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Creating the Intelligence Layer: Welcoming CPO Gab Menachem

A transcript of the conversation about what it means to build a digital product in 2026—and why we hired Gab
Company

Apr 14, 2026

6 min read

Adrian Wainwright

Adrian Wainwright

VP Brand & Storytelling, Amplitude

Amplitude CEO Spenser Skates and CPO Gab Menachem in Amplitude's SF office

Today, Amplitude announced its newest CPO, Gab Menachem. The following is from a conversation between Gab and Amplitude CEO Spenser Skates about the next chapter for Amplitude’s analytics platform.

SPENSER:

When we started Amplitude thirteen years ago, the question we were trying to answer was simple: did anyone actually use what you just shipped?

That sounds obvious now. It wasn’t. Most product teams were guessing. You’d ship something, watch the sign-up numbers, read the support tickets, and try to reverse-engineer whether you’d built the right thing. The feedback loop was broken—not because the data didn’t exist, but because no one had built a system to close it.

That’s still the question that Amplitude helps you answer. But the world around it has changed completely.

The products teams are building today don’t look like the products of five years ago. They’re building agents that make decisions. They’re shipping experiences where the software itself is reasoning about what to do next. You can now create a product used by a million people in the time it used to take to run a single sprint. The build-and-ship side of the cycle has been transformed by AI. It’s faster, cheaper, and more powerful than it’s ever been.

And that makes the other side of the loop—the learning side—more important than it’s ever been. If you can build ten times faster, you can also make mistakes ten times faster. The constraint isn’t knowing how to build anymore. It’s knowing what to build.

That’s what Amplitude solves. And that’s why I wanted Gab.

GAB:

When we first talked, I said something I’ve been thinking about for years, that the word “analytics” doesn’t capture what we do.

It’s not wrong, but it anchors us to a moment that has already passed—the moment when “product analytics” meant a dashboard a PM checked on Monday morning to see how last week went.

What Amplitude actually does is close the loop. You build something. You ship it. Users interact with it. And then—this is the part that matters—you bring that signal back into the product so you can build the next thing better. That loop has always been what we do. It’s just that the loop is spinning faster now, and what’s going around it looks completely different.

When I was building Loom Systems, we were doing something similar for IT operations: taking signals from inside complex systems—logs, anomalies, behavior patterns—and using them to help engineering teams understand what was happening before it became a problem. ServiceNow acquired us, and I spent the next six years helping grow this and other products to more than a billion dollars in revenue.

What I learned is that the hard part is making data actionable in real time, at the point where decisions get made. That’s what Amplitude's platform does. And not just for IT or for Monday morning reviews, but for every moment in the product lifecycle.

SPENSER:

I’m focused on making sure that capability reaches every team that needs it. And Gab, that’s what you’re here to do, too.

I’ll say something that might sound strange coming from a CEO: I’m not that worried about competition.

Not because competition isn’t real. It is. But because the thing we’ve built over thirteen years—the behavioral data infrastructure, the accuracy of the models, the way the system understands funnels and experiments and replay all together—that isn’t something you can spin up in a few months.

We benchmarked our AI against the text-to-SQL tools the data warehouse companies have been pushing. 76% accuracy on complex production queries, versus roughly 10% for the others.

That gap is the product of a decade of work that we’re just going to keep building it together.

GAB:

Honestly, the product is further ahead than the market knows. That really surprised me when I started onboarding.

The pace of what’s coming out of this team is remarkable. We’re in the middle of AI Week right now—the whole company is spending the week building AI tools, not talking about AI—and I’m watching teams ship things that would have taken months two years ago. The agents. The accuracy benchmarks. The MCP integrations that let external AI systems query Amplitude's behavioral data in real time. The energy is incredible.

The opportunity in front of us is to keep up that momentum and to make sure the outside world understands what the inside of this company already knows.

SPENSER:

One more thing worth saying directly.

There’s a version of this announcement that’s purely defensive: “Our CPO hire proves that AI is good for analytics, not bad.”

But I didn’t hire Gab to defend anything. I knew he was the right choice for us because the market we’re in just got dramatically bigger.

The market that needs an intelligence layer to understand what their products are doing—to close that loop between building and learning—has gradually grown from mostly consumer-app product managers to encompass enterprise-level software.

But with AI, now every company can build any kind of AI-powered product. That’s a massive expansion of the problem we’ve always solved.

Gab has spent his career at that intersection of complex systems, behavioral data, and the teams trying to make sense of both. He’s a founder. He knows what it means to ship something and to need to know immediately whether it’s working.

We’re excited to have him at Amplitude to build the intelligence platform that every AI-first company is going to need. That work starts now.

Gab Menachem is CPO at Amplitude. Spenser Skates is CEO and co-founder. Follow for more at @Amplitude.

About the author
Adrian Wainwright

Adrian Wainwright

VP Brand & Storytelling, Amplitude

More from Adrian

Adrian work closely with founders, executives, and product leaders on the communications challenges that AI companies face: clarifying their vision, building trust before proof arrives, and translating the capabilities and consequences of AI into the stories that matter.

More from Adrian
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