GTM 148: Winning Every Tech Shift from a 3X Founder (From Internet to AI)

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Sean Whiteley is a three-time founder and the Co-Founder of Qualified, the AI pipeline automation platform purpose-built for inbound GTM teams. Previously, he founded GetFeedback (acquired by Campaign Monitor) and Kieden (acquired by Salesforce), where he also served as SVP & GM. With over two decades at the forefront of tech’s biggest transformations—from on-prem to cloud to AI—Sean offers a rare, long-term view on how to build companies and go-to-market engines in the face of massive disruption.

Discussed in this Episode:

• Why the speed of AI adoption outpaces every previous tech wave

• How the role of RevOps and team design is being reshaped by agentic systems

• Why today’s buyer journey is nonlinear, AI-assisted, and fully in control

• Tactical breakdown: how Sean mapped and tagged every task at Qualified for AI automation

• Why success teams must sit at the core of GTM strategy, not as an afterthought

• The most common GTM myth Sean is seeing today—and why it’s outdated

• The characteristics Sean looks for in long-term co-founders and GTM hires

If you missed GTM 147, check it out here: RevOps Is a Hidden Growth Engine with Navin Persaud, VP of RevOps at 1Password

Highlights: 

02:00 Sean’s journey through on-prem, cloud, and now AI

05:00 Ops leaders as the new AI orchestrators inside GTM teams

08:30 From workflows to autonomous agents: how org charts are shifting

10:30 The “two-way doors” mindset for fast experimentation

13:30 The future of GTM: agents, trust falls, and buyer-led journeys

15:00 From personalization to “relevance at scale” in modern marketing

18:00 AI unlocks speed and efficiency—how that reshapes CAC payback and TCO

24:00 How Qualified created internal AI blueprints across every team

28:30 Inside the AI SDR: replacing manual inbound sales with 24/7 automation

32:00 Success is not post-sales—it’s the center of the GTM experience

36:00 Reinventing yourself as a founder through three companies

39:30 What still hasn’t changed: customer value and trusted partnerships

47:00 GTM myth: “We control the buying process”—why that’s dead

51:00 Where Sean learns about AI: customer conversations > thought leadership

Guest Speaker Links (Sean Whitely):

• LinkedIn: https://www.linkedin.com/in/seanwhiteley

• Qualified Website: https://www.qualified.com

Host Speaker Links (Sophie Buonassisi):

• LinkedIn: https://www.linkedin.com/in/sophiebuonassisi

• Newsletter: https://substack.com/@sophiebuonassisi

Where to find GTMnow (GTMfund’s media brand):

• Website: https://gtmnow.com

• LinkedIn: https://www.linkedin.com/company/gtmnow

• Twitter/X: https://x.com/GTMnow_

• YouTube: @gtm_now

• The GTM Podcast (on all major directories): https://gtmnow.com/tag/podcast/

Sponsor

Trinet

Founding a company is hard enough. Navigating payroll, benefits, and compliance shouldn’t slow you down. That’s where TriNet comes in. They work with startups and scaling businesses to help take HR off your plate, so you can stay focused on building product, growing revenue, and hiring great people – the go-to-market engine. B2B companies like Hivebrite and Equilend trust TriNet to help handle the infrastructure of their workforce, so their teams can focus on execution.

The GTM Podcast
The GTM Podcast is a weekly podcast featuring interviews with the top 1% GTM executives, VCs, and founders. Conversations reveal the unshared details behind how they have grown companies, and the go-to-market strategies responsible for shaping that growth.

Visit gtmnow.com for more episodes and other interesting content.

GTM 148 Episode Transcript

Sean Whiteley: AI affords you the ability to question how you’ve done things historically, and there’s a new way to do it, and you have to start thinking differently.

we’re at the first step of a marathon

The great thing about operating today is speed.

there’s some very clear areas where the AI is just going to be better at this particular job function or set of workflows.

A buyer has more power than they’ve ever had.

The buyer has all the power and so now they’re going to go out and they’re going to do research and the AI or an agent is going to go out and do a lot of research for them.

What AI really does is it unlocks vast capabilities that are going to lead to doing things much, much faster and much more quickly.

It’s very clear that the future is not what it is today. We don’t know exactly what it is. But we need to go out and we need to run these experience and invest in these areas because if you don’t, you’re going to get left behind.

And the best teacher in the world is experience. Experience is the ultimate professor.

Sean’s journey through on-prem, cloud, and now AI

Sophie Buonassisi: This episode explores what it takes to build and scale companies during massive platform changes. Sean Whiteley, a three-time founder, shares what it’s like to build companies during some of the most pivotal shifts in tech history. I. From the on-premise and internet era to cloud computing and now ai, he shares our expectations.

Team structures GTM strategy and startup velocity have evolved across each era and what founders need to understand to succeed in this next wave. Sean is the founder of Qualified and AI pipeline automation platform for B2B companies. Previously, he was the founder of Get Feedback, which was acquired by Campaign Monitor in 2015.

He also founded Kaiden, a search marketing company that got acquired by Salesforce in 2006 onto the episode.

Sean, welcome to the podcast.

Sean Whiteley: Thanks, Sophie. Thanks for having me.

Sophie Buonassisi: Absolutely. I’ve been super, super excited for this conversation and I’ll jump right in. But you know, you’ve had a friend row seats to three of the biggest platform shifts. In tech, the internet era, the rise of cloud, and now ai. Can you walk us through how each of these waves fundamentally changed how companies are built and brought to market?

Sean Whiteley: Yeah, you’ve dated me a little bit, Sophie, appreciate that. Uh, sure. Yeah. I’ve been operating for the last 20 years, largely in enterprise software and almost exclusively sort of in the go-to-market area. I think the number one thing that’s changed is speed. And if you think about, you know, the way that when on-premise moved to cloud, right?

