Those two letters have always meant more than one thing.
PM. Depending on where you work, what you do, or what decade you came up in, those initials could attach to four completely different job titles. Product Manager. Project Manager. Program Manager. And if you’re raising an eyebrow at the fourth one, that’s kind of the whole story.
Production Manager.
Go ahead, say it out loud to a room full of tech people and watch the blank faces. It’s not on the roadmap. It’s not a Jira role. It’s not something your recruiter screens for. But it’s real, and for some of us, it was the first job we ever had without knowing it.
Picture a high school kid putting together a morning show segment at a radio station. He’s scheduling guests, organizing segments, pulling music playlists together for multiple shows when the regular host is out sick, and somehow managing his own Friday and Saturday night party show on top of all of it. Nobody handed him a certification. Nobody enrolled him in an agile workshop. Nobody gave him a title. They just said, here’s the schedule, make it work, and don’t let there be dead air.
That kid was a project manager before he knew what project management was. He had stakeholders, in this case the guests he had to wrangle and the listeners he had to keep. He had deadlines, because in radio you can’t push a show. He had scope, because every segment had a start time and an end time and you had to stay in it. He was coordinating, scheduling, producing, and delivering something real every single week, and he was doing it completely by instinct.
Thinking back on it now, the assumption was that moving from radio into tech would be a massive adjustment. Learning a whole new world, a new vocabulary, a new way of working. And in some ways it was. But here’s the thing that nobody warned about: the Production Manager work was very close to the Product Manager work. The labels changed. The instincts were the same.
That’s the thing about those two letters. They’ve always been a container for a set of skills that don’t actually care about the industry. You’re taking something complicated, making sense of it, getting the right people aimed at the right target, and making sure something actually gets done before the clock runs out. Whether that clock is a radio airtime or a sprint review doesn’t change the fundamental work. It changes the vocabulary and the tools, but not the muscle.
Here’s where it gets interesting though. Because the muscle is still the same, but the exercise keeps changing. And right now, in 2026, the exercise is changing faster than it has in a long time.
The career arc that goes through all of it, every title, every variation, looks something like this. You think of a product, research it, pitch it. You write the recommendations, build the reporting, manage the sprints. You track milestones, manage portfolios, handle the program-level view across multiple workstreams at once. For a long time, that was the full picture of what it meant to be a PM in tech. It was a lot of work. It was genuinely complicated. And it was enough.
Then it changed.
Now the reports are more thorough. Now you’re expected to predict risks before they happen, not just track them after they land. Now you’re managing a team of analysts, coordinators, and specialists who help you manage the portfolio, which means you’re not just doing PM work, you’re leading a function. That was already a significant shift from where things started. But it kept going.
Now you’re not just talking about the next feature. You’re expected to vibe code the MVP, get it into GitHub, and write the PRD that lets a development team take that prototype and scale it into something real. If you haven’t heard the term “vibe coding” yet, here’s the short version: it’s using AI tools to build working software by describing what you want in plain language and letting the AI generate most of the code. You’re still making the product decisions. You’re still defining the user flows, the success metrics, the constraints. But you’re doing it in a working environment, not just a document. According to data published in early 2026, 92 percent of U.S. developers now use AI tools daily and 41 percent of global code is AI-generated. The expectation that PMs can at least navigate that environment, not just observe it from the outside, is no longer optional at a lot of companies.
So yes, the role has changed again. For those of us who’ve been rolling with every version of it, this one is exciting. Not comfortable, necessarily. Exciting.
Here’s a specific example of what “not comfortable” actually looks like in practice.
There was a recent interview for an opportunity that genuinely checked every box. Multiple rounds, thoughtful questions, the kind of conversation that makes you feel like the company has actually read your resume and not just your LinkedIn headline. Then the VP asked, during the interview, whether there would be willingness to sit with the team and vibe code a solution to a problem together.
The honest response was a pause. Not because the answer was no. Not because vibe coding is unfamiliar territory, it isn’t. But because there’s something genuinely different about doing technical, creative, real-time problem-solving in a room full of people who are also evaluating you, who aren’t your team yet, who you’ve known for approximately forty-five minutes. It’s one thing to build something by yourself at midnight. It’s another to do it live while strangers watch.
The answer was yes. Not a polished, strategy-speak yes. An honest one. “I’d be nervous, but I would love to try that with your team.”
As of right now, the waiting game is still on. No offer yet. Which means the headhunters reading this should know: still available. Just, you know, with a current skill set. The point of telling this story isn’t to fill space while the inbox loads. It’s because that moment in the interview captures something real about where PM work is heading. Companies are already testing whether their candidates can do the new version of the job, not just describe it. The bar isn’t just “do you understand vibe coding.” It’s “can you do it under pressure, with strangers, on a problem you’ve never seen before?” That’s new. That’s a meaningful shift in what’s expected.
And the research backs it up. GetProductPeople, a resource for product leaders, reported in 2025 that vibe coding rounds are being introduced into PM interview loops at major companies including Google, Stripe, and Netflix. Candidates are being asked to complete live prototyping tasks under time constraints. The interviewers aren’t just checking technical ability. They’re watching how candidates handle ambiguity, define scope quickly, and make tradeoffs in real time. Those are the exact same skills a radio production manager needed at 17 years old on a live show. The tools are different. The test is the same.
McKinsey research shows that generative AI improves PM productivity by nearly 40 percent when used well. That’s a meaningful number. It also means the gap between PMs who have learned to work with AI tools and those who haven’t is widening every month. By 2030, Gartner predicts that 80 percent of routine PM tasks will be AI-managed. The administrative work, status tracking, basic reporting, meeting summaries, ticket organization, most of that is already being absorbed by automation. What’s left is the work that requires judgment. Strategy. Stakeholder relationships. The ability to look at a messy problem and decide what the right first move is.
