says. “But it’s designed to deliver to that average mean that allows us to say, ‘that works, that makes sense.’ And that’s really the trap….these days, there’s less patience in the industry for discovery and research.” Introducing the Sense – Shape – Steer Framework To combat this new reality, Bansi developed the Sense – Shape – Steer framework to help teams navigate the complexity of building AI-powered products. Sense. Understanding the Problem/Opportunity.“Sense is where you’re really creating that sense of what is worth solving,” Bansi explains. “It’s the intersection of what the user needs, what insights we have in terms of their challenges, and the opportunities that are present. But we mustn’t stop there. We then look to see what AI can do for us. And where we see the intersection, that’s the sweet spot.”Shape. Designing the AI-Enhanced User Experience.We emerge from the Sense step with rich insights into our user’s desired experience, Bansi continues. “And as we approach Shape, we do so with an emphasis on the kind of UX challenge that we are trying to solve – from the user’s perspective. Using a storyboard, we proceed frame by frame to define the user’s journey, the problem that we are trying to accomplish.”Steer. Implementing, Evaluating, and Iterating.The Steer step comes once you have built something and you launched, Bansi says. “This is where we define and clearly articulate our AI eval criteria that we’ve said are critical for product success,” Bansi adds. “I’ve seen products make it or break it depending on whether they got their AI evals right. It’s one thing to hypothesize that your solution will work. But it’s a completely different thing when you actually try to build sophisticated agentic AI layers where there’s multiple configurations and prompts.” Broader Insights, Future Outlook The conversation underscores the notion that while AI accelerates development and content generation, it also requires subject matter experts in UX and Product to demonstrate greater vigilance than ever to maintain quality and relevance. The Sense – Shape – Steer framework calls on product teams to think first about user needs before considering whether and how to integrate AI. Our episode with Bansi Mehta feels like the capstone conversation to recent episodes with Nesrine Changuel, Teresa Torres, and Oji Udezue, where we examined bringing Delight to the user experience, re-engaging Discovery in the development process, and adjusting to the Speed of today’s AI-driven development. The post 182 / How ‘Sense Shape Steer’ Helps UXers Design AI Solutions, with Bansi Mehta appeared first on ITX Corp..
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    32 mins
  • 181 / From IC to PM: Practical Insights for Effective Leadership, with Keith Lucas

    181 / From IC to PM: Practical Insights for Effective Leadership, with Keith Lucas
    Feb 17 2026

    Keith Lucas is a startup advisor, author, and leader who specializes in building high-impact teams. In this episode with Product Momentum, Keith delivers a master class on leadership, team building, culture, values, and motivation. Our conversation is especially relevant in the context of transitioning from a technical individual contributor to product team leader in high-tech organizations.

    Here’s what we learned:

    IC to Team Lead: Navigating the Mindset Shift

    The transition from hands-on IC to leader of a highly technical team requires a mindset shift from “me to we.” The transition requires an adjustment of priorities from solely outcomes-based to team health, inspiration, and mental well-being.

    “A simple trick I use, when I wake up every day my first thoughts are, is the team on a good path? Are they unblocked? Are they inspired and mentally healthy? Are they all in a good place to have impact? Knowing those things helps reduce friction on the team and increases the odds of our success.”

    Two ‘New Leader Archetypes’ – Overcoming Team Dysfunction

    Keith discusses two types of leaders who struggle in their new roles. The first is the hands-on leader who has fallen into the oxymoronic trap of trying to “micromanage at scale.” The other is the visionary talent-oriented leader whose eagerness to succeed leads to the team’s being focused on too many things. The hands-on person is just trying to get stuff done by being effective, efficient, Keith says, while the talent person is committed to autonomy and building a team that scales.

    The goal is to put both of those value sets together. For the hands-on leader, that means creating regular touch points with your team. For the talent-oriented leader, it’s about closing loops while showing the team how to go from vision to delivering real outcomes. “In both cases,” Keith adds, “use a regular cadence for when you get together to talk about progress, challenges, and course correction.” This approach creates the right kind of trust — a trust in the system that you have opportunities to contribute in a healthy way.