It sort of shifted the way everyone thought about the software delivery model. And everyone started to sort of question the ways that they had done things historically. And I think that’s happening again in a major way with, uh, this platform shift that we’re, you know, really just beginning right now. I mean, we’re all talking about AI and how excited we are about it, but at the end of the day, we’re at the first step of a marathon and I think we’re sort of in that phase where everyone’s starting to really. 

 Question the way that we’ve done things historically. And I think speed is number one. Things that have changed, like speed to value, speed to market. I think historically, you know, you walked in, uh, with an idea and a slide deck and then it moved into, hey, you need kind of a prototype now you’re expected to have an MVP.

So I think the speed and time to value is really sort of the most significant change, um, that I would point out.

Sophie Buonassisi: That’s a really great point. Speed. What would you say the biggest impact that has on overall go-to-market.

Ops leaders as the new AI orchestrators inside GTM teams

Sean Whiteley: Yeah, I mean, I think everything is being reimagined. You know, everything’s not going to happen overnight. Uh, everyone sees, everyone’s had that sort of. I’m on the moon at the moment with LLMs and sort of the capabilities and the intelligence that’s bringing, and everyone’s looking across their entire organization, not just the go-to-market.

They’re looking at product and eng and how, you know, my time to development speeds up. You know, just yesterday I had a conversation with one of my engineers and they identified an area of our stack that potentially had some risk and that instead of like. launching a barrage of battery test cases.

They wrote an agent that went out and sort of really did a lot of testing and they wrote it in a day. And like when you have those moments of clarity where you start to understand that. AI affords you the ability to question how you’ve done things historically, and there’s a new way to do it, and you have to start thinking differently.

And that applies to not only tech, but also your operations and your processes and your team structure. So I think at the end of the day, right now, everyone’s thinking about it. How have I done things historically and how is that going to change and what are the expectations? And I think so everyone’s really, you know, thinking outside the box.

It’s a really fun time to be operating because when you think like you’re not limited by some of the constraints you’ve had historically, uh, it really sort of opens up a huge array of opportunity for you. So it’s a really exciting time to be operating.

Sophie Buonassisi: Definitely. Definitely. And what role would you say ops or operations would play then if we’re imagining reconfiguring or potentially reconfiguring organizations?

Sean Whiteley: Huge. You know, when you get to be, as we talked about, seasoned, you have conversations with people earlier in their career, and I’ve always been a huge fan of people that come from an op ops background, whether it’s rev ops or mops or even engineering ops. Ops. They control the data, they control the systems, they control the processes, and so they’re going to be integral in.

this next phase of development for, for businesses. And I think that, as it pertains to, you know, the AI or agents. A big part of building agentic systems, which is very diff different than the systems we’ve built historically, is like, I almost call it like a trust fall. Like you have to sort of have that moment where you realize that the AI is going to be doing the work and you’re going to be evaluating the output from the AI, and there’s nobody better in a company in terms of who understands intimately.

A go-to market. Obviously given our audience today, who understands the go-to market better than the ops team. And so the ops team I think is going to be increasingly important in the role of a business as it relates to whatever function you’re sort of re-imagining with, with ai.

Sophie Buonassisi: I love how you framed that around. We’re actually focused more on output today. We’ve really focused on input and being the vehicles for that input, and now we’re actually on the other side. What else would you say from an organizational design perspective, are you either seeing or anticipating,

From workflows to autonomous agents: how org charts are shifting

Sean Whiteley: Well, I mean, I think the low hanging fruit and the thing everyone’s talking about is fewer people. You know, anyone who’s been an operator or owns a p and l understands that your largest expenditure, your largest part of your opex is W2. So obviously when you start to look at, you know, really sort of big teams you look at sort of like, is there.

An opportunity here to cut down on that W2. So obviously that’s where everyone starts. I think secondly, people start to take a look at. The tasks and workflows that these people are executing, and a lot of them are really ripe or really strong candidates for automation with AI in any, any language tasks.

Anything as it relates to having to traverse across a vast amount of data. You know, these are things that the AI is just going to be significantly better at. And now if we’ve moved into this world of. Sort of understanding some of the capabilities afforded to us by LLMs and language models, and then moving into sort of building some of these AI workflows and automating some of these workflows and now building fully autonomous agents.

You know, you start to really sort of take a look at your organizational structure and your teams and you start to sort of. See the future in terms of like, there’s some very clear areas where it’s, it’s a given that the AI is just going to be better at this particular job function or set of workflows. And then I think what that’s going to lead to next is a very big transformation in terms of some core processes and operations that we’ve been using historically.

We talk about it at our company, at Qualified, we talk about. how we do demand gen, how we do pipeline generation, all the tasks and workflows associated with all the things that marketing teams do. And we’ve kind of broken them down into this massive, massive list of segments and tasks and workflows.

And we’ve kind of tagged them for like, what are the ones that are just clearly going to be better executed by the AI or by an agentic layer. And you know, once you do that, then you start to get into, wow, it’s not just the systems and the tech that’s changing, it’s not just some of these workflows. It’s like.

The entire thing is going to get rewritten. So, you know, much like I draw a lot of parallels to, to cloud, and, you know, our first company was acquired by Salesforce and that was kind of early days in cloud. And what we were doing back then was we weren’t talking about features and functions. We were talking about things like multi-tenancy and shared infrastructure and, TCO and, and just the fact that this software delivery model just unlocked a lot of things.

And that’s kind of the world that we’ve been living in cloud for the last, you know, 20 years. A lot of that is happening again. A lot of that unlock is here. Uh, it’s starting to become clear that a lot of the things that we’ve been doing for the last 20 years are going to change significantly. It’s going to take time, but I.

The “two-way doors” mindset for fast experimentation

The great thing about operating today is speed. I mean, you can do things very quickly and one of the things, one of the conversations we have a lot with my founding team is we talk about one-way doors and two-way doors. You know, a two-way door is something you can walk through. You can try it. If it doesn’t work, you can walk back through the door.

