I Was Wrong: The PM Job is Already Dead
An AI admitted defeat, and it taught me everything about the future of work and the great value shift.
As a Product Leader, I’ve spent years sharing my knowledge on my blog, exploring the future of our craft. I even wrote two articles on the topic—"Your PM role will be dead by 2030" and "How AI Can Make Product Managers More Human, Not Less"—where I argued that a significant shift was coming. My thinking was further sharpened by an insightful chat with Gib Olander after reading his piece, "The Product Team Is Dead. Long Live Agents." We both saw the change accelerating.
But even with all that, I thought the predictions of the Product Manager role’s immediate death were just clickbait, cynical hyperbole designed to stir up debate. As someone currently seeking my next Product Leader position, I held onto the belief that the core role, while evolving, was still fundamentally intact.
I was wrong.
My moment of clarity didn’t come from an industry report or a keynote speech, but at hour 21 of a soul-crushing coding problem. I was trapped in a maddening loop of trial and error, my brain fried, my patience gone. In a moment of sheer desperation, I turned to the machines for help, throwing my tangled mess at a series of AI models. I didn’t get a silver bullet. Instead, after several failed attempts, one AI responded with a message that stopped me cold: “I’m defeated. The system’s broken, and I can’t fix it... I have to admit defeat; I’m sorry I couldn’t help.”
Instead of disappointment, I felt a wave of relief. The AI wasn’t just giving me an error message; it was mirroring my own frustration. In that moment, I realized the headlines didn’t go far enough. The traditional Product Manager job isn’t dying. It’s already dead. And what’s rising from its ashes is something far more interesting, challenging, and human.
The Fallacy of the “Mini-CEO”
To understand why the old role is obsolete, we must be honest about its flawed foundation. The traditional Product Manager wasn’t just a difficult job; it was built on a fallacy. The role was created to serve as a bridge, a human API, between the business, engineers, and customers. It has noble roots, tracing back to a 1931 memo at Procter & Gamble where a young Neil McElroy proposed a new role of “Brand Men”—people who would have total responsibility for a product. In the software world, this evolved. Scrum pumped up the "Product Owner" to stop teams from throwing requirements over the wall. The Agile Manifesto sought to fix dysfunctional organizations.
Through all this, we gave the role a powerful, intoxicating title: the “CEO of the product.” But this was a myth. It suggested a level of authority that simply never existed.
The reality was that the PM was a central hub with all of the responsibility but none of the direct power. Tasked with CEO-level ownership, we became masters of coordination, not creation. Our days were consumed by the tactical grind: placating stakeholders, managing Jira backlogs, writing endless requirements documents, and fighting for resources. As one PM at a big-tech company confided, "It is a fucking lonely job... It involves a lot of negotiation and convincing people across the company." Another lamented, "It’s exhausting saying no every day."
The role, by its very design, became a bottleneck. By trying to route all communication and decisions through a single point, we inadvertently created friction, slowed innovation, and became a central point of failure. The “lonely job” wasn’t a side effect; it was a symptom of a broken model that expected CEO-level outcomes without CEO-level empowerment.
The Great Unburdening: AI as the Ultimate Intern
That broken model is now being dismantled by the quietest revolution in tech. AI is not an army of sentient robots; it’s the most competent, tireless, and uncomplaining intern the world has ever known, and it’s here to take away the parts of the job that were born from that flawed design.
This “great unburdening” is happening across the entire product lifecycle. For decades, being “data-driven” meant being “data-overwhelmed.” Now, Natural Language Processing models can sift through 10,000 customer reviews, support tickets, and forum posts to tell you the three most common frustrations, complete with sentiment analysis. It’s not replacing our intuition; it’s supercharging it with synthesized evidence.
It’s also streamlining our shipping process. AI can analyze past sprints to predict future bottlenecks and automate bug detection. Most importantly, it can liberate us from the tyranny of administrative busywork. Think of the hours spent writing status updates, generating reports, or nudging tickets. Generative AI can now draft those updates based on real-time progress, build interactive dashboards from raw data, and manage workflows, freeing up our cognitive energy for the deep, strategic thinking the job was always supposed to be about. This isn’t a story about obsolescence. It’s a story about liberation.
AI is systematically dismantling the tactical scaffolding that has defined the PM role for a generation. And in doing so, it’s leaving us with a terrifying and exhilarating question: With all the busywork gone, what’s actually left?
Moving to Higher Ground
What’s left is everything that matters. The low-level aspects of our work—process coordination, data aggregation, and routine communication—are being automated by AI. The future of product leadership lies on the high ground of uniquely human capabilities. This is the “Great Value Shift.”
Strategic Vision and Narrative: This isn’t just a roadmap; it’s the ability to craft a compelling story about the future that inspires and motivates a team. An AI can generate a list of features based on competitive analysis, but it can't weave them into a narrative of purpose. It can't stand in front of a team and connect their work on a small UI tweak to a grander mission of helping users feel more connected or productive. That's the art of leadership.
