AI Selling Rewards Curiosity | Workflow Discovery with Seong Park

[upbeat music] Welcome to the Revenue Builders podcast, hosted by Jon Kaplan and John McMahon. This minisode features Song Park, SVP of customer support and services at Cursor, on one of the biggest shifts happening in go-to-market right now. AI selling rewards curiosity more than certainty. Song breaks down why the real work starts after signature, why workflow discovery matters more than a pilot, and what leaders need to understand about guiding customers from experimentation to real business impact. Let's dive in.

What about that-

Yeah

... AI champion you're talking about-

Yeah

... as it, as it relates to... I'm just gonna play the other side of it. I'm a CFO. I don't want an AI champion going out there and signing up 15 different AI companies, 'cause I got security issues. It's gonna get sticky in the workflow. So it sounds like it's gonna, by the very nature of things, customers are gonna try to push you into pilots.

Always.

So okay, so now it's even more, it sounds like to me, that our ability to really qualify, not just getting them to sign up, 'cause it can stay in an AI lab for a while.

Mm.

'Cause th- I would think that you guys gotta get it sticky, you gotta get it into something that impacts the business, it's gotta be a critical workflow, blah, blah, blah, all the stuff you just said. What... Tell me about the challenges of that as it relates to, you know, the go-to-market experience even, you know, pre-sales and post-sales.

Yeah. The former way of selling, um, rewarded certainty.

Yes. [laughs]

Right?

Yeah.

If you think about where we are in kind of the AI era, we're actually more rewarded on curiosity, on experimentation, um-

Yeah

... workflow discovery. How do we, like, manage all these things in a way that, again, is gonna be kind of unique to each customer and then, uh... And that's what I mean by the real sale starts after the signature, right?

Yeah.

'Cause then you get exposure to all the inner workings of a customer. So it's kind of like our responsibility to, again, understand those things and help them drive the experimentation, help them drive their own kind of curiosity to figure out, A, what does the shape of our engineering team look like? What does our workflow kind of materially change, right? Because instead of spending the majority of their time doing coding, guess what? That gets compressed, because you've got tools that almost remove all that, like, work that developers have been doing, but it gets pushed out into other areas of that development life cycle. It's change management, right? For decades we've been talking about change management with digital transformation, application modernization. This is yet another flavor of it, but it happens at such a velocity and scale that I think it's kind of a free-for-all right now. Because if you think about customers trying to figure out their own strategies on how to be more AI native, you have on one extreme, right, uh, we have a customer who's got, you know, uh, tens of thousands of, uh, engineers. There's a mandate to go and basically, um, use as many tokens, unlimited tokens, to go and, you know, build, right? And then you have customers who are doing this thing called, like,