If it’s a one-way door, it has larger implications, broader implications you probably wanna talk about a little bit before you actually go through that door. Right now there’s more, two-way doors than ever. You know, you can really, the time for you to do something. So fast, it’s faster than it’s ever been in the history of software.

So experimentation, trying things, trying to sort of get feedback from your experience with it. You know, your feedback cycles are faster than they’ve ever been. So it’s, uh, you know, again, I, you know, I keep coming back to this. It’s a really fun time to be operating, but at the same time, you have to be cognizant of the fact that there’s a lot of unknowns.

You know, we are, we are really, really early in this journey. Then again, it’s moving faster than any sort of shift I’ve ever seen.

Sophie Buonassisi: There’s so many different routes. I wanna go down, Sean, but your last point there, it’s faster than you’ve ever seen. How does this compare with other major shifts that you have experienced?

Sean Whiteley: You know, a platform shift is something that happens, you know, not very often. You know, you’ve seen, you know, the internet, electricity, steam engines, like these are, these are sort of platform shifts. And now when you think about, you know, cloud, what, what cloud really did, was it, it, it changed the software delivery model and it sort of highlighted immediately all of the shortcomings of on-premise.

And as soon as people started to understand that, they started just doing things differently. As an example, everything moved to the web. You go to the web for everything, and as a result of everyone going to the web, all marketing becomes digital. All marketing became trackable, and everything kind of grounded in that.

Now we’re entering a world where a lot of the work and the research and the buying process is going to be executed by the ai. For instance, you’re going to use deep research. You’re going to go out and you’re going to do a lot of research, and that’s the thing I. Our core premises in our company is that the buyer is in control of a process.

You know, people in the go-to-market that think they can control a buying process that’s becoming less and less true every single day, and now it’s completely gone. The buyer has all the power and so now they’re going to go out and they’re going to do research and the AI or an agent is going to go out and do a lot of research for them.

And of course they’re going to talk to their communities and their peers and they’re going to talk to customers and they’re going to do their own research. They are very much in control of a buying process. And as a vendor, you know, we can influence that. We can do the right things, which is build a great product, make sure that we’re really driving enterprise value, make sure that we’re giving them the level of support they need, as it relates to our product, but the buyer is in control.

The future of GTM: agents, trust falls, and buyer-led journeys

And I think that more and more in this new world. People are going to be evaluating outputs of the AI, and they’re going to take that and they’re going to refine that, and they’re going to give it back to the AI. And they’re going to be just really, you know, whether you’re coding something, designing something, building a process, building a system, you know, again, that trust fall.

The AI is really doing the work, and it’s our job to make sure that we give the AI, the data, the context, the moderation, that it really needs to execute things well.

Sophie Buonassisi: The buyer is in control of the process. I love that. What does that look like tactically for you as Qualified?

Sean Whiteley: So we’ve, we’ve always sort of had this, when we started the company, we talked about this at length in terms of if you’re buying a blender or you’re buying enterprise software, you know, we always used to go to Google. There used to be a statistic that said. 82% of buying processes started with a Google search.

And you went to Google and you started doing some research and you got these blue links and you clicked on them. You did some research, you’d go to the website, you’d read a little bit of information, you might do a trial, you might download some content. You also go to your communities, you know, and the marketing community is very powerful, right?

You go and you talk to people about their experience with this company or this team, or this product, or this service. You gotta read reviews on G2. so there’s, the buying process today is not very. Reminiscent of the buying process even, even of 10 years ago. And so we’ve talked about sort of this idea of personalization.

From personalization to “relevance at scale” in modern marketing

We like the holy grail for market marketers, of course it is the right time, the right message, right person. But what’s happening now is that it’s a collection of experiences and you can’t, it’s, it’s not linear and it’s not something that’s structured. It’s this crazy, messy. Squirrely diagram of all these different interactions and experiences that span lots of different channels and lots of different areas.

And the number one thing that you can do is you can make sure that. You try to create relevance. So one of the things we talk about here is relevance at scale as opposed to personalization at scale. And we know that AI is going to unlock a lot of capabilities as it relates to creating bespoke experiences on a one-to-one individual basis.

But it’s gotta be organic and it’s gotta be buyer led. We really think that the buying process is a continuous conversation. It’s a conversation between yourself and a buyer. It’s a conversation with a buyer and their community or their team. So it’s kind of one continuous conversation that spans a whole bunch of channels with a lot of different inputs, and really, again, it’s very buyer led.

A buyer has more power than they’ve ever had.

Sophie Buonassisi: Mm-hmm. And going back to speed, you probably have. An increase of speed too to understand the buyer process and how it’s evolving.

Sean Whiteley: Sure. I mean, you know, we, we’ve, we’ve talked about speed to lead. You know, speed to lead is certainly one of those things that marketers think about a lot. There’s many statistics that talk about, you know, the faster you get there, the, and serve somebody’s request, the more likely you are to convert.

But I think. Speed applies to everything now. Speed applies to, you know, time to value, time to market, time to get back to a customer, time to get them, you know, connected with the information that they’re looking for. So speed, I think, is probably the number one word I would use to describe the implications of this platform.

Shift, obviously intelligence, but what that’s going to lead to is speed and time to value. And I think that’s what every company right now is starting to understand and they are really sort of investing in the areas of unlocking. I think in terms of what AI really does is it unlocks vast capabilities that are going to lead to doing things much, much faster and much more quickly. And I think that’s going to be, again, that’s going to manifest in the expectation from a buyer that things happen in real time. So the world of asynchronous. It’s going to have its place, but you know, again, real time, hyper personalized on the buyer’s timeline and on the buyer’s terms. That’s the world that we’re, that we’re living in today.

Sophie Buonassisi: You mentioned TCO and other areas were really the focal points and nobody’s talking about features and functions. Now they are. What do you think our next era is if we’re not talking about features and functions from a revolving forward from that?

