The 3Ps Framework (for fixing People, Product & Process)

In this two-part compilation, Christian and Jonas tackle one of the most common and least honestly discussed challenges in product leadership — landing in an organisation where something is fundamentally off, and figuring out what to do about it.Part one is about diagnosis. Using a simple framework of three Ps — People, Product and Process — they walk through how to read the symptoms of a dysfunctional organisation, why interviewing across all levels matters more than any onboarding document, and how to bring your stakeholders along on the exploration journey rather than surprising them with a revolution later.Part two is about the fix. Why starting small with one team beats announcing sweeping change, how to run hard structural decisions quietly through leadership before they go anywhere near the wider organisation, and why the sequence of changes matters as much as the changes themselves.When you join a broken organisation, you are not doing product management anymore. You are doing change management. The sooner you pick up that playbook, the better your chances of actually making something better.

Product management is your craft. But walking into a broken organisation? That's a change management exercise. In this episode, Christian and Jonas make the case that product leaders need to step outside the product playbook and borrow from change management, organisational design, and leadership theory. The conversation covers the dangers of sparking a "revolution," why you should always run hard structural changes quietly through leadership before going wide, how to sequence people, process, and product changes so they land and stick — and how to stay standing when the headwinds come.

This will happen to everyone at some point in their career; joining an organisation where something is ‘wonky’. The trick is how to deal with it. In this episode, Christian and Jonas break down the 3 Ps framework — People, Product and Process — and walk you through the exact method for diagnosing what's really wrong when you land in a new organisation.You'll learn:Why being subtle when you join a new team is the biggest mistake you can makeHow to line up the right interviews from day one — and what to listen forThe gap between what your internal team believes and what customers actually experience — and why that gap is your diagnosisHow to spot People, Product and Process problems fast using real symptomsWhy KPIs that don't measure your actual goals are worse than no KPIs at allIf you've ever joined a team and felt something was off but couldn't put your finger on it - this one's for you.

In this episode of the *10-Minute Product Podcast*, we build on last week's topic of leading effective product reviews with executive stakeholders. This time, we zoom out and discuss what happens *outside* the review meeting: how to ensure your product strategy connects meaningfully with your company's strategy.Jonas and Christian explore why “product island” is such a common trap and how misalignment across strategy layers — from company vision to product roadmap — creates disconnects in communication, prioritization, and ultimately, value delivery.We share a practical case where a company struggled for months to build a coherent roadmap. The breakthrough came not from reprioritizing features, but from aligning executives on the *criteria* for prioritization. Once shared outcomes were defined, everything clicked into place, enabling consistent strategic decision-making.We also discuss:* Why measurable outcomes are the “glue” between company goals and product strategy* How product teams can proactively support a company in clarifying its own strategic metrics* How outcome-driven strategy empowers teams and prevents “feature factory” dynamics* Practical ways to connect your roadmap activities to company goals such as LTV, loyalty, or funnel improvements* How metrics create decision points and momentum rather than endless debateThe takeaway: Avoid running your product strategy in isolation. Lean in, anchor everything in measurable outcomes, and build a strong bridge between product and company strategy. This unlocks better communication, better prioritization, and better results.If you enjoyed this conversation, follow the podcast, leave feedback, and listen to more episodes!

In this episode, Christian and Jonas dig into a universal product leadership challenge: how do you translate complex product work into clear, high-impact decision-making at the executive level?We explore why sharing detailed backlogs, plans, and spreadsheets in Product Reviews often derails discussions — and how shifting perspective from tasks to signals enables better alignment, trust, and outcomes.Key topics include:Why more detail = more opinions and slower decisionsTurning complexity into clear signals that show progressLinking commitments to measurable business impactRecognizing when requests for detail actually signal mistrustHow to elevate roadmap conversations to strategic outcomes

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.