All we’ve heard about for a few years now is how product management is dead because of AI. How product managers won’t have jobs in 2 years, or how if we don’t vibe code harder, we won’t survive. Our processes and workflows have been condensed into prompts; our SDLC into prototypes; and our formerly impressive thinking and skill sets into a few simple commands in Chat, Claude, Lovable, or Replit.
Simply put, we are toast.
While some aspects of this are sort of accurate, the rest of this is total bullsh*t.
That said, it doesn’t actually change much for product managers. We shouldn’t get too comfy, because while I firmly believe product management is in no way dead, I do believe AI has found a way to discern the good from the great, faster and at a larger scale. Allow me to explain in full.
The overarching, fundamental truth is this: AI has driven exponential, expeditious growth in tooling and efficiency for product managers, especially those on the more technical, forward-thinking side of our practice. It has done this at a pace and scale we have never come close to experiencing. That said, great product managers have always had to be very adaptive, evolve with the industry and the latest technology, and this time is no different.
What this pace and scale have done is weed out the good from the great product talent in a way we haven't seen before. And that’s just fine. It has also shown us where AI breaks down within product, and where PMs must continue to bring our true skills - where we must continue to be great.
So, what hasn't changed with AI? Where will the great product managers continue to shine? Here are some fundamental product truths that continue to hold, even in the age of AI.
If our teams don’t know what we’re building towards and why, it’s much harder to solve problems and achieve the results we want across teams. Let alone make stakeholders and executives happy with those results. How about getting everyone aligned on priorities when we have instances of lean or shared resources? Forget it.
The absence of clear, measurable goals remains one of the most consistent issues we see in companies, even today in 2026. We could have product managers vibe coding all day, every day, but without clear goals, what would they be coding? Would each PM be off coding something different in their own bubble every day/week with no alignment, and delivering random stuff to engineering?
Only one word comes to mind when I think about that in the absence of clear goals, and it’s WASTE. And then I think about the impact on and reaction from my engineers, and what they’d be dealing with in those handoffs, and the second word is NIGHTMARE, and the third is TURNOVER. None of those words is a good word in this context. Without goals, vibe coding is just more waste, so the AI doesn't help us all that much. We still need to create that direction up front, get folks aligned, and be sure we are building towards the right stuff at the right time, then let’s speed up the delivery, and we can prototype all day.
The fact remains that without clear alignment on what we are building towards and why, there will be a painful, avoidable level of waste and inefficiency in product development - AI or not. You must set clear goals, align teams towards them, and ensure there are measurable outcomes, or you’re still just throwing spaghetti at a wall.
Ever notice that all the things folks traditionally list when they say product is dead sound like project management tasks? Writing tickets, managing sprints, resourcing, managing schedules, etc., are often the areas identified first/most when people talk about the parts of the product that are most easily automated or saved by AI. Many of these are also the first to go to a project manager, a product owner, or a much more junior team member. In other words, they are far less fundamental to great product than some of the more strategic, ‘art of product’ leaning things we talk about. While those pieces are surely part of a product manager's life in some environments/roles, they are not the crux of what makes us special. They aren’t part of the art; they’re part of the science, and I’d argue that part is easier to replace with AI.
Product managers who only had tactical skills before were never great. They were tactical product managers. They lacked strategic skills. They likely weren’t going to last in this field long term. That may sound harsh, but in any field, there are folks who are mediocre and those who are great. Those that stand out above the rest. Those that are highly skilled, who adapt faster than the rest in times of change, those that learn new skills and tools fast, who adopt new domains at the drop of a hat, who take on new challenges seamlessly, who flex between tactical and strategic like it's nothing, you know the types I'm talking about. This is true in product management as well, and with the AI wave, these product managers will be just fine. Their jobs aren’t dead. They are the ones who won’t have any trouble sticking around, applying their skills to new tools, learning to adapt to our new world, and flexing between being a VP, leaning back into the weeds, and embracing the change again.
