To move toward your ultimate goal, you need some mid-term steps called Product Goals. Here, I show you how to effectively create it with the power of AI.

Multi-product portfolio governance is difficult because products carry their own history, pressures, and priorities. Misalignment, trust gaps, capacity myths, and unresolved dependencies intensify the challenge. Success depends on deliberate alignment practices, shared understanding, clear boundaries, and leadership that creates the conditions for honest, system-level decision making.

En un entorno complejo con incertidumbre y ansiedad por resultados en tiempos cortos, los líderes necesitan empoderar, delegar, distribuir el poder de la toma de decisiones. Pero no solo se trata de delegar de manera instantánea, sino de construir una cultura, de cambiar mentalidad y, sobre todo, de practicar la confianza para lograr que a quienes se delega sientan el apoyo y respaldo para decidir. En el siguiente post muestro algunas ideas sobre como enfocarnos en el empoderamiento.

are always changing. But we don’t need a better plan - we need better ways to learn, and we need to keep our options open.

Prior to blaming the Scrum Master, organisations must ask themselves, do we value a culture where truth can be shared without retribution? Do we have clear guidelines in place, or have we shifted the ambiguity and the risk to the Scrum Master? Are we actually prepared to face the uncomfortable, that weak and outdated assumptions and leadership practices are exposed? No amount of Scrum training, SAFe certification, or the implementation of agile tools will help an organisation that is blind to the truth. No framework will fill the void left by the lack of leadership.

Scrum often isn’t what fails to scale, portfolio design does. Teams can run a good Scrum and still be slow because the real constraint sits upstream in funding, governance, and decision rights. Your product portfolio type determines which dependencies help you win and which ones quietly slow you down. In a loosely coupled portfolio (different strategies/customers, limited reuse), success comes from autonomy, local decision-making, and minimal coupling. In a strongly coupled portfolio, success comes from intentional integration—the right dependencies, supported by governance and funding. So the goal isn’t “reduce dependencies.” The goal is: design the right dependencies for your portfolio, strengthen the ones that create advantage, and remove the ones that don’t.

Business portfolio cohesion is a strategic choice that shapes organizational architecture. Four archetypes—from Single Integrated Business to Holding—affect structure, processes, and culture differently. The core tradeoff: integration delivers synergies and scale, but sacrifices local agility. A diagnostic tool helps verify alignment between strategy, operating model, and real centralization/decentralization effects. There's no "right" portfolio type—only the right fit between architecture and operating model.

in diesem Artikel teilt PST Simon Flossmann drei Fragen, die sich jedes Scrum Team stellen sollte, wenn ihr Product Backlog mehr als 100 Einträge hat.

A practical way to leverage AI to increase the Daily Scrum effectiveness.

KI-Agenten versprechen schon seit langem Produktivitätssteigerungen, aber bisher verlangten sie Programmierkenntnisse, die den meisten agilen Praktikern fehlen oder die sie nicht beherrschen. In diesem Artikel teile ich meine ersten Eindrücke darüber, wie Claude Cowork diese Barriere beseitigt.

"Technical Debt" is a big topic in the Professional Scrum. This article addresses a specific new pain point: AI generates code fast (increasing Velocity), but creates massive maintenance debt. This warns Scrum Teams against false velocity.

Anthropicの「Claude Cowork」は、ユーザー行動の観察から生まれ、わずか10〜14日でリリースされたAIエージェント型ツールです。 生成AIによって開発コストが下がる一方、ボトルネックは「どう作るか」から「何を作るべきか」へ移っています。 その結果、プロダクト判断・意思決定・実験スピードに強い組織と弱い組織の差はさらに広がります。 今後は、文化・構造・リーダーシップを含めた“変化に強い組織づくり”がこれまで以上に重要になります。

Anthropic's “Claude Cowork” is an AI agent-based tool born from observing user behavior and released in just 10 to 14 days. While generative AI reduces development costs, the bottleneck has shifted from “how to build” to “what to build.” As a result, the gap between organizations strong and weak in making sound product-related decision, and and running experimentations at speed, will widen further. Going forward, building resilient organizations—encompassing culture, structure, ability to learn and leadership—will be more critical than ever.

Generative AI removes the natural constraint that expensive engineers imposed on software development. When building costs almost nothing, the question shifts from “can we build it?” to “should we build it?”

Modern org charts were built for slow, one-way telegraph communication. Today's instant, multi-directional flow turns hierarchy into bottlenecks - slowing decisions, diluting insight, and killing innovation.

Using the AQAL model provides a sophisticated framework for Scrum Teams to diagnose why a team followed the rules of Scrum but still failed in the delivery.

AI has turned code ownership from a theoretical concern into a practical business risk. Developers assume they own AI generated software because they guided the process and shipped the product, but copyright law depends on human authorship, and much of that code may not qualify. This usually does not matter until money is involved, when investors, buyers, or courts require proof of ownership. AI makes it faster than ever to build software, and just as easy to build something valuable that you do not actually own.

If you drive your car without a destination, you are NOWHERE at the end of the day. The Sprint Goal is the destination of your Sprint trip. You should learn how to effectively create it.

Scrum events don’t work because they’re scheduled. They work because they create transparency, inspection, and adaptation. If nothing changes after your Sprint Review, Daily Scrum, or Retrospective, Scrum isn’t broken — it’s being ignored.

In diesem Blog Artikel beschreibt Mark Rehberg, wie die Idee der Vision aus der Produktentwicklung auf die Zusammenarbeit in Scrum Teams übertragen werden kann. Er zeigt, dass auch Teamarbeit als „Produkt“ verstanden werden darf, das sich bewusst und schrittweise weiterentwickelt.

