I recently took the stage at Data Science Conference Europe to discuss a massive shift occurring in our industry: the evolution of the Product Manager into what I call a Full-Stack Product Developer. In this post, I’m recapping that talk briefly, and sharing the slides.
Traditional PM Role and Changes in Expectations
We are moving past the era where PMs simply define products; today, thanks to AI, automation, and no-code tools, we are empowered to actually build them as the barrier to building is lower than ever (e.g. you used to have to know how to code, today you can ‘talk’ to Lovable or a similar tool in natural language and get apps and websites in minutes).
Product managers used to be ‘just’ decision makers – they did not implement or build prototypes and solutions. This setup worked in the past, but with the barrier to building becoming lower, expectations are rising. Nowadays, a PM should be able to make Proof of Concept (POC) or even a Minimum Viable Product (MVP), analyze and visualize data, configure cloud services on a basic level, etc.
One example of these changing expectation is Google now asking candidates interviewing for product roles to vibe code live on spot. Duolingo CEO asking all employees to do a vibe code project.
Individual Profiles: Broad and Shallow or Narrow and Deep
Previously, professionals used to specialize in their single domain, for instance, software engineering or product management. Full Stack Product developers are in between, they are generalists who do both at a certain level. With the new tools and technology, they are much more effective, so a generalist PM can relatively easily build a working POC or even MVP.
Additionally, nobody says generalists need to stay ‘shallow’ – in fact, someone who specialised earlier would not be as skilled in other domains as someone who was a well-rounded generalist before becoming a specialist, making them more valuable. (Remember the ‘T-Shaped Person‘ metaphor.)
Team Profiles
The teams are changing as well, not only individuals. With the rise in productivity and effectiveness thanks to AI and emerging technologies, smaller teams would do more. I believe they would consist of a small number of high-skill, high-agency individuals. 80-90% generalists, 10-20% specialists. And (agentic) AI.
The Slides
Here’s the full presentation. It covers the topic in more detail.
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