Special Edition: The AI Masterclass for Product Leaders

The pressure on Product Leaders to integrate AI is immense. But where do you start? How do you implement it? And how do you know if it's even working?In this special compilation episode, Christian and Jonas combine their essential 3-part AI trilogy into one definitive guide. They cut through the hype to give you a practical, step-by-step playbook for turning AI buzz into real product value.In this episode, you will learn:Part 1: Where to StartWhy the "we need AI" panic is the wrong approach.How to map your existing customer use cases (automation, quality, decision support) to potential AI solutions.The importance of starting small, iterating, and validating, even while allowing for "wild experimentation."Part 2: How to ImplementThe four fundamental pathways for AI implementation: Build, Rent, Borrow, and Acquire.A practical framework for deciding which path is right based on speed, cost, control, and strategic importance.Part 3: How to Measure SuccessHow to define success metrics before you write a single line of code.The critical art of bridging the "engine room" scorecard (technical metrics like precision and recall) with the "use case" scorecard (business metrics your stakeholders care about).How to use iterative milestones and transparent communication to manage stakeholders and build trust.

Over the past few weeks on The 10-Minute Product Podcast, we’ve explored how product leaders can approach AI — from identifying the right use cases to implementing solutions effectively.In this final episode of our AI trilogy, we bring it all together:👉 How do you actually measure success with AI in your product portfolio?Here are some highlights from our discussion:📏 Define success earlyBefore you build anything, decide how you’ll measure success. What does “better” look like for your use case — faster, more accurate, higher conversion?Don’t wait to tack on metrics later. Make measurement part of your design phase.⚙️ Bridge two scorecardsEvery AI system has a technical scorecard (precision, recall, drift) and a use case scorecard (user outcomes, business value).Success comes from connecting the two — aligning what the model optimizes with what your customers actually care about.🧭 Communicate and engageAI is iterative and uncertain. The best product leaders turn that uncertainty into a story — sharing progress, setbacks, and insights transparently so stakeholders stay engaged and confident in the journey.🏁 Think milestones, not moonshotsInstead of betting big on year-long AI programs, break your work into small, measurable wins. Each milestone builds trust, learning, and momentum across the organization.As we discussed in the episode — everything is academic until a user clicks a button and finds value.

Your CEO just said, "We need 10 AI initiatives by Monday!." Now what? The pressure is on product leaders  to integrate AI into our products, but the path forward is anything but clear. Making the wrong choice can cost you in development time or customer value.In this episode, we break down the four fundamental pathways for AI implementation. We'll help you understand when to license a third-party API versus when to build a model from scratch, and what the less-known "Borrow" and "Acquire" options truly entail.In this episode, you will learn:Acquire: When does the step of acquiring an entire AI company become the most strategic move?Build: Internalising the knowledge and AI capabilities inhouse and consequences in lead time that you need to considerRent: When to go for the AI-as-a-Service from a 3rd party vendor.Borrow: The power of leveraging partnerships as a way to move you forward on the AI agenda.Decision Framework: A practical guide to help your team choose the right path based on speed, cost, control, and strategic importance.This episode is essential listening for CTOs and Product Leaders tasked with turning the hype around AI into real product value.

Everyone is talking about AI, but where do you actually start? The pressure on product leaders to "just add AI" can lead to costly mistakes and dead-end projects.In a trilogy on AI for product leaders, we start with the most important thing: use cases. AI is not a magic solution; it's a new tool for solving existing customer needs.Where should you start?Start by mapping your current use cases. What value do you deliver to customers today? AI doesn't change these needs, but it can change how you solve them. A company's use cases typically fall into two categories:Automation: Helping users complete tasks faster (e.g., time savings).Quality and Decision-Making: Ensuring quality or providing the user with data to make better decisions.The Journey to AIAI implementation is a maturity journey. Start simple and iterate. A global retailer began with a simple analysis of where products sold best and ended up with an advanced solution for hyperlocal marketing based on store data. Product methods like validation and user feedback are still essential.It is crucial to analyze existing use cases rather than starting "AI initiatives" without a clear purpose. This ensures faster results and better anchoring in the organization.Make room for experimentsIn addition to focusing on existing needs, it's important to give teams the freedom to experiment. The "crazy" ideas can turn out to be the biggest products of the future. AI development is unpredictable and requires short feedback loops.This was an overview of how to get started with AI by focusing on use cases. In the next episode, we will discuss "build vs. buy" and the implementation itself.

The true test of leadership isn't avoiding mistakes—it's how you respond when they happen. This episode is a guide to leading yourself through those critical moments. Through their own stories of fumbles and flawed decisions, Jonas and Christian show how self-reflection and transparency can transform a simple error into your most valuable experience.Episode summary:In product leadership, making mistakes is an unavoidable part of taking risks. This episode explores the idea that the true measure of a leader isn't avoiding errors, but how they respond to them. The hosts discuss different types of mistakes—from simple oversights to avoiding necessary conflict—and offer a framework for handling them: stop, reflect, plan, and, most importantly, communicate transparently. Sharing learnings builds trust and transforms errors into invaluable experience, unlike "happy path" work.Through personal 'war stories,' they explore the painful consequences of delaying tough people decisions, ignoring fundamental disagreements with a boss for months, and overlooking technical 'data drift' in a machine learning system.Ultimately, the conversation emphasizes that leaders must model this behavior. By openly discussing their own fumbles, they create a culture where it's safe for teams to fail and learn. The key takeaway is to embrace mistakes and deal with them constructively, as they are the primary fuel for career progression and leadership evolution.