If you don't use the Definition of Done in your Scrum Team, read this blog.

The "Definition of Done" (DoD) is a core Scrum element. As teams integrate AI agents (like Devin or Cursor) into the Sprint, the DoD must evolve to include "hallucination checks" and "bias testing." This is a highly relevant, practical guide for modern Scrum Teams.

Das A3-Rahmenwerk kategorisiert die KI-Delegation, bevor Sie diese veranlassen: Assist (KI entwirft, Sie überprüfen und entscheiden aktiv), Automate (KI führt nach expliziten Regeln und Prüfungskadenzen aus) oder Avoid (bleibt vollständig beim Menschen, wenn ein Versagen das Vertrauen oder eine Beziehung beschädigen würde).

How often have you heard the word Empiricism in connection with Scrum? I believe almost every time someone says Scrum, they do bring up Empiricism.

A human passes The David Sabine Test when others can clearly tell they’re interacting with a human. A human fails the test when they cannot be distinguished from a computer.

Self-managing teams with specialists and experts often fail quietly. The problem is not expertise. In this blog, PST Robb Pieper explains what actually breaks self-management and why most leaders miss it.

AI agents have long promised productivity gains, but until now, they demanded coding skills that most agile practitioners lack or are uncomfortable with. In this article, I share my first impressions on how Claude Cowork removes that barrier.

Free up your time to focus more on the human-centric and strategic activities as a Product Pro by leveraging AI Agents.

In pursuit of efficiency and improved customer outcomes, many firms are implementing a Product Operating Model (POM). Books such as Transformed by Marty Cagan have created a cult-like wave of POM hype and associated tools, products, and services. The POM wave is sweeping through the business landscape. But is a Product Operating Model right for you?

O Scrum falha quando é tratado como algo exclusivo das equipas de desenvolvimento. Sem mudança de mentalidade na liderança e na gestão, o quadro de trabalho transforma-se em controlo, métricas de output e trabalho mecanizado. Scrum não é um conjunto de rituais para equipas, é uma mudança organizacional. Quando só uma parte da organização muda, o sistema inteiro empurra tudo de volta ao modelo antigo.

This blog explains how Product Goals set strategic direction while OKRs make progress measurable through behaviour focused Key Results. It shows how both tools support evidence based decisions, prevent output driven thinking, and help Scrum Teams stay aligned, learn faster, and deliver value with clearer intent.

What will you get if you invest your time and money in learning AI?! Let's dissect it.

I'm sure you've all heard this one: If a tree falls in the woods and no one is around to hear it, does it make a sound? It seems to me that a lot of organizations lately have changed this question to: If you don’t track your work with a ticket, did it really happen?

Diferentes autores e abordagens falam sobre Product Operating Models de formas distintas, mas todos buscam resolver o mesmo desafio: conectar estratégia, times e aprendizado em ambientes complexos. Este artigo explora onde esses modelos convergem e por que ciclos de valor se tornaram um elemento essencial dessa discussão.

In diesem Artikel gibt PST Simon Flossmann 3 Gründe, warum Scrum Master sich zum Produkt-Coach entwickeln sollten

With your AI transformation, others perceive you differently in your professional network, which opens new doorways for you. But how?!

Stop asking 'Can AI do this?' Start asking 'Should AI do this?'

AI forces organizations to align machine speed with governance and funding. In doing so, it structurally closes Product Ownership's authority gap - distributed decisions, adaptive governance, and outcome funding become unavoidable.

Scrum doesn’t just define events—it places them *inside* a Sprint for a reason. The Sprint is the container that gives coherence, continuity, and consequence to inspection and adaptation. Without it, Scrum Events become disconnected conversations instead of a learning system.

In diesem Blog Artikel beschreibt Mark Rehberg, dass komplexe Probleme keine einfachen Lösungen haben. Scrum nimmt diese Komplexität nicht weg, sondern hilft dabei, sie sichtbar zu machen und Schritt für Schritt damit umzugehen. Scrum ist keine Abkürzung, sondern ein Werkzeug zum Lernen und zur kontinuierlichen Verbesserung.

RSGT2026にて、「EBM実践のカタ」として、エビデンスベースドマネジメント（EBM）を実践する際に気にかけるべき実践的な問いのカタを提案しました。ここではその詳細を解説します。

Teams across digital delivery keep running into the same ten traps, not through incompetence but through comforting untruths that quietly undermine performance. From believing more people will speed things up to treating roadmaps as commitments or assuming AI will magically fix dysfunction, these lies shape behaviour and slow progress. Real improvement starts with recognising the patterns, challenging convenient assumptions, and rebuilding product delivery on evidence, focus, and honest reflection.

Somewhere along the way, when "Agile Consultants" began rebranding the Scrum Master as exclusively a "Coach," the role became dangerously hands-off. The result? A generation of Scrum Masters who are disconnected from the reality of product development.

This case study examines through an Evidence-Based Management (EBM) lens what happens when teams operate on rebuilt technical foundations owned by their investor.

Learn how to gain entry-level Scrum Master experience, build credibility, and prove value without waiting for the job title in this latest post with PST Robb Pieper.

Temporary fixes are supposed to be temporary. That's why Technical Debt should be on the Product Owner's radar.

In my practice, I get the chance to talk to a lot of different individuals from many organizations. Here are some of the things that really stood out to me about 2025.

AI changes what work is visible. It does not change what matters in work.

In diesem Artikel fasst PST Simon Flossmann zusammen, was im Alltag für Scrum Master wirklich zählt.

AI is closing the Product Owner data gap by accident. Revenue accountability finally meets real-time access - but decision rights, funding, and governance still lag. Dashboards don't equal authority.