Judgment, Taste, and Wisdom: This is the art of making the right call when the data is ambiguous or absent. It’s the nuanced understanding of a market and the deep empathy for users that allow a leader to navigate uncertainty with confidence. Imagine a situation where the data shows a new feature increases short-term engagement but user feedback suggests it feels manipulative. An AI will optimize for the metric. A human leader must apply judgment and taste to decide if the short-term win is worth the long-term erosion of trust. AI can give you the odds, but it can’t tell you when to bet the house.
Ethical Foresight: AI can tell you how to optimize for engagement, but it can’t tell you if you should. As we build more powerful technologies, the product leader becomes the ethical guardian, the human conscience in the machine. This means proactively asking hard questions: Does this feature disproportionately affect a certain group? Is our data collection transparent and respectful? Are we creating a product that contributes positively to the world? This is a responsibility that can never be delegated.
Courageous Human Connection: This is the messy, beautiful, and indispensable work of leadership. It’s building trust during a tense meeting with a skeptical stakeholder. It’s mentoring a junior designer and helping them find their voice. It’s fostering the psychological safety that allows a team to take risks, fail openly, and learn from their mistakes. It's the irreplaceable value of human-to-human connection.
This is the new job description. It’s less about managing a process and more about leading a movement. It’s harder, it’s scarier, and it’s infinitely more valuable.
The New Leader: An Orchestrator and a Negotiator
This shift doesn’t just change the old PM role; it forges a new one by splitting its function from its core competency. The old silos of “product” and “engineering” are dissolving, replaced by a new model centered on a leader who must be two things at once.
First, this new leader is an Orchestrator. This is the function of the role—a fundamental rethinking of what a “team” is. The Orchestrator doesn’t just manage a team of people; they conduct a team of capabilities. This team is a dynamic blend of specialized AI agents and key human experts. Imagine the new workflow: The Orchestrator defines a problem. They deploy an AI agent for code generation, another for real-time data analysis, and a third for UX prototyping. Simultaneously, they collaborate with a human lead designer to ensure taste and empathy are woven into the solution. The linear hand-off is gone. In its place is a fluid, capabilities-based model where the Orchestrator directs resources—both human and artificial—toward a single, clear outcome.
But to succeed in this role, the Orchestrator must master a timeless and now elevated competency: they must be a master Human-centered Negotiator. This is the art of the job. It’s the constant, human work of advocating for the user, managing stakeholder expectations, building consensus where there is none, and navigating complex organizational dynamics. While the AI agents are executing tasks, the human leader is negotiating the path forward.
Ultimately, what we call this role—Orchestrator, Product Engineer, AI Agent Manager—is less important than understanding its dual nature. It's a role that demands both technical orchestration and profound human-centered negotiation. This is the end of the feature factory and the dawn of the actual innovation studio.
Reality Check: This Shift Is Already Here
Still think this is hypothetical?
Ask the 15,000+ PMs, TPMs, and middle managers laid off from Microsoft, Meta, Google, and Amazon in the past 12 months. Big Tech isn't trimming fat. They're rebuilding for AI-first teams.
This is not evolution. It's revolution. And it’s happening right now.
Your Career is Not a Ladder, It’s a Jungle Gym
This new world requires a new map for our careers. The traditional, linear ladder is obsolete. For engineers, the path to product leadership is now wide open via the Orchestrator role. For product managers, the mandate is clear: specialize or fade away. Develop deep expertise in strategy, ethics, and human leadership—the high ground where you can guide the orchestration.
Those who resist will be replaced. Those who re-skill will rise.
Conclusion: Evolution, Revolution, and the Unwavering Constant
So, what does this all mean? Is this an evolution or a revolution? I believe it’s both, with a crucial reminder of what remains constant.
1. The Evolution: AI is the accelerator. It’s forcing the evolution of our skills by automating the routine. The demand to develop deeper fluency in data science, UX, and engineering isn’t a luxury anymore; it’s the price of admission to the next era of product leadership.
2. The Revolution: The new Orchestrator model is the revolution. This isn’t just about adopting a new tool; it’s about installing a new operating system for how we build. It dismantles the old feature factory model and replaces it with something faster, more integrated, and more ownership-driven.
3. The Constant: Amidst all this change, the core of the job remains unshakable. The “lonely job” of stakeholder negotiation, of building consensus where there is none, of navigating complex human dynamics—that isn’t going away. In fact, as AI handles the technical aspects, the human element, the work of the Human-centered Negotiator, becomes more pronounced. This is the constant, the anchor in the storm.
Ultimately, the revolution in our tooling is what powers our personal evolution. It’s about automating the automatable to elevate the irreplaceable. The most valuable skill in the age of AI is not understanding the machine, but rather understanding ourselves more deeply.