In this episode of the 10-Minute Product Podcast, we’re diving into a concept that might just change how you lead: Product as a Service.Think your job is to “own the roadmap”? Think again.Think being the “CEO of the product” still flies in 2025? Yikes.We break down:🔥 Why being precious about “your” product is a fast track to isolation.🧩 How great product teams serve the whole org (without being doormats).💥 What happens when you stop dictating and start facilitating.📈 How to show value like a boss — with metrics, not just vibes.😬 And yes, what to do when your idea is the hill you think you want to die on.If you’ve ever clashed with stakeholders, been ghosted by sales, or wondered why no one understands what product actually does… this one’s for you.👉 Like, comment, and subscribe — unless you prefer working in a vacuum.

Customer segmentation is difficult. Some now obvious things apply to many people, such as sending emails or scheduling calendar invites. Some things apply to smaller groups, say bookkeeping for small businesses. As you dive deeper, segmenting users by relatively obvious dimensions such as business vertical, geography, regulatory framework and other large filtering only goes so far. What methods can you apply to dive deeper? Transcript: Welcome back to the 10 Minute Product Podcast! Today’s episode is all about customer segmentation. Well, it helps identify groups of customers with shared behaviors or needs. It allows you to sell software repeatedly rather than as a one-off service. With segmentation, you can build for a broader audience, making sales more predictable and scalable. Exactly. And it’s not just about selling—it’s also about upselling and feature adoption. Knowing your best customers and understanding their behavior is key to driving growth. So, how do you go about it? First, your organization must have honest discussions, just like prioritization or hiring. It may expose gaps in your understanding—like realizing you don’t know exactly why people bought your software. But that’s valuable insight. Then, it depends on whether you're B2C or B2B. Different frameworks work for different cases. The key is exploring what fits your business best. Agreed. Gaining insights into customer behavior is eye-opening for both sales and product teams. Segmentation helps define what a “good” customer looks like—someone who spends money, adopts features, upgrades, or refers others. The goal is to classify customers: High-value customers who engage deeply with your product A middle segment with potential for growth Low-engagement customers requiring re-engagement strategies There are also external segmentation factors, like regulatory constraints or infrastructure. For instance, launching in Germany means supporting specific payment systems. So, what types of segmentation exist? You can segment by country, language, industry, or product use cases. But the key question is: Who is your ideal customer? A great example is LinkedIn. Free users get minimal attention compared to recruiters, who are paying customers. This strategic segmentation drives LinkedIn’s product decisions. Do you have any examples? Yes! At Google, we studied the accounting industry’s advertising behavior. Dutch accountants monetized well, but Nordic accountants didn’t. The reason? Nordic accountants lacked websites. We solved this by helping them establish a digital presence. This created a new customer segment rather than just targeting existing ones. That’s clever—you didn’t just segment customers, you created them! Another case: I worked on an ad platform where industries had different advertising needs. Traditional segmentation didn’t work, so we applied the “Jobs to Be Done” framework. Instead of grouping by industry, we grouped by shared advertising goals. This approach was far more effective. Great point. Segmentation isn’t just for product teams—it impacts sales, customer success, and marketing. Understanding customer pain points enables more relevant sales pitches and higher conversions. Yet, companies often resist segmentation. Reasons include lack of data, uncertainty about where to start, or time constraints. Have you encountered this? Absolutely. The key is to approach it in stages. Start small, find quick wins, and demonstrate impact. Once you show results, teams will buy in. Agreed. Just get started. Don’t overanalyze—start with available data. Sales and customer success teams interact with customers daily. Talk to them, join calls, and gather insights. Strong advice. Well, that wraps up our episode on customer segmentation! If you found this valuable, please like, review, and share your thoughts. Got any product or growth blockers? Let us know, and we might cover them in a future episode. Thanks for listening, and see you next time!

In our latest episode of the 10-Minute Product Podcast, we unpack essential strategies for aspiring Chief Product Officers during interviews. Discover why securing the right mandate is crucial for success—and learn the questions to ask to uncover organizational dynamics, clear mandates, and potential pitfalls. From probing team alignment to spotting red flags in company culture, this episode guides you to make informed decisions and set the stage for impactful leadership. Don’t just land the job; ensure it’s the right one for you!

The role of a product leader is to have a maximum impact through the Product organisation - and this means pushing back on the high volume of often conflicting priorities from stakeholders and customers which will tie up your roadmap and resources that will distract you without end. Saying NO constructively is a hard skill to master without upsetting stakeholders and team - all the while they loose trust in your strategy. It sounds simple but anyone who has been in this position has learnt fast how difficult this is to navigate. Keeping a steady focus and trust in the impact over time is incredibly hard in dynamic environments.  In this episode of The 10-Minute Product Podcast we tackle this dilemma and provide hands on pointers to how you can navigate it successfully. We also share cases from our own experience which you can apply in your own role as a product leader.

What career advice would you give a younger version of yourself? In this episode we will give the pointers from the experience we have gained from 20 years in Product Management.  We all know the feeling; our industry is constantly changing and we are under pressure to always adapt our skills and knowledge to stay relevant. Just in the past 2 years, the global stagnation and layoffs in the tech industry has created a super-competitive situation for the prized positions. And GenAI is now writing the PRDs! So is there an approach to follow to stay up to date, be relevant and re-invent yourself? Please follow us, as we travel 20 years back in time to younger versions of Christian and Jonas and give them the most important advice we have learned during our careers.