AI unlocks speed and efficiency—how that reshapes CAC payback and TCO

Sean Whiteley: I’ll draw some parallels. The economic ramifications of AI are maybe the most important thing to think about. Anybody who’s operating a business, anybody who’s an operator. You have different challenges at different times and different stages in the business.

Like first and foremost, you’re trying to find product market fit. You’re thinking about distribution, right? It’s one of the biggest challenges any sort of startup has. But at some point you also start thinking about tried and true health metrics of the business. You start looking at cac, payback periods and ASPs and you start looking at your burn multiple.

You start thinking about the rule of 40. AI really unlocks efficiency. So the other thing outside of speed is efficiency. So the ability to do things that you need to run the business but not, you know, pay. A tremendous set of w twos to get that done. It unlocks efficiencies and scale that I think is really going to be a game changer for, for companies.

So, you know, speed and efficiency, you hear these terms a lot. We’re all talking about AI all the time. These become buzzwords, but they’re real as an operator. If you own a p and l, you think about these things and I think, the future is going to be a very different shape when you think about an A team or an organizational structure.

Sophie Buonassisi: And the shape will look different. What about measurement? How do you anticipate those expectations shifting? Even if it’s from a. A timing perspective, maybe we’re going monthly, quarterly to weekly, for example.

Sean Whiteley: Yeah, like I said, the expectations are changing. You know, over time, one of the things that’s changed is we’ve had more capabilities, right? Like at first we started building, you know, back in the day, right? You, you know, we. At my first company, we shared a rack of servers. We went to the data C center and assembled rack-mounted servers.

That changed very quickly and, you know, software became a service and then you got infrastructure and platform as a service, you know, and now you have large language models that everyone has access to. So everyone’s starting to think about. You know, how does this change and how, you know, how things are measured?

I think everyone’s going to, everything’s going to get stepped up. Expectations are higher. Like I said, you know, it’s when you can actually open up an application, give it some prompting and some inputs, and what it can actually spit out for you is, you know, again, 10 years ago, we, it would’ve completely blown our minds.

Now I think it’s an expectation that you can have, you can go from. Idea to wireframe to code in hours. In hours. So that expectation is going to change some metrics, especially as it relates to time to value. But you know, some of the metrics are going to remain the same depending on what area of the business you’re in.

You know, you’re still measuring things around objective and subjective measurements. You’re measuring things like if you’re in the go-to-market. The tried and true values are still going to be there. Do I have pipe coverage for my sales team? Right? Like, how, how is my sales team executing against their quota?

Like, these, these are all things that, you know, are going to remain constant, but what might change is the quality of your pipeline, how you measure that. I. other things people are talking about of course, is pricing models. You know, pricing is going to be more aligned than ever to value. So, you know, any platform shift is going to cause people to question everything.

And part of that is going to be metrics. and I think that will all sort of, you know, come to light over time.

Sophie Buonassisi: Definitely, yeah. I’ve heard some stories of measurement being expected by alternative investors, for example, now on more of a week, over week basis, even just to have that purview as opposed to purely monthly or quarterly. Super interesting to see. Have you shifted any of your qualifications?

Sean Whiteley: We, I mean, we’ve, again, we’re six years into this business and we are starting to sort of operate at a larger scale. So we certainly and it’s been a wild six years for anyone who’s been an operator. You know, we had, you know, a. A global pandemic. That was a new one. We had the great sort of correction we had during the zero interest rate period.

We had the banking crisis and now we’ve got tariffs. So it’s been a topsy-turvy ride. And of course, on top of all of this, uh, maybe the biggest platform shift anyone’s ever seen in the history of their career has just happened. So it’s been a wild ride. And I think one of the great things about being at a.

At a smaller company at a startup is that you can pivot and you’re pretty agile. And so change can be a big enabler for you. And so, we’ve changed a lot and we probably changed more in the last 18 months than we did the entire history of the company just based on what was happening in the world and accommodating some of these things.

So yeah, we’ve changed a lot and also we’ve also changed our values, you know, I mean. You go from growth, growth, growth, new logo expansion, thinking about top line, and then you, you know, during the sort of downturn for tech, we were thinking about CAC payback periods. We were talking about efficiency metrics.

We were thinking about extending our runway. We were thinking about, you know, where we need to be burning and we always invest in engines. Product development never stops, but at the same time, on the go-to-market, you wanna burn more than you need if people are not, you know, buying. So we’ve shifted a lot as it pertains to the environment, but the last 18 months we’ve made probably more changes than I’ve ever made at any company because of the shift that has just, you know, kind of come into our industry.

Sophie Buonassisi: I wanna dive quite tactically here. Sean, you mentioned previously that you are tagging. Different initiatives and really mapping out the entire organization, seeing what can we actually implement AI around? What does that process look like? If someone, you know, another founder, for example, were to wanna do a similar exercise, you know, how often are you meeting who’s involved in those meetings, and how often are you actually deploying these new AI strategies across the org?

How Qualified created internal AI blueprints across every team

Sean Whiteley: We’ve challenged every single one of our leaders to have a blueprint for, hey, how AI is going to impact their various organizations. And that spans the front office and the back office. So everything from product and engineering, uh, hr, recruiting IT security. marketing, sales, sales ops, mops, support everything.

Everyone has to have a blueprint, and we’ve also freed up an experimental budget for them to sort of go out and invest in things that will help them to understand and learn and educate themselves because it’s very clear that the future is not what it is today. We don’t know exactly what it is. But we need to go out and we need to run these experiences and invest in these areas because if you don’t, you’re going to get left behind.

That’s really clear. So we made it a mandate for every single one of our lieutenants across our business to sort of have a blueprint and a map for how they’re going to transform with the capabilities that we have today. as that relates to, what we do and the products that we build, again, when you use ai.

