Why is product discovery — the practice of identifying the right things to build before switching to delivery — so hard to implement? In my previous article I described two systemic problems: must-have features and weak goals. In this article I’ll focus on three key challenges that the are down to the product org itself. […]
Many companies recognize it’s better to develop products through research, experimentation, and evidence-guided decisions, yet few are able to make product discovery truly work. While the concept has been around for a long time, implementation is often half-hearted, partial and ineffective. AI dev hype is making things worse. In this and the following artile I’ll
We are regularly told that AI has caused a deep shift in product development. The old patterns are no longer relevant, and you have to either adapt or die. In this article I’ll try to assess if that’s indeed the case. Have we fundamentally changed the way we develop and sell tech products? Is this
Marty Kagan and Elias Lieberich, just published an article titled “The Product Model at Google”. It’s a good article that gets many things right, but I think there’s also a more nuanced picture that’s worth talking about. I see Google as an example of a company that used to have one of the best product
The Product Operating Model at Google – A Critical View Read More »
Whenever I teach product discovery, someone will raise their hand and ask a variant of this question: “This feels slow. Wouldn’t it be faster to just launch it and see what happens?” The answer is No. If you skip product discovery you may get bits into production faster, but you’ll create value far slower. This
All tech companies have to choose what to build, but approaches vary — from top-down projects to bottom-up research and experimentation. Your company is probably somewhere on this gamut, but it’s not always a deliberate choice. It’s important to realize that these are not the only two possible models, and that there isn’t necessarily just
Impact is a central concept in product development, but it’s often unerdused or misused. In this article I want to suggest a thinking tool, The Total Impact Matrix, to help you use it better. The impact of an idea is the sum of value it creates for our target audience — customers/users/partners — and for
Generative AI is transforming product management, or so we’re told by AI companies and influencers. The vision appears to be all about output: The PM producing roadmaps, backlogs, PRDs, user stories, and prototypes faster than ever before. Some companies are accepting these claims as truth and pressuring their PMs to use AI, but in my
AI and Product Management: Becoming More Evidence-Guided Read More »
By now you must have heard an awful lot about how gen-AI will “10X” tech workers’ productivity and massively cut development costs. This promise is music to the ears of executives and tech-eutopians, but currently is not backed by any rigorous research (most of the evidence comes from coding competitions and reported usage — mostly
In his latest book, Transformed, Marty Cagan introduces the term The Product Operating Model (POM) which he defines as “How the best tech-powered companies work …— principles, practices, and competencies ”. I feel that, like Product Discovery, which Cagan also coined, the Product Operating Model is going to be an important and useful concept, but