Your Agile events aren’t failing because people lack training. They’re failing because your organization adopted the rituals while rejecting the transparency, trust, and adaptation that make them work. And often, the dysfunction of mechanical ceremonies isn’t a bug. It’s a feature.
The public Scrum training market is shrinking, while demand for self-paced AI and Product courses is growing among agile practitioners. Consequently, I will shift toward online courses on AI for Agile and Product Operating Models in 2026. And I will rejuvenate the Agile Camp Berlin in the summer of 2026. Learn more about what is in the pipeline.
Peter Yang, a renowned product leader, argues that AI will split product roles into two groups: Generalists who can prototype end-to-end with AI, and specialists in the top 5% of their fields. Everyone else in the dangerous middle risks being squeezed.
How does this apply to agile practitioners: Scrum Masters, Product Owners, Agile Coaches, and transformation leads? It does, with important nuances.
The Mastering AI with the AI 4 Agile Online Course launches this week, and I am proud that I avoided another delay. Scope creep happened despite my supposed expertise in preventing exactly that. The course expanded from a simple prompt collection to over 8 hours of video, custom GPTs, and materials that I’ll apparently continue to update indefinitely, as I’m still not satisfied that it’s comprehensive enough. (Also, the field is advancing so rapidly.)
At least the $129 lifetime access means you will benefit from my urge to fight my imposter syndrome with perfectionism and from my inability to call a project “done.” I guess we are in for the long term. 🙂
🎓 🛒 The AI 4 Agile Online Course Is Available — Join Now at $ 129 until October 20, 2025: AI 4 Agile — Master AI Integration for Agile Practitioners.
“Good Enough Agile” is ending as AI automates mere ceremonial tasks and Product Operating Models demand outcome-focused teams. Agile professionals must evolve from process facilitators to strategic product thinkers or risk obsolescence as organizations adopt AI-native approaches that embody Agile values without ritual overhead.
Recent research shows AI isn’t just another tool—it’s a “cybernetic teammate” that enhances agile work. A Harvard Business School study of 776 professionals found individuals using AI matched the performance of human teams, broke down expertise silos, and experienced more positive emotions during work. For agile practitioners, the choice isn’t between humans or AI but between being AI-augmented or falling behind those who are. The cost of experimentation is low; the potential career advantage, on the other hand, is substantial. A reason to embrace generative AI in Agile?
Agile teams have always sought ways to work smarter without compromising their principles. Many have begun experimenting with new technologies, frameworks, or practices to enhance their way of working. Still, they often struggle to get relevant, actionable results that address their specific challenges. Regarding generative AI, there is a better way for agile practitioners than reinventing the wheel team by team—the Agile Prompt Engineering Framework.
Learn why it solves the challenge: a structured approach to prompting AI models designed specifically for agile practitioners who want to leverage this technology as a powerful ally in their journey.
ChatGPT can be an excellent tool for those who know how to create prompts. The simplest form of prompting ChatGPT is to feed it the task and ask for results. However, this approach is unlikely to trigger the best response from the model.
Instead, invest more time in prompt engineering, and provide ChatGPT with a better context of the situation, desired outcomes, data, constraints, etc. The following article offers a primer to creating ChatGPT prompts for Scrum practitioners to get you started running. You will learn:
In this comprehensive Scrum Master Interview guide, we delve into 83 critical questions that can help distinguish genuine Scrum Masters from pretenders during interviews. We designed this selection to evaluate the candidates’ theoretical knowledge, practical experience, and ability to apply general Scrum and “Agile “principles effectively in real-world scenarios—as outlined in the Scrum Guide or the Agile Manifesto. Ideal for hiring managers, HR professionals, and future Scrum teammates, this guide provides a toolkit to ensure that your next Scrum Master hire is truly qualified, enhancing your team’s agility and productivity.
If you are a Scrum Master currently looking for a new position, please check out the “Preparing for Your Scrum Master Interview as a Candidate” section below.
So far, this Scrum Master interview guide has been downloaded more than 25,000 times.
If you are looking to fill a position for a Product Owner in your organization, you may find the following 82 interview questions useful to identify the right candidate. They are derived from my sixteen years of practical experience with XP and Scrum, serving both as Product Owner and Scrum Master and interviewing dozens of Product Owner candidates on behalf of my clients.
So far, this Product Owner interview guide has been downloaded more than 10,000 times.
Age-of-Product.com’s parent company — Berlin Product People GmbH — offers Scrum training classes authorized by Scrum.org, Liberating Structures workshops, and hybrid training of Professional Scrum and Liberating Structures. The training classes are offered both in English and German.