You have to have domain expertise. There’s a lot of companies out there who are building AI products, and that’s great. If you don’t have domain expertise, it’s not going to be great. And I think that’s one of the fundamental things that we try to create a lot of rigor around is staying close to what we do, the data that we have, the processes that we know intimately, and not sort of straying out beyond that.

And so we’ve all had that experience with ai. My first experience with AI that kind of blew my hair back was mid journey, and as soon as I got into mid journey, I, my, I was. Blown away, right? Another walking on the moon moment. But then you realize that, you know, if you don’t understand how to prompt it, if you don’t understand how to give it the guidance and the context that it really needs, the output is not going to be nearly as good.

Right? You have to know how to say shallow depth of field, 50 millimeter fixed Boca. If you know all of these sorts of concepts and you’re a photographer or designer, you’re going to, midjourney is going to be a great tool for you. And that’s that, I think that’s a good metaphor for all ai. When people are building AI applications and agentic systems, you have to have the data.

You have to give the AI all the context about the data, and you also have to again, build out all the moderation and trust that it needs to be working off your enterprise data. So the last 18 months, I think we’ve learned a lot and changed how we operate quite a bit. But also again, you know, you’re, you’re sort of building for a future state.

You’re building for a future state and that sometimes is not a good fit for the way that companies have been operating for the last 20 years. So that change and that transformation is hard for businesses. So we’re cognizant of that fact. And what we’re trying to do is build systems in a way that enables a company to sort of.

Ease into, or move into some of these new ways of doing things, uh, without disrupting their business because it’s not like you can stop what you’re doing today. So again, it’s not like an overnight thing

Sophie Buonassisi: And not to make this a Qualified plug, but you are at the forefront of ai. Building Qualified in AI.

Sophie Buonassisi: pipeline automation platform. I appreciate any kind of company or person that is really helping educate because it is challenging and everybody gets their own mandate and has to go out and source that information.

So I actually watched the AI SDR Summit and that was extremely informative. Everything from even pricing AI agents and how to think about that. So. I’m like what, what are you seeing since you are at the forefront of the AI space, especially for AI, SDRs?

Sean Whiteley: Yeah, we were a bit lucky. We had a very, very natural entry point into this. For one, we’ve been building conversational interfaces since day one, and you know, again, you know, ai, UX is going to change dramatically. Sometimes it feels like I. A natural language interface is a bit like the DOS era of AI, but at the same time right now, like everything has a natural language interface.

Inside the AI SDR: replacing manual inbound sales with 24/7 automation.

Like you have a natural LA language interface to apps and data and reporting and you know, a natural language interface is kind of how you talk to the AI. And we sort of had, we already had a pretty significant presence in terms of companies who had our conversational interface connected to their go-to-market systems and data and processes and operations and teams and already deployed in production. So we had this really nice entry point as it relates to building LLMs and AI workflows into the product. And our premise from day one was that, you know, the SDRs early in their career, they are what’s standing between a buyer and a seller, you know, which is an interesting concept and.

Historically, they were given a hammer and a nail email and calendar and said, go do band. we felt like there was a lot of data out there that was very relevant for these people doing this very hard job, but we needed to go surface it to them in a meaningful way. So data from. CRM systems, marketing automation systems, a BM platforms intent systems, B2B advertising systems.

Like how did they get there? Who are they? Are they in RSCP? What’s our relationship? Are they in a key industry? Are they looking at my high margin products? Are they an open opportunity? Like, all these things are things that would be really great for the SDR to know, but there was no way for them to know it.

So we spent the first six years trying to aggregate data from disparate systems and surface it to me in a meaningful way to the SDR. Now we’re taking the SDR out. We had a very natural entry point into data aggregation workflows and really gave the SDR context for the job that we’re trying to do.

Now we’re giving the AI context for the job it’s trying to do. So we had very natural entry points, right? We sort of understood how companies were set up, how they were operating, what their team looked like. What, what, what they needed to be successful. So now really what we’re doing is it was, you know, again, I’ll call it lucky.

We already had a very significant presence where we could actually start to, test and trial and run our A-I-S-D-R. And it didn’t take long for us to figure out, this is just a great place to start. A lot of language tasks, a lot of system updates, a lot of, sort of trying to traverse a lot of different data that lives in different places.

And an AI SDR speaks every language 24/7. You don’t pay their W2. So, you know, we work with companies in a variety of different ways. Sometimes they wanna replace this function over time, and sometimes they just wanna drive more efficiency into the team that’s doing this job already and allow them to work on higher value activities.

So you know, at the end of the day, again, it was just a very good entry point for us. And we are very focused to be clear on inbound. So, marketing, so our, our, our SDR Piper is inbound. It serves the marketer, it serves the CMO. There’s a lot of people focused on outbound. And that’s another big challenge, big opportunity.

We’ve chosen to sort of stay very close to, you know, mops and, and marketers as it relates to sort of inbound workflows that can be automated with ai.

Sophie Buonassisi: That’s fantastic and I do highly recommend if anyone hasn’t

Checked out AI SDR Summit. It is free on demand. It’s an amazing resource. There’s different tracks, different topics, but Sean, we’ve talked a lot about what’s changing and what has changed, what hasn’t changed, what have you seen kind of remains true.

Success is not post-sales—it’s the center of the GTM experience

Sean Whiteley: It is a great question. I mean, you know, everyone is so consumed with the change that that’s happening. You know, some, some things still remain tried and true. You know, we always think about for one, look, we, we want to make sure of that. What we’re building is providing a VA value for a company, and I think over time.

One of the things I’ve learned in my career is that there’s a lot of incentives within a company in terms of the way a company runs that are not necessarily aligned. And you think about like a sales organization and how they’re metriced and how they’re measured. One of the great things about sales is it’s very measurable.

It’s something I’ve always really appreciated, like sales. Sales is fun, it’s exciting, and it’s. Highly measurable marketing ever since it became digital. Very measurable, right? I mean, we do out of home things as well. If you drive one-on-one, you’ll see our billboards. I have no idea how well they’re working hard to track.

