Here’s the uncomfortable truth for AI product managers:

Leader 4 62 140
calendar_todayschedule1 min read
— Originally published at www.linkedin.com

Building an AI product ≠ Using AI in a product.

One means AI is the heart of the solution.

The other just adds AI to something that already works.

You can know everything about models, prompts, benchmarks, inference speed

But if you can’t frame a real problem, prioritise for adoption, or deliver user value...your AI product is headed for the demo graveyard.

So, if I had to pick just one skill for an AI PM?

I would pick product thinking.

Every. Single. Time.

Because:

  • Technology doesn’t define the outcome. Product thinking does.
  • AI feels like intelligence, but it doesn’t understand your users yet
  • Model performance ≠ product-market fit.

We’ve seen this before: Cloud. APIs. Mobile. Data science.

Hype surges. Adoption stalls.

Not because the tech isn’t ready, but because the “product work” wasn’t done.

Let’s not repeat that with AI.

2 Comments

2 votes
1
🔥 Join developers growing publicly
Share your knowledge, build in public, and grow your developer presence with a global community.

More Posts

Cisco's Amy Chang: A Model's "Passport" Doesn't Tell You Where It Actually Came From

Tom Smithverified - Aug 27

The Sovereign Vault — A Comprehensive Guide to Protocol-Driven AI

Ken W. Algerverified - Jun 4

Your App Feels Smart, So Why Do Users Still Leave?

kajolshah - Feb 2

Your AI Doesn't Just Write Tests. It Runs Them Too.

Kevin Martinez - May 12

Defending Against AI Worms: Securing Multi-Agent Systems from Self-Replicating Prompts

alessandro_pignati - Apr 2
chevron_left
8.2k Points206 Badges
Indiaaimletc.com
83Posts
52Comments
14Connections
Nikhilesh is an entrepreneur, teacher and tech nerd
He is an IIT Kharagpur alumnus. He is also a Goo... Show more

Related Jobs

View all jobs →

Commenters (This Week)

3 comments
2 comments
1 comment

Contribute meaningful comments to climb the leaderboard and earn badges!