    Value-Based Culture: The Foundation of Decisionmaking

    Keith thinks about culture as “the team’s operating system.” And the foundation of that operating system is the team’s values — i.e., their standards of behavior.

    “The team’s values are really the foundation of the operating system,” Keith says. “If the system is to be reinforced, then decisions about who gets hired, promoted, and retained must be informed by those values.” If that’s not happening, Keith adds, you end up with a culture that may be codified, but never truly realized.

    Here’s some more key takeaways:

    • 04:58 – Moving from chief IC to chief team builder
    • 07:32 – Micromanaging at scale is an oxymoron
    • 13:08 – Values: embrace them, socialize them, apply them
    • 18:07 – Vision Doc: The anti-job description
    • 20:21 – Start with Goals; Structure will follow

    As the author of Impact: How to Inspire, Align, and Amplify Innovative Teams, Keith Lucas distills years of experience at the intersection of data, storytelling, and strategy into a practical framework that helps leaders move from player/coach to true team builder while avoiding common scaling pitfalls like diminishing impact, productivity loss, culture dilution, and disempowerment.

    The post 181 / From IC to PM: Practical Insights for Effective Leadership, with Keith Lucas appeared first on ITX Corp..
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    34 mins
  • 180 / Oji Udezue: The Renaissance PM – Core Skills for Today’s AI-Driven World

    180 / Oji Udezue: The Renaissance PM – Core Skills for Today’s AI-Driven World
    Feb 3 2026

    The Product Momentum team first met Oji Udezue following his keynote at INDUSTRY 2025. And we just knew we had to have him on the pod. Oji is a highly skilled product leader whose CV includes companies like Calendly, Atlassian, and Microsoft. In addition, he co-authored (with wife, Ezinne Udezue) Building Rocket Ships, Product Management for High-Growth Companies a manual for product leaders, product managers, and executives who want to build faster, better, and more profitably (raise your hand if that describes you!).

    In this episode, we begin broadly by discussing the evolving role of product management in the era of AI. We then pivot quickly, drilling into some of the new challenges that require today’s product leaders to:

    • Readjust to the accelerated pace of product development in today’s AI-empowered world (the three-speed problem),
    • Re-emphasize product management’s core principles that remain constant, and
    • Reconsider what counts as essential skills for today’s product manager.

    AI’s Impact and the Three-Speed Problem

    Companies do three things to build great technology products, Oji says: customer science, construction/development, and go-to-market. Each step on this cycle moves at its own pace. Before AI, engineering speed was the process bottleneck. But with AI-driven automation, construction has become much faster, creating new challenges in synchronizing these three phases.

    “We’re all going to spend a lot of time balancing that equation,” Oji adds, “finding the practices, the team structure, the team ratios, the new AI tools that help us keep this thing fast but then speed up customer science and GTM.“

    Essential Skills for Today’s ‘Renaissance PM’

    The AI transformation calls on product managers to add new arrows to their quiver of skills – e.g., curiosity, humility, agency among them. In the same way we transitioned from a pre-internet to internet environment, Oji adds, AI “requires brand new thinking.”

    But the old skills still apply: “These are worth bringing up because a lot of PMs don’t have them: communication, creativity, the ability to ship, and leadership – being the kind of person people want to follow – all of that has to do with judgment. The role is evolving into that of a “renaissance PM” who blends traditional skills with new AI-related capabilities.

    Evolution of the PM Role

    Has the PM role evolved so much that the skills required to perform it are now preeminent to the role itself? Is that where AI is taking us?

    “I’ve always thought the skills…the mindset…was way more important,” Oji offers. “The title just gives us a way to put it in a box. The title is nothing without the skills. That’s why I wrote the book. Because I want more people to have the skillsets” required to succeed in this new world order.

    The post 180 / Oji Udezue: The Renaissance PM – Core Skills for Today’s AI-Driven World appeared first on ITX Corp..
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    42 mins