But at the same time, marketing is pretty, pretty measurable. And when you think about all of the functions across a company some are more measurable than others, but at the end of the day, you’re still trying to. Build a great team, build a great culture. You’re trying to make your customers successful.

A number one, what you want is you want your customers telling all of their community that like I. I invested in this, I partnered with this company. Everything that they said has come true, and these are the returns that we’ve gotten from it. That’s the number one thing you want. Nothing makes a founder happier than hearing one of their customers presenting.

I was at a marketing event recently, and I saw something unprompted. A CMO talking about some of the things that’s really worked for them as it relates to ai, and they presented a bunch of metrics and data about, about Qualified and it, it made me supremely happy because this was not something we partnered with them about.

And really that’s what you want at scale. You want someone saying like, everything that they said came true. And I think his, and I think the other thing we think about differently is we don’t think a sales process changed when you, when it’s closed one. This, that’s the beginning. And we’ve invested pretty heavily in a success model that, to be honest, we’ve had to defend from time to time in terms of the CAC and the opex.

’cause it’s expensive for us. But at the same time, we believe that enterprises need a partner beyond software and technology. They need someone who can help them operationalize it, help them solve problems, and help make sure that this thing is in a place that it needs to be for their business. The success function, you know, I think oftentimes gets talked about differently than a sales process.

We’ve tried to put them as closely as close together as possible. Not for expansion, but just for the entirety of the sort of holistic view of a partnership model as it relates to software.

Sophie Buonassisi: And if you’re, you’re comfortable sharing completely. Okay. If you’re not, what kind of allocation or breakdown would you say that you have for CS compared to maybe pre-sales, like sales as a function or marketing?

Sean Whiteley: Yeah. You know, I, in, in terms of, I’ll just say this. We, my first two companies were bootstrapped, and this one is venture backed. Uh, we’re series C and we have investors that we really rely on not just for capital, but for advice. You know, we work in the business and they work across a variety of different businesses.

They have a big portfolio, just like you guys have, you know, the GTM fund. You guys have a Large swath of companies you work with at different stages and you work with your operators and you try to help them as much as you can. And so one of the things that we’re very, we’ve talked about at length is the investment we’ve wanted to make in our success model.

We wanted one of our tenants when we started the company. We said we wanted to have the world’s number one success team at our company. So that. They have a trusted advisor to help them with what they need. And that doesn’t necessarily mean a hands-on keyboard. So we certainly don’t wanna be a services business.

Reinventing yourself as a founder through three companies

We’re a product company, first and foremost. Product is the number one thing. Trust is our number one value. Product is number two always, but the success model that we have is a big investment financially for us. And we have had to defend, uh, that model. And I’ll continue to do it till the end of time because it’s really been a good motion for us in terms of just building that relationship with our customers that I think you need to operationalize software at scale for a global enterprise.

Sophie Buonassisi: Definitely and the economic downturn. To pandemic, I think really shifted perspectives and opened eyes up, investor eyes, all eyes to the power of CS and the importance of looking at CAC payback periods above just a pure acquisition line.

Sean Whiteley: Yeah, a hundred percent.

Sophie Buonassisi: What about, you know, digging into that founder journey, know you’ve bootstrapped and sold two companies to date, you’re now a series C venture backed founder of Qualified. How have you had to kind of reinvent yourself as a founder throughout these three journeys? It takes a special person to go COVID journey three times.

Sean Whiteley: Yeah, we’re a bit of a unique animal in that we’ve got a really close knit team that’s been together for a really long time. Uh, I’ve been with my co-founder Craig for. 27 years now. Uh, we started in on-premise together in integration infrastructure, and we’ve been together ever since. We also have two technical co-founders, Copa and Bing.

They’ve been together, we’ve been together for them for our last two companies. So we’ve spent a tremendous amount of time together solving a variety of problems. Uh, we have a really natural. sort of divide and conquer mentality. We all know what’s best suited for each person in terms of who should take ownership of what initiatives within the company.

So we have a really nice and, and when you get older, you have a network. One of the nice things about being venture backed is that you have capital to go and hire the amazing people that you want. So, over time we built out a really great network. We. We’ve been lucky enough to work at some great companies like Salesforce in the early days.

Tremendous talent pool, the tremendous learning process for us.Seeing Salesforce kind of go from that, you know, 2005 to, to the 2000, you know, I. 13, 2014, very sort of pivotal experience to be there. So we’ve been able to go out and pick top talent to bring into the company and we have the money to pay them, which is great.

Of course you have a lick pref stack on your head now, but that’s okay. So it’s a very different journey and I think, uh, and there’s so many differences for one, when you’re a first time founder. You have this almost admirable aggression. You know, you, you just don’t know a lot. How could you, you’re probably pretty early, but you’re brazen and that’s fantastic.

It’s great hair on fire and you can, you know, your, your appetite for wrist is really big. And that’s great. And I think that’s a really special thing about a first time founder but you’re learning a lot. And the best teacher in the world is experience. Experience is the ultimate professor. And I think in our second company, we learned a lot of lessons.

What still hasn’t changed: customer value and trusted partnerships

First and foremost, we built a CX company. It wasn’t, it wasn’t our passion. To be honest, we had a great product, we had a good exit. It wasn’t our passion. Uh, so when we started Qualified, you know, we said we need to do what we know and love. And that’s, you know, working in the go-to-market, working on MarTech.

And so we feel really at home in this problem. And I enjoy the conversations I have every day. I spend a lot of time talking to the C-suite, talking about the problems that they have, the challenges they have, the things they’re thinking about, how they’re thinking about AI as it relates to what they’re trying to do.

And. I really enjoy the conversations and when you, when you’re invested in these, conversations to the degree that you’re, you’re enjoying it, it makes a world of difference in terms of, you know, how hard you’re willing to work and how well you can execute. So, I think the number one lesson I’ve learned over time is that, you know, you really need to love it.

