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 […]
Is AI Disrupting Product Development? Read More »
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
Why Not Just Launch It? (AI Edition) Read More »
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
Four Product Discovery Models: A Practical Map Read More »
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
The Total Impact Matrix – Beyond Blind Bets Read More »
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
Beyond Productivity: Gen-AI’s Deeper Use Cases Read More »
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
The Product Operating Model Explained Read More »
In the first article in this series I reviewed common prioritization approaches, including opinion/consensus/HiPPO, rules-of-thumb, and Cost of Delay. I also explained why prioritization as part of product discovery — prioritizing what to test — is far more effective than prioritizing what to build. You greatly reduce the cost of prioritization errors, and at the
Prioritization Techniques Compared – Part 2 Read More »
Prioritization is the process of choosing which ideas/bets to invest in and which to postpone or park. It entails two cognitively-hard tasks: 1) evaluating the merit of each idea, and 2) comparing multiple ideas and choosing an order of precedence. If that’s not difficult enough, prioritization decisions are often a flash point of debate and
Prioritization Techniques Compared — Part 1 Read More »