How AI Is Transforming the Product Manager Role | How to Be a Top Product Manager

Five years ago, I could predict what a PM would do all day:

Write specs
Attend meetings
Manage stakeholders
Review metrics

Today? It’s completely different. And it’s getting weirder.

AI isn’t replacing PMs. It’s transforming what PM work actually means. If you don’t understand this shift, you’ll struggle in your next PM role.

What’s Actually Changing

1. Prototyping is Now Instant

Before: You’d spend weeks writing a spec. Then engineering would spend 2-3 months building it. Then you’d discover you were wrong.

Now: You can build a working prototype in a day using AI tools.

I’m not exaggerating. In the last 6 months, I’ve built:

A customer survey tool (Claude + Supabase, 4 hours)
A competitive analysis dashboard (ChatGPT + Google Sheets API, 2 hours)
A customer support chatbot (Cursor + Claude, 3 hours)

None of these are production-ready. But they’re real enough to test with customers.

What this means for you: Specs are dying. Your job is increasingly to validate ideas with users quickly, not write detailed specifications.

2. Your Spec Can Now Change

AI can generate docs, analyze data, and update specs in real time.

Before, changing your spec was a big deal. Everyone had to re-read it. Confusion ensued.

Now, you can have a living spec that updates as you learn. Use AI to:

Analyze customer feedback and add it to your spec
Update metrics and adjust targets
Generate edge cases you hadn’t considered
Create acceptance criteria from customer quotes

The spec is now a living document, not a frozen artifact.

What this means for you: You’re a curator of information, not the author. Your job is to collect customer insight, feed it to AI tools, and keep specs current.

3. Data Analysis is Instant

Before: You’d need a data analyst to run queries. You’d wait 2 days for results.

Now: You can ask ChatGPT or Claude to analyze data in seconds.

Example: “Here’s data on feature usage. Why did engagement drop last week? What should I do?”

Not perfect, but fast enough to guide decisions.

What this means for you: You don’t need analysts for routine questions anymore. You need analysts for strategic questions: “How do we set up our metrics system correctly?“

4. The Product Engineer Role is Now Viable

This is the big one.

Before, a Product Engineer was a rare hybrid: someone technical enough to code but strategic enough to understand product.

Today, with AI, you don’t need to be that technical. You can be someone with PM skills who uses AI to build.

So the Product Engineer role is becoming more attractive and more common.

What this means for you: If you want to stay relevant, you need to learn to code at least a little. Or learn design. Or learn data analysis. Pick something you can do hands-on.

What’s NOT Changing

PMs aren’t becoming engineers. And engineers aren’t becoming PMs.

What’s changing is that the boundary between the two is getting blurry.

What PMs Still Need

1. Customer Empathy AI can’t talk to customers. It can’t read between the lines. It can’t understand what a customer really needs when they’re angry.

2. Strategic Thinking AI can’t answer: “Is this the right problem to solve?” or “Should we enter this market?” These require judgment, risk tolerance, and long-term thinking.

3. Taste AI can generate ideas. But only humans decide which ideas are good.

4. Judgment Under Uncertainty Most PM decisions are made with incomplete information. AI can’t make those calls. You have to.

What Changes is How You Spend Time

Before: 40% writing specs, 30% in meetings, 20% analyzing data, 10% with customers

After: 5% writing specs, 20% in meetings, 5% analyzing data, 50% with customers (testing ideas), 20% building/prototyping

You’re spending more time with customers. Less time writing. Less time analyzing. More time validating.

What This Means for Your Career

If you’re currently a PM:

Option 1: Go Deeper on PM Strategy

Stay traditional. Lean into the areas AI can’t do: strategy, judgment, taste, customer empathy.

You become the visionary PM. Less time on execution details. More time on what matters most.

Option 2: Become a Product Engineer

Learn to build. Use AI to amplify your skills.

Instead of writing a spec and handing it off, you build prototypes. You validate with customers directly. You own outcomes, not just decisions.

Option 3: Become a PM-Analyst Hybrid

Lean into data. Use AI to automate routine analysis.

You become the PM who understands the metrics deeply, can spot patterns others miss, and uses data to make strategic calls.

The Uncomfortable Truth

AI is creating a bifurcation in the PM market.

On one side: senior strategic PMs who do the thinking. These jobs will be rarer but better paid.

On the other side: product engineers and PM-adjacent roles who execute. These jobs will be more common but less prestigious.

In the middle: mediocre PMs doing routine PM work. These jobs are disappearing. Tools are automating this work.

If you want to survive and thrive, you need to pick a side. Either go deep on strategy (hard, requires seniority) or go deep on execution (requires building skills).

My Prediction

In 5 years:

“PM” will still exist, but it’ll mean something different
Product Engineer will be as common as PM
Most companies will have both roles explicitly
The tools will be better, faster, cheaper
The bar for PM judgment will be higher (since thinking is harder to replace than execution)

What You Should Do Today

Start building. Use Claude, ChatGPT, Cursor, or Replit to prototype ideas. Build muscle memory around AI tools.
Spend more time with customers. You can’t delegate empathy.
Learn to think strategically. This is increasingly your superpower vs. AI.
Don’t be afraid of the change. Weird times create opportunities. The PMs who adapt fastest will do best.

The PM role isn’t dying. It’s evolving. And if you evolve with it, you’re going to have more impact than ever before.

Part II of “How to Be a Top Product Manager” dives deep into how AI is reshaping PM work, what new skills you need, and how to position yourself for success in this AI-transformed landscape. If you’re serious about staying relevant as a PM, it’s essential reading.