You really have to have passion for it. It sounds goofy, it sounds cliche, but you know, at the end of the day, it makes, uh, it makes your job a lot more fun.

Sophie Buonassisi: Definitely, and that really is the journey, right? The day in, day out work. And for listener context too. After Sean and Craig’s, uh, company was acquired by Salesforce, both went on to spend over six years at Salesforce, and Sean served as SVP and GM over at Salesforce. Sean, it’s very rare. Somebody will go on the founder journey three times with the co-founder. And what character traits do you think or would you advise others to look for in a co-founder that are really going to distance together?

Sean Whiteley: A co-founder is extremely important. I mean, maybe the most important decision that you make. And again, you know what, what we’ve learned very early on is we have our own culture at our company and we have our own sort of dynamic. When I first met my co-founder back in the day I saw him operate from afar and was pretty impressed just at just his capabilities and what he was doing.

I was a big fan, and we finally got to work on a project together, and it was like an all night POC at Sony Pictures Entertainment. I’ll always remember it, and I watched this guy and I was like, this is a guy that I, I am impressed with and I really like him and. We enjoy working on this problem together all night.

By the way, it was an all-nighter and you know, we sort of decided back then we saw a cloud coming and we said, you know, this is going to be pretty huge. Had that walking on the moon moment with SaaS where, you know, instead of installing, you know, drivers and software, I just went to a browser. Salesforce was there, I saw it.

I built out a workflow and I was like, oh, this is it. Like this is it. And so we quit and. Inked basically within 90 days of that sort of aha moment.

Sophie Buonassisi: Wow.

Sean Whiteley: And we sort of have a, we’ve, we’ve established a cadence, so we typically. Do it. We, we ink, we have like an ink brand.I’m usually the catalyst for getting the team together and the way I get them to stop what they’re doing and jump into a startup is I start paying rent and tell the, and send them their portion of the rent and that gets them in the office and we start, we start banging on the problem.

And then again, like, just to give you an idea as to what, how things have changed. When we started Qualified, we walked in, for some, we ran a process for some seed. We walked in with a prototype that was working and we actually had some people work, like using it, and they were like, wow, amazing. I can’t believe you guys have this.

that’s not going to cut it anymore at all. So I think, uh, back to sort of your question about the dynamic, choosing a founder is important because they’re going to be with you for the entire journey. The idea of having a co-founder largely, sometimes it’s, uh, someone on the business side looking for a technical co-founder.

That’s sort of a different sort of arrangement where it’s, there’s a clear lines of delineation. We have a four founder model here. So we’ve got Bing and Gopal on the technical side of the house running product and Eng. And then Craig is the CEO. And then we spend a lot of time on every other area of the business.

Outside of eng in product, but we all coalesce around the product. The product is the number one thing that we focus on. So we coalesce around the product, but everyone else has their clear areas of responsibility. And when you’ve been working together as long as we have, it’s very clear what job should be owned by what, what sort of person.

So it’s a, it’s a, it’s a luxury that we have because I talk to a lot of people. Or interviewing a co-founder, trying to find a co-founder when there’s already an organic sort of team in place, gives you the ability to get to work.

Sophie Buonassisi: Going back to speed can move a lot quicker. Was there ever a time throughout the three companies that you thought, this is going to be the last one we all work on together, or you didn’t anticipate starting a third one together?

Sean Whiteley: Yeah, great question. You know, so after we exited our last company, we did take some time off operating, we’ll give you gray hair as you can see. So we did take some time off. We took about a year off. and actually at that time, I. The hot thing was crypto. And so a lot of people were really thinking about that.

Our Bing and Gopal were coding crypto and they were sort of immersing themselves in that world. I took some time off. I’ve got two young daughters and I, my wife at the time, was general counsel for, for Block, for Square. And uh, so she was grinding pretty hard and I took a year off and just sort of reset and, uh.

Had a great time just, just not building software. And during that time we started talking about some different ideas and sort of, we started to come up with this concept that everything’s going to change here. And this was before ML was the thing. But what we saw was there’s a big change coming and we like this idea of this ongoing conversation.

So conversation was something that we really had. Thought was powerful and we wanted to apply it to enterprise go-to-market. We had seen conversational products. To be honest, Intercom was really our inspiration as product builders. When we used it, we were like, this is great. It’s connected to our data and our systems.

It’s a real time natural language interface where we can talk to our users. We really love the concept and so we wanted to apply that concept. So we just decided that we. We had too much passion for the idea, and we were also a little bit too young to retire, so we decided to jump in.

Little did we know we’d be in for a wild ride that we’ve been on for the last six years, but it’s been, it’s been an extraordinary experience and I’m glad, glad we did it.

Sophie Buonassisi: That’s incredible. We’ll love to see the progress. You guys are doing tremendous work in this space and really appreciative of the educational AI content that you’re doing too.

Sean Whiteley: Yeah. Yeah. Our, our pleasure.

Sophie Buonassisi: Now last two questions, Sean. Always the same. is, and we have actually talked, touched on this a little bit, but what is one tactic or strategy that’s working for you today at Qualified?

Sean Whiteley: Yeah, I think, like I said, you know, we, we did touch on this. I think the value we’ve placed on a partnership model I think is really important. And I think it’s worked really, really well for us. Again, our first two companies, we found product market fit. We had good exits. We had never really made the investment that we needed to, to really work deeply with your customers.

And what we’ve found is that it’s yielded. A lot more than just N-R-R-G-R-R and NDR, like a lot more, you know, you have, you learn so much from your customers, you know, especially when you sign up great customers, you can learn a ton from them. And customers drive our roadmap. Customers, customers drive what we’re doing, where we’re putting resources and investments.

So our success model, I think, and you know, Dan Darcy, who runs our success team, has done an extraordinary job, all that entire team. They have the values that a founder wants to you. You want your team to think like a founder. That’s what we say all the time. Think like a founder and founders are willing to go the extra mile.

