From Lenny's Podcast with Tomer Cohen, CPO at LinkedIn

How the Product Manager
Is Becoming a Product Builder

The role isn't disappearing. It's expanding — one person, entire lifecycle, AI handling execution. Here's how.

Based on Tomer Cohen's talk on Lenny's Podcast · Watch on YouTube →

The Lifecycle You've Always Had to Navigate

Eight stages. Dozens of tasks. A team to execute each one.

Tomer opens with the full product development lifecycle: Insight → Research → Solution → Roadmap → Design → Code → Test → Launch. Eight stages, each with a deep column of execution tasks.

You know this map. The PM's job was to navigate it — holding the vision and priorities while specialists executed at each stage. PM as coordinator.

Product Development Lifecycle — full detail view

Product Development Lifecycle — from Insight to Launch, with every sub-task at each stage. This is the scope of what building a product actually requires. It used to take a full team.

The Model
PM defines direction + priorities. Specialists execute at each stage. The PM's leverage comes from coordinating across the team — not from doing the work at each stage personally.

Then AI Agents Entered Every Stage

The execution layer just got automated.

Tomer adds a layer: an AI agent under each stage. Not a future vision — already deployed at LinkedIn.

Research Agent at Insight. Growth Agent at Research. Trust Agent at Solution. Design Agent at Design. Coding Agents at Code. QA Agent at Test. Maintenance Agent at Launch. The entire execution layer, automated.

Product Development Lifecycle with AI Agents

AI agents at every stage. Research Agent, Growth Agent, Trust Agent, Design Agent, Coding Agents, QA Agent, Maintenance Agent — the execution layer at each stage of the lifecycle now has an AI handling it.

Every stage that used to require a specialist now has an AI agent — at your direction. The person who directs the agents needs to understand the full lifecycle, not just one stage.

"I'm working really hard to automate everything except the five skills that make a great builder." — Tomer Cohen, CPO at LinkedIn

What This Creates

One person. The entire lifecycle. Insight to Launch.

If AI handles execution at every stage, the coordinator of specialists role dissolves. What replaces it is bigger: The Full Stack Builder. One person who owns Insight to Launch — not by doing everything manually, but by directing, evaluating, and course-correcting at every stage.

The Full Stack Builder. One person in the center of the entire lifecycle — spanning from Insight on the left to Launch on the right. The coordinator role is replaced by the owner role.

The Shift in One Line

        Before: PM coordinates specialists through the lifecycle.

        After: PM directs AI agents through the lifecycle — and owns the result end to end.

Growth PM, Platform PM, Data PM, Technical PM — these titles existed because execution was siloed. When AI handles execution, silos collapse. What remains is the person with judgment to direct the whole system.

What's Human vs. What's Machine

Your decade of PM experience is the entire top layer.

Two layers in the Full Stack Builder model. At the top: Human. Vision, Empathy, Communication, Creativity, Judgment — the skills you've spent a decade building. They can't be automated because they require knowing what good looks like and when something is subtly wrong.

At the bottom: Machine. Research synthesis, code generation, design, testing, deployment. AI is filling this in rapidly at every stage.

Human vs Machine — Full Stack Builder chart

Human vs. Machine, across the full lifecycle. Top layer: Vision, Empathy, Communication, Creativity, Judgment — the human skills that drive every stage. Bottom layer: Machine automation filling in execution. This is the Full Stack Builder distribution.

You already own the top layer. The question is whether you can use it to direct AI through the bottom layer.

Vision

Empathy

Communication

Creativity

Judgment

The Implication

        The more AI takes over the bottom layer, the more valuable the top layer becomes. Senior PMs with deep human judgment get significantly more leverage in the Full Stack Builder model — not less. The people who get displaced are those who never developed judgment and relied entirely on execution.

The Speed Change Nobody Talks About

Multiple full iterations in the time it used to take to run one.

It's not just that one person spans the full lifecycle. It's the speed. Traditional cycles took months per iteration. With AI handling execution, the lifecycle compresses dramatically.

Tomer shows it: MVP → Iteration One → Iteration Two, stacked — each running a full insight-to-launch cycle in the time the old model spent in research alone.

Product lifecycle iterations — MVP, Iteration One, Iteration Two

MVP → Iteration One → Iteration Two. Three complete insight-to-launch cycles, now running in compressed time. The bottleneck has shifted from execution to judgment. How fast can you evaluate, decide, and direct the next iteration?

The bottleneck has moved from execution to your judgment — how fast you can evaluate, decide, and direct the next iteration.

"The people winning right now aren't shipping faster because they have more engineers. They're shipping faster because one person with great judgment can now direct AI through an entire lifecycle." — Framing from Tomer Cohen's talk on Lenny's Podcast

What This Means If You're Still Mostly Managing

You're not falling behind because you're bad at your job. You're falling behind because the job changed.

Everything Tomer describes is happening now. The Full Stack Builder model is already being hired for. Specialty PM postings are declining. Companies that adopted it are already iterating faster.

Most senior PMs don't see it because they're busy — in roadmap reviews, stakeholder meetings, Jira. Busy managing while the role shifts underneath them.

The irony: PMs most at risk are often the most senior — those who mostly coordinate and rarely build. Junior PMs have been building with AI out of necessity. They're a year ahead.

The Gap That's Opening

        There are now two kinds of senior PMs. The ones who've learned to direct AI through the full lifecycle, and the ones who haven't started yet. The gap between them is growing every month. The skills aren't hard to learn — but they take time to build, and you have to start.

The good news: you already have the hardest part. Vision, Empathy, Communication, Creativity, Judgment — those took a decade and can't be shortcut. What you're missing is execution fluency: directing AI through design, code, test, and launch. That's learnable.

How the Product ManagerIs Becoming a Product Builder