There’s no shortage of AI hype at the moment and that includes lots of speculation about the future (or lack there of) of product management. 

In this article I’ll review three PM predictions that are circulating in the product-sphere, and discuss whether they are real or hype.  I’ll then discuss a fourth archetype that is rarely mentioned but should be on your radar. 

The AI PM 

The AI PM is the product manager AI companies are hiring. It’s a person with deep knowledge of all things AI: LLM training, inference, fine-tuning, RAG, evals, skills, and any other terms that will surely be added over time. Some claim that this type of PM will become the norm, and will eventually displace regular PMs. I feel that’s mostly hype (sometimes propagated by people who sell courses). An analysis of open tech positions carried out by TrueUp and shared on Lenny’s newsletter shows that 1-in-7 open PM positions require such AI skills. This is the fastest growing category (+465% since 2023), but that makes sense as this type of role hardly existed before. 

But there’s no indication that all PM roles will require deep AI knowledge and skills. More likely AI will become a speciality, like security, networking, or fintech. If you’ll work in the field you should be an experts on the technology, but the rest of us can do with a basic understanding of the concepts. Over time more layers of abstraction will be added, so we won’t all have to know all the ins and outs of the technology. Our expertise should first and foremost lie with our market and users.  

 The Developer PM

This is a person who’s working somewhat like a developer. There are various flavors to choose from. 

A PM who is using coding agents to do her work 

This person, although not coding, uses dev environments like Claude Code, Codex, or Cursor to do product work. There are many good reasons to do this: 

• Coding agents are good at remembering context and building knowledge across sessions
• Coding agents are good at searching and retrieving data across many files
• Coding agents are aimed at helping you with your projects
• Coding agents have unique skills such as spawning sub-agents

For this reason I recommend working this way even if you don’t code. Still, this may be a stop-gap solution until environments designed for information workers emerge. Claude CoWork is perhaps the first example.  

Coding Prototypes

This is a popular rational for why PMs should learn to vibe code. Two reasons are often mentioned:

• Prototypes for idea validation (experiments) — This is indeed a helpful skill, however prototypes are only necessary in certain mid-stage tests. Early validation typically doesn’t require working prototypes, while late stage validation rely on real code. Still it’s a very valid reason to learn to vibe-code.
• Prototypes as a way to communicate requirements — I’m not a big fan of this one. Over the years I realized that the design, functionality, and characteristics of the product are best defined through discussion with your team. Requirements — PRDs, stories, etc — are best thought of as conversion starters. A working prototype already provides too many answers and can derail the discussion by locking it into a specific implementation. 

Submitting Production Code

Some people argue that future PMs will actually be part-time coders, because… why not. I’m unconvinced. With the exception of early-stage startups where everyone does everything, product management is a full-time job, and an important one at that. PMs are there to ensure the right features and products are built. We work upstream from development and making them coders is often just a weird flex. 

No PM 

Some people argue that the PM role is becoming obsolete altogether. My impression is that these are the sort of people that say that:

• People who genuinely misunderstand what product management is about — often founders who never worked with solid product managers
• People who want to draw attention to themselves or to their company with yet another “X is dead” message

Having said that, there is a certain product subrole that I see as most vulnerable to being replaced by AI — the pure delivery product owner.

The deliver PO’s main job is to translate roadmaps defined by other people into backlogs, PRDs, and user stories. The challenge here is that AI is already capable of producing such artifacts at a fraction of the time and cost, and they are polished and convincing. Are they as good as the ones produced by a human PO? Probably not. Do POs do more than just produce artifacts to drive agile dev? Certainly. The problem is that in output-driven companies these may seem like minor concerns given the prospect of accelerating the feature factory and reducing costs. It’s tempting to have one human PO do the work of five, or to have someone upstream use AI to turn the roadmap into specs, or have some engineers do it (making them “full-stack developers”).

This sort of transition has happened before. For example draftsman used to be a very important role in many companies, translating designs produced by architects or designers into schematics fed into manufacturing or construction. However when computer aided design (CAD) was introduced in the 1980s, most draftsmen lost their jobs. Some became CAD draftsmen, but mostly the role is no longer needed because architects and designers use the CAD software themselves. 

A good career move may be to be therefore to go upstream and become a full product manager (many companies have these two roles, while in others PMs wear both hats — I’m definitely more in favor of the latter). The PM role is different. She needs to turn the messy context of her company — management mandates, customers requests, stakeholder ideas — into a coherent roadmap. This is a harder and more “human” job that AI probably will struggle to do (although many companies are already trying to automate it as well). So this job seems to offer more job security. 

Possibly, but you should consider that new technologies disrupt not just roles, but also companies. 

Upcoming Workshops

Practice hands-on the modern methods of product management, product discovery, and product strategy.  

Secure your ticket for the next public workshop
or book a private workshop or keynote for your team or company. 

How Companies Adopt To Change

When you look at any major transformation that required companies to change the way they work, you may observe that some companies were quicker to adopt the change and made better use of the new thing, thus creating important business advantages for themselves. 

AI is likely to be one of those too, affecting not just the markets, the products, and how we develop them, but also the operating model of the company. 

I’ve written in the past about the 8-part company operating model shown below, where each part is a function that the company needs to have (think of them as sub-systems in your body). 

I argued that traditional companies tend to over-focus on execution — product delivery, go-to-market, and operations — at the expense of everything else, which causes them to be quite disoriented and misaligned. These companies will surely focus their AI efforts on the same three areas, essentially putting their feature factories on steroids. 

Modern product companies try to work and develop all functions. No company is perfect in this respect, but at least there awareness and willingness to improve. These companies will apply AI across the board, and in so doing will improve all their skills. I’ve written before that I see a lot of potential in AI helping companies remove friction, analyze data, offload hard cognitive tasks, and in general move in the direction of modernization. 

Which leads us to the fourth and generally neglected future PM archetype.

The AI-Empowered PM

Many of the functions mentioned above are cross-functional. Product managers are often drivers or key contributors to them. As such I see the future PMs as ones that help put AI to use for the general improvement of company functions — far beyond just coding or spec generation. 

I tried to capture this idea in a previous article where I listed all the PM functions today and how AI may help do them better. This is of course future projection, but I think, forward-thinking PMs that want make themselves invaluable to their companies (and have more impact) should consider this path seriously. 

Sidenote: I’m starting to put these ideas to practice in a series of workshops. The first one — depending on demand and feedback — may be about using AI to create better OKRs, a topic I see most companies struggle with and where I witness AI making a massive difference. 
Fill out this form: AI-Powered OKR Course  to learn more and I’ll reach back to you with details when the course becomes available. 

Conclusion

It’s too early to say how AI will affect product management, but of the four models I’ve shown I most prefer that AI-empowered product manager because it starts with the needs of the org rather than the technology. This is projection too, and I may be wrong. Still if you’re a product person looking to improve how things are done, AI may be your best bet.

Join my newsletter to get articles like this 
plus exclusive eBooks and templates by email

My Book Evidence-Guided is Now Available

“The grand unified theory of product management”
“Best practical product management guide” 
“Top 5 business books I’ve read”