That’s not a smaller job. That’s a harder one.
And it’s not just happening in tech.
Healthcare has been going through its own version of this shift, maybe more quietly than the software world, but just as significantly. Project management roles in healthcare have expanded substantially over the past decade, and the scope of what those roles cover has grown to match. Hospital systems are now running full portfolios at any given time. New electronic health record implementations. AI-assisted diagnostics. Patient flow redesigns. Regulatory compliance overhauls. Facility construction projects. The healthcare PM isn’t just someone who ran a few IT upgrades and got promoted. They’re managing multidisciplinary teams that include physicians, administrators, external vendors, data scientists, and architects, often all at once, on timelines where the margin for error has direct consequences for patient care. The vocabulary is different. The instinct is identical.
Construction project management is in the middle of a similar evolution. AI-powered scheduling tools are now embedded in major construction platforms, automatically reassigning tasks based on real-time resource availability and historical performance data. The PM who used to spend two days a week updating Gantt charts and chasing status updates now has systems doing most of that automatically. That freed time doesn’t disappear. It gets redirected toward the strategic work, the contractor negotiations, the scope conversations, the stakeholder updates that require a human in the room. According to research published in 2025, 72 percent of project managers across industries anticipate significant changes to their core responsibilities as AI adoption increases. The ones who are already experiencing that shift aren’t mostly in tech. They’re in construction sites, hospitals, manufacturing plants, and financial services firms, all asking the same question: what exactly is my job now?
The finance sector has been asking it too. Program managers at banks and investment firms have watched compliance and reporting work get partially automated, while the expectation for strategic contribution has grown. The Association for Project Management noted that the number of organizations using AI in project work has nearly doubled in recent years. The implication is straightforward: if AI is handling the volume work, the PM is expected to handle the thinking work. And “thinking work” is harder to learn in a weekend course.
What this all adds up to is a role that’s expanding, not contracting. The title says one thing. The actual job description says something bigger. Product management, in the traditional tech sense, used to be roughly defined as the intersection of business, design, and engineering. That definition still holds, but the circle has gotten larger. Now it includes data fluency, AI literacy, basic prototyping ability, strategic communication, and the capacity to move from “here’s the problem” to “here’s a working version of a potential solution” without requiring a six-week scoping process. GrowthX published a useful framing of how this shift has changed the core of product work: traditional product management was deterministic, meaning you’d define the requirement, build the feature, and measure success. AI product management is probabilistic, because the product’s behavior changes as it learns. You’re not designing every edge case anymore. You’re designing how the system learns from them. That’s a fundamentally different kind of thinking.
For program managers, specifically the technical ones at large companies, the past 18 months have been clarifying in a way that wasn’t entirely comfortable. Several major tech companies quietly reduced headcount in roles that were primarily coordination-heavy, administrative, or focused mainly on running meetings and updating dashboards. The program managers who held their positions weren’t the ones with the most years of experience or the longest list of certifications. They were the ones who could think strategically, communicate value at the executive level, understand the technical work well enough to make real decisions about it, and contribute something that a workflow automation tool couldn’t replicate. The message wasn’t subtle. If most of what you do can be automated, the company will eventually automate it.
None of this means the path forward is panic. It means the path forward is intentional.
There’s a realistic way to think about where people land on this spectrum right now. Some are rolling. They’ve always been curious about what’s next, they pick up new tools quickly, and they find this moment genuinely exciting. They’re the ones already experimenting with Cursor and Claude and Replit, not because someone told them to but because they can’t help themselves. They’re comfortable not knowing everything because they’ve always figured things out as they went. When a VP asks them to vibe code something in a room full of strangers, their first instinct is nervousness and their second instinct is yes.
Some people want to adapt but aren’t sure they can. They’re not resistant. They’re uncertain. They’ve spent years getting good at a specific version of this job, and being asked to essentially learn a new one while still doing the old one is genuinely hard. For that group, the research offers some reassurance: 85 percent of professionals believe on-the-job learning is the best way to bridge the AI skills gap. Not a certification. Not a bootcamp. Practice. Pick one new tool, use it on something real, get incrementally less afraid of it. The goal isn’t to become an engineer. It’s to become someone who can work next to an AI-assisted engineering team and contribute something meaningful. That’s a reachable bar.
And some people won’t adapt, not because they’re incapable but because they’ve decided not to. That’s a legitimate choice. But it comes with a real cost. The PMI, the World Economic Forum, and multiple independent labor researchers have all pointed to project and product management as net job growth categories through the end of this decade. The jobs are there. The question is whether the skills match the version of the job that’s actually being hired for.
Here’s the honest truth about what it means to be a new PM, whether new means new to the field or new to this version of it. The job has never been one fixed thing. It was always a collection of instincts wearing whatever title happened to be available. A kid at a radio station scheduling guest appearances and pulling music playlists was doing the same core work as a product operations lead organizing sprint cycles and managing a feature roadmap. The instinct to take complexity, make sense of it, and drive something forward is the constant. Everything else changes.
The radio work wasn’t a detour. It was the foundation. And every version of PM work since then, every title, every tool, every new expectation that seemed a little too far outside the comfort zone, it’s all been built on that same instinct. The only people who don’t survive the next version of this job are the ones who confuse the title with the skill. The title changes. The skill is yours.
If you’re in this conversation, whether you’re a PM in tech, in healthcare, in construction, in media, or in some industry that hasn’t fully figured out what to call this role yet, share where you are with it. What’s changing in your world? What’s the newest thing someone asked you to do that you weren’t expecting? Find me at @cesarmorenoai on social, and let’s keep this going. More of this kind of conversation lives at cesarmoreno.ai, and if you want it in your inbox on a regular basis, the newsletter is right there waiting.