I’ve talked a lot about this rare, special, and amazingly talented type of product manager before. These are the types of folks who can flex seamlessly between tactical execution, strategy definition, leadership, learning new tools, varying subject matters, adapting quickly to new environments, and embracing change. These are the product managers who will outlast the rest in the age of AI, for all of those reasons and more.
They aren’t overly focused on the traditional career ladder of titles, and managing a team of people has never been their main goal. They love being close to the work and have remained inherently flexible, hyper-adaptive, and supremely skilled throughout their careers. Throw in rockstar communication skills, incredible stakeholder management prowess, and collaboration chops like no other, and you can see why the Super IC would be in high demand in the age of AI. No inflated ego, no mid-upper level management or leadership titles to contend with, hands-on productivity and outcomes, and it's a win-win-win all day. I see more and more companies seeking this type of candidate profile for their hiring needs as they move away from leadership-only product roles and back to hands-on delivery as a requirement for their product positions at nearly every level, including VP and CPO, so watch for more about the Super IC out there.
Product will never be the same everywhere - it will differ based on company size, stage, team maturity, product maturity, team dynamics, leadership experience, funding, tech stack, and so many other factors. It’s a lot harder for AI to suss all of that out within an org, see and feel the dynamics and spot tension, sense how a team is operating and where the sensitivities are, where leadership weaknesses or distrust may lie, see where accountability may be lacking or where better guardrails may be needed, or many other human/team elements come into play.
Because product can often be a make-or-break role that acts as a glue across many teams and functions within an organization, many of these soft skills are critically important, and AI cannot automate these. How well we identify these needs and issues, and how effectively we solve these situations, often drive how successful our teams and organizations will be, even if those teams are much leaner due to AI. There will still be people, even if fewer of them, so it's that much more important that we have the right people in the right seats, playing the right roles. It’s clear we haven't gotten AI right just yet.
These needs remain at nearly every company and team I encounter today, in 2026, with all the AI in the world at our disposal. Vibe coding, prototyping, excellent prompts, endlessly available research and data, all of the automation in the industry has not solved for these elements that I believe are the true art of product, and they’re all still in high demand. They all still require great product thinking, excellent stakeholder management, top-notch communication skills, and intricate dependency identification and risk management, which AI tooling can surely aid us with, but which require our art, minds, and experience to guide. Or, at a minimum, to quality-check our AI outputs.
Product hiring is still a nuanced process, and that has not changed. Don’t be swayed by fancy AI experience on resumes and think you should change your hiring criteria, or hire someone solely because you see that they can build prototypes or ship code quickly. Unless that’s specifically what you’re looking for in a product manager.
The same is true for being swayed by name-brand companies they've worked for in the past - stick to what’s most relevant to your needs rather than being wooed. Relevance to the stage, size, industry, and product maturity will yield better hiring results any day than, for example, hiring a FAANG product manager into a 0-to-1 startup (which, in most cases, won't yield a great outcome).
Craft the specific job description your organization requires, based on the skillset and experience you need, the goals and growth you want to achieve in the next 12-36 months, and where your company is and wants to go with your product. Evaluate the needs you have related to AI, and what skills and experience a product candidate needs to have, with respect to the other roles within your organization. Consult with your engineering team and other cross-functional teams that will interface with product, and build out a job description that is uniquely suited to your needs (see above - product is nuanced and different everywhere, so this matters a ton, and very specific job descriptions will yield better candidates and far better results in your hiring process).
So, while AI has drastically changed the tech industry as a whole, I would argue that it has not fundamentally changed product management as much as the LinkedIn headlines may suggest. The art of product is still required, even with AI available to automate many other parts of our practice. The core pieces that make product management so necessary and so special are still essential and still in demand - it just looks a little different.
This job was always about adapting and evolving. That hasn't changed, and it still takes a great product manager to suss out true customer needs, define the right goals, build a strategy to achieve them, and ensure you're building the right solution to solve those customer problems. AI hasn't changed that. It’s just made it much easier to tell the difference between good and great product managers.
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