Your insights are dying in dashboards

When people ask me how I ended up running a company in the sales and revenue space when I've been coding my whole life, the honest answer is: by accident.

And that accident is the reason I want to talk to you today about something we've been calling revenue activation, why insights keep dying in dashboards, and what we've learned from deploying AI across some of the largest revenue teams in the world.

The accidental origin story

When my co-founder and I started Hyperbound back in January 2024, we weren't building what we're known for today. We were actually building one of the earliest AI SDRs out there. The term "AI SDR" didn't even exist back then. People had no language for it yet.

The problem was, neither of us had ever sold anything in our lives. We didn't know how to run a discovery call. We didn't know how to run a demo. We definitely didn't know how to handle a serious negotiation. And we had very few conversations coming in, so every single one mattered.

So we did what engineers do. We built a tool to solve our own problem. We built a little AI bot we could role-play with before each customer conversation.

We'd practice objections, work through tricky scenarios, get more comfortable with the language of sales. It was a hack, a workaround, a way to compensate for the fact that we were complete beginners.

Then we went to a conference in New York, and everything changed.

One of the CROs at a roundtable came up to my co-founder and asked, "How did you guys learn how to do sales?" At that point we had about ten customers, real revenue, and we'd only been at it for three months. He couldn't believe we'd ramped that fast.

We told him, honestly, that we practiced on an AI bot before some of our conversations. He looked at us like we were speaking another language. So I pulled out my laptop right there and let him try one of our role-play bots himself.

Keep in mind, this was early 2024. The latency was about fifteen seconds between responses. Today our bots respond in under a second, sometimes as fast as 800 milliseconds. Back then, fifteen seconds felt like an eternity. And yet, his mind was completely blown. He'd been in sales for fifteen years and had never seen anything like it.

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To us, this was normal. My co-founder had worked on some of the precursor models to ChatGPT. We'd been building conversational AI for nearly a decade. But that gap between what felt obvious to us and what felt revolutionary to him was the signal.

That night, we went home and built an entirely new product. The next day, we pitched it to every CRO at the conference. Every single one had the same reaction. So we launched it in January 2024, and it went completely viral. LinkedIn, TikTok, Instagram, YouTube, you name the channel.

About two weeks in, the CEO of Gong booked a demo on our calendar. Our qualification form asked, "How many reps do you have?" He wrote, "Enough." The second question asked if there was anything else we should know. He wrote, "We will crush you. Quit while you're ahead." And he signed his name.

We weren't even competing with Gong at the time. We barely understood what our own product could do. But that moment told us we were onto something real.

What we learned from two years of AI role-play

We spent the next two years refining the AI role-play product and deploying it inside some of the largest public companies in the world. LinkedIn. IBM. Autodesk. Companies with thousands of reps and complex enablement needs.

Here's the thing nobody warns you about when you implement AI role-play at scale: adoption is the hardest part. You can build the best practice environment in the world, but if reps don't show up to use it, none of it matters. You know practicing makes them better.

They might even know it too. But getting them to actually do it, consistently, is a different challenge entirely.

So we started thinking about the whole problem differently. We started asking ourselves what it would take to connect practice to performance in a way that managers, reps, and revenue leaders could all see and act on. That's the lens we now call revenue activation.