Tip
Ayo Omojola talks about Cash App differentiation: “Being different is not enough, because it’s very easy to build a thing that’s different from what exists today, because you just have to look at what exists today and build something else. Being better is not enough, because it’s also easy to say, ‘Hey, I’m going to make this thing better and just charge you more money for it.’ It has to be better than what exists today in a way that matters to the end user. For us for a long time it was when someone says, ‘Hey, why are you betting on Venmo?’ I’d be like, ‘Try and send me a dollar that I can use now,’ and there was only one app you could do it with.”
Turns out AI product differentiation works the same way.
Your team is launching an AI analytics tool. The PM says: “We’re using GPT-4 Turbo instead of GPT-3.5—it’s way more accurate!” That’s different. The eng lead says: “Our UI is cleaner than Tableau—way better UX!” That’s better. But neither matters to your target buyers. Different doesn’t win. Better doesn’t win. Different + better + matters wins.
Younger product leaders build features they find cool. They chase technical differentiation (“we use the latest model!”) or design differentiation (“our UI is beautiful!”) without validating whether buyers care. They haven’t shipped enough products to market to know that most “differentiation” is irrelevant.
You’ve seen this movie before. In 2016, your team built an analytics dashboard with gorgeous visualizations—way prettier than competitors. Customers didn’t buy it because they needed SQL export functionality, not prettier charts. In 2019, you shipped a chatbot with state-of-the-art NLP—technically superior. Customers churned because they wanted phone support, not better bots.
You know the pattern: differentiation only matters if it solves a problem customers will pay to fix. So before you let the team ship “AI analytics with GPT-4,” you ask the hard questions: “What problem does instant answers solve that weekly reports don’t solve?” “Would a CFO pay $50K/year for this, and why?” “When we demo this, what’s the 10-second sentence that makes them pull out their credit card?”
The answer emerges: instant answers don’t matter to CFOs who review quarterly. What matters is automated anomaly detection—the AI flags unusual patterns before they become problems. That’s different (competitors require manual review), better (catches issues weeks earlier), and matters (prevents costly mistakes). You pivot the messaging and roadmap accordingly.
This judgment—knowing the difference between differentiation that impresses peers versus differentiation that converts buyers—comes from watching enough product launches succeed and fail. Junior PMs think differentiation is about being clever. You know differentiation is about solving problems customers can’t solve themselves. That calibration comes only from seeing both patterns repeatedly over decades.
Context
Ayo Omojola co-created and scaled Square’s Cash Card alongside Cash App (grew from 50K to 50M+ monthly actives). Currently Chief Product Officer at Carbon Health.
His key insight from Cash App: the app won against Venmo not by being different (many P2P apps existed) or better (incremental improvements), but by being instant—money available to spend immediately, which mattered enormously to users despite seeming like a small feature. For experienced executives evaluating AI product strategy, this pattern recognition is critical—you’ve launched enough products to know what kinds of differentiation actually convert buyers versus what impresses engineers.
That comes from seeing the full launch cycle repeatedly.