Check out the upcoming timetable of training classes, workshops, meetups, and other events below and join your peers.
Welcome to the 522nd edition of the Food for Agile Thought newsletter, shared with 35,812 peers. This week, Gary Marcus questions the viability of large language models, citing unresolved flaws such as hallucinations and weak reasoning — Quo Vadis AI? Teresa Torres and Petra Wille reflect on AI’s role in user interviews, warning that tech cannot replace skilled human insight, while Peter Yang sees the PM role in AI-native firms shifting toward builders who align quickly. Also, OpenRouter’s massive token data analysis reveals rising agentic use and open models, and Willem-Jan Ageling dissects why many corporate transformations still stall.
Next, Dave Baines urges product managers to stop hiding technical work and instead align it through transparency and joint prioritization. Chris Jones and Marty Cagan remind stakeholders that their job is not to demand features but to enable outcome-driven problem solving. Saffron Huang’s team finds Claude changes engineering workflows at Anthropic and raises career questions. Also, Teresa Torres shares 50 AI use cases from her own process, and Eric Barker recommends strategy over emotion when dealing with difficult coworkers.
Then, Jing Hu questions the true ROI of AI investments, citing McKinsey data showing limited gains and weak agent adoption. Mike Brock calls AGI from LLMs a flawed idea dressed as progress. Mike Fisher warns that chasing velocity without slack leads to chaos, Martin Eriksson urges teams to simplify decisions through focus and consent, and Andi Roberts challenges Tuckman’s model. Finally, John Cutler explains why tools fail when they don’t tackle underlying behavioral constraints.
Welcome to the 521st edition of the Food for Agile Thought newsletter, shared with 35,803 peers. This week, Addy Osmani challenges engineers to sharpen critical thinking using a structured questioning approach to stay focused in AI-enhanced workflows. David Pereira cautions product managers against chasing AI tools at the expense of core skills like decision-making and alignment, and Martin Casado shares hard lessons from building new markets, from pricing mistakes to scaling traps. Grant Harvey recaps Ilya Sutskever’s view that scaling has peaked. Meanwhile, the 18th State of Agile Report signals a return to outcome-driven agility.
Next, Itamar Gilad outlines four product discovery models that balance control, creativity, and evidence, while Teresa Torres and Petra Wille explore how emotional recovery supports resilience in product teams. Simon Willison evaluates Claude Opus 4.5, noting its strength but also the blurring lines between top models. Johanna Rothman links flow metrics to culture change through storytelling, and Andi Roberts presents a hands-on framework to help teams align mindset, mechanics, and routines for better performance.
Then, Stuart Williams explains how AI shifts critical thinking toward context and judgment. Zvi Mowshowitz critiques Gemini 3 Pro’s confident errors. Allan Kelly says Agile evolves beyond hype, John Cutler explores cognitive style clashes in teams, and William Hudson warns against mixing up personas. Finally, Laura Tacho rejects activity metrics and proposes an outcome-focused framework for evaluating developer performance.
Leadership resistance to your pre-mortem reveals whether your organization’s operating model prioritizes comfortable narratives over preventing failure. This article shows you how to diagnose cultural dysfunction and decide which battles to fight.
Welcome to the 520th edition of the Food for Agile Thought newsletter, shared with 40,332 peers. This week, Shane Parrish explores Charlie Munger’s take on the psychology of bad decisions, revealing mental pitfalls that sabotage judgment. Teresa Torres distills how AI product teams earn trust and learn faster by narrowing focus and embracing uncertainty. Lenny Rachitsky talks with Stewart Butterfield about building useful products without falling for the founder’s ego, and Jim Highsmith warns that alignment fails without accountability. Also, Christina draws a clear line between tracking performance and setting meaningful, time-bound goals.
Next, Dean Peters presents AI workflows that help PMs stress-test ideas faster and reveal shallow thinking, while Ethan Mollick explains how Gemini 3 behaves like a junior teammate, not just a chatbot. Benedict Evans positions AI as a platform shift, still searching for business models. Maik Seyfert shows how informal shadow systems drive real decisions, and Laura Klein breaks down the costly myths behind skipping user research and the cultural blocks that enable them.
Last, Jenn Spykerman shares tactics for surviving AI chaos when leadership checks out, including spotting failure early and scoping for safety. Gergely Orosz talks with Martin Fowler about how AI reshapes coding while core engineering still holds firm, and Brian Balfour shows how AI prototyping slashes costs and accelerates product alignment. Then, Maarten Dalmijn warns against premature complexity in architecture. Finally, Max Woolf explores Nano Banana’s edge in precise image generation despite style transfer issues and IP risks.