And I think that our whole success team has that mentality. So it’s been really great to see the energy that they’ve brought, you know, and not as it relates to, to NDR and things like that, but as it relates to just the relationship we have with our customers. So I think that’s worked really well for us.

Sophie Buonassisi: And this is almost the inverse of what we’ve discussed around what’s actually working for you, but what is one widely held belief that revenue leaders hold that you think is bullshit or no longer serving us?

GTM myth: “We control the buying process”—why that’s dead

Sean Whiteley: Yeah. Something I think has been withering for a long time, but I think has just completely gone off a cliff, is that the go-to-market could control the buying process. It is not linear. It is getting farther and farther from that. The buyer is in control and when I look at the systems, even systems of record that some companies are using right now, when you look at things that are journeys or templated or scripted, uh, that world is gone.

It’s gone. You know, systems, now they’re instruction based, they’re AI driven. Everything is going to be one-to-one personalization. Like the best segment is a segment of one, and everyone is an N of one. Now. So all of the things that we’ve done historically, the systems, the processes, the operations, they’ve all sort of been in this world of trying to script out a linear buying process.

And I think that world is absolutely gone. I think it’s been withering for a long time. I think it’s completely gone now, and I think that over the next, you know, five, seven years, I think Ag agent systems are completely going to disrupt the way that companies think about the go-to-market entirely.

Sophie Buonassisi: I love it. And you are at the forefront of AI building Qualified. Where are you really sourcing a lot of your education around ai?

Sean Whiteley: A lot, A lot of, so one of the cool things about selling, we sell into a lot of companies that build SaaS software, so. A lot of high tech sa it’s, a lot of our customers. And what’s great about that is they’re all building AI products. They’re all on their own AI journey, either from a product and ENG perspective, or from an operationalization perspective.

So I’m lucky enough to spend a lot of time talking to our customers and learning from them about how they’re using ai, what’s working, what’s not, where they’re, where they’re thinking about investing. And you know, that spans the gamut from. How do we evaluate it? Like what are our expectations? What has our experience been?

So I learn a lot from our customers. I do spend quite a bit of time. Listening to long form media, I’ve listened to a lot of your podcasts, some really great ones. I also spent quite a bit of time on YouTube at the beginning. So I really want to ground myself from several different areas. So one real world production AI, which is what you, the conversations you have with your customers, but also what’s coming, you know, it’s every single day you hear about something new and different, and.

I do it for a variety of reasons. One, I certainly don’t want to get into a world where we build. I wouldn’t build anything horizontal right now. You know? I mean, right now, the way that these companies are moving, you certainly wouldn’t put yourself in a position where you can just get run over by, you know?

Where Sean learns about AI: customer conversations top thought leadership

One of these large language model providers, you don’t want to get into their world, but at the same time, you wanna really understand the real world implications of what’s happening. And oftentimes there’s a big disconnect between what people say and actually what happens when you get into production.

So I want to be grounded from both sides. So I want to hear about the vision. I want to hear about the art of possible. I want to hear about what’s coming, but I also want to hear about what’s happening in reality, what happens behind the firewall. So I try to ground myself a little bit with one foot in both worlds.

Sophie Buonassisi: That’s fantastic. And Sean, where can people find you if they wanna get in touch or follow your journey?

Sean Whiteley: I mean, you can find me on LinkedIn, of course. You can always shoot me a note on email, Sean, it Qualified. I’m happy to talk to you unless you’re prospecting.And then at that point, I may not reply. Bbut you know, LinkedIn is always a great way to get in touch with me. I’m always happy to connect with people on LinkedIn.

Sophie Buonassisi: I love it. And with that actually, what advice would you say if people were trying to prospect a co-founder of a company or. Company of your, your stage, like what has stood out to you?

Sean Whiteley: It is pretty funny. I do find myself, for one, I have a lot of respect for the job that they’re trying to do. I never hold any ill will from people trying to prospect and get connected. But I always do find myself saying, now, why would you send this note to me with this content, with this subject line?

I always find myself sort of critiquing the outreach a little bit. And so for one, the, a founder is oftentimes not the person who would actually buy the software that they’re trying to, to, to sort of speak to me about. It would be someone within my team. More often than not, uh, I think that outreach is, uh, is poor because it’s not right.

Time and it’s not the right person. So I think that that’s pretty easily remedied.I do find myself critiquing it a little bit, but you know, at the end of the day, founders are going to approve. A purchase or I may potentially influence a purchase, but more likely you should be going to the head of that line of business, uh, to try to get connected to them.

But I do appreciate a lot of times, some of the tactics companies use to get connected. I appreciate the hard work.

Sophie Buonassisi: Definitely yeah. Interesting to observe different tactics, and you’re solving it for the inbound motion and like a lot of companies are trying to tackle that outbound. So hopefully we’ll see

Sean Whiteley: Yeah.

Sophie Buonassisi: timely, relevant messages coming soon.

Sean Whiteley: Yeah, we talk about. We refer to inbound as the Glen Gary leads. These are people that legitimately are interested in running a process and they’re running an evaluation and they’re doing their research. They’re doing their homework, they’re doing all the things to educate themselves so they can make an informed decision about a need that they really have.

We love inbound, outbound, different animals. Very important, right? But it’s a really hard problem to solve. Outbound is, has historically been really challenging, but you know, you’re going to do it. And I think that, you know, given the capabilities that AI brings to outbound, there’s going to be a lot of calories spent on it.

We feel really comfortable in the inbound world. We think these are really high value engagements and interactions. And we feel like we’ve got a really good mode there. So we, we, we like to sort of stay in the inbound world right now.

Sophie Buonassisi: Excited to keep following your journey and everything that you’re building at Qualified. Thank you for the time. Thank you for sharing your insight. To our listeners, thank you everyone for joining and tuning in, and we’ll see you next week. Thank you, Sean.