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Revenue Builders
How AI Is Rewriting the Sales Playbook and Raising the Bar on Human Performance with Alex Varel
01:02:30
Alex Varel joins John Kaplan and John McMahon to unpack what it takes to sell in this new environment, where technical depth, curiosity, and adaptability are no longer optional. The conversation explores how AI is reshaping productivity, why ICPs must evolve weekly, and how elite sellers distinguish themselves by orchestrating value across increasingly complex buying groups.
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- [00:00]
Alex Verrill
No matter the technology, we're going to have to go out and attack the market and generate a pipeline. We're going to have to have the courageous ability to qualify the pipeline. We're going to have to stay on top of mastery of messaging. We're going to have to manage the icp, which is extremely dynamic in this space, by the way. We can talk about that, but I have to manage the territory and prioritize the territory. And then fifth and final, no matter where I'm at, I'm going to have to deliver an accurate forecast
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Podcast Intro Announcer
welcome to the Revenue Builders Podcast, a weekly show featuring B2B sales leaders and executives. Hosted by five time CRO John McMahon and Force Management Co founder John Kaplan, the show takes guests in the barrel behind the scenes with the people who've been there, done that, and seen the results. Revenue Builders covers best practices for scaling and growing your business while sharing the pitfalls to avoid Enjoy today's Episode
- [00:54]
John Kaplan
welcome to another episode of the Revenue Builders Podcast. Today we're joined by Alex Verrill, EVP of Worldwide Sales at Cerebra Systems, for a conversation about what he calls the great Pivot in a world where the SaaS apocalypse is forcing a total reevaluation of the software only model. Alex is sitting at the white hot center of the AI infrastructure revolution. He's moved from the human layer up of upskilling to the silicon layer of raw compute power, leading a global organization that is building the very highway the future of AI runs on. Today we're stripping away the buzzwords to talk about the rise of the technical athlete. This is a great discussion of what the most elite sellers in the world are doing and will be doing in the future. The infrastructure of inference. What is actually happening in the background to generate a single word of AI output and why speed is the only currency that matters. Intelligence over hierarchy. How elite leaders are leading AI agents to exponentially increase productivity and redefine the role of the modern seller. If you want to understand where the real value is being created in the AI gold rush, you don't want to miss this. Let's get into it. Alex dude, it's great to see you again. Thanks for coming back on. Johnny and I have been waiting for this one.
- [02:33]
Alex Verrill
I'm excited to be here. It's great to see the both of you. Happy Tuesday.
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John McMahon
Happy Tuesday.
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John Kaplan
So buddy, how do you want to kick it off?
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Alex Verrill
Want to talk politics? I want to talk religion. I want to talk narco trafficking. I want to talk about tax dollars on hospice centers and daycare and learning centers.
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John McMahon
Right.
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Alex Verrill
And then I figured we. No, I'm kidding.
- [02:54]
John McMahon
No, it's a good idea.
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Alex Verrill
Is it? You want to podcast? Yeah. Figured that's not talked about enough. We might as well cover it.
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John Kaplan
Well, we know we got our audience in Texas covered.
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Alex Verrill
Yeah, you might, you might understand where I would come in on those topics. But.
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John Kaplan
So I.
- [03:12]
Alex Verrill
All I want to do just to open up quickly because the only time that I've been on the show, I read a little bit of poetry and I thought that I would start some sort of pattern or tradition. I. I don't know if it took off, but I wanted to read something just really quickly and then we can jump to. To business, if that's okay, buddy.
- [03:29]
John Kaplan
I appreciate it, John. It might be putting like, perfume on a pig for Johnny, but let's. Let's try it.
- [03:35]
Alex Verrill
Okay. Okay.
- [03:36]
John Kaplan
So.
- [03:38]
Alex Verrill
Okay. Yeah. Shots fired. So Joseph Campbell, the Power of Myth. He had an interview with Bill Moyers back in the 80s. He was a professor of mythology. Extremely influential on, On. On a number of. Of levels. Anyways, I'm going to give you this excerpt from the Hero's Adventure. He studies mythologies and creates these unbelievable observations around them. And he says in the Hero's Adventure out of the Power of Myth, this interview where Bill Moyers is just going deep down mythology with him, he says, furthermore, we have not even to risk the adventure alone, for the heroes of all time have gone before us. The labyrinth is thoroughly known. We have only to follow the thread of the hero path. And where we had thought to find an abomination, we shall find a God. And where we had thought to slay another, we shall slay ourselves. Where we had thought to travel outward, we will come to the center of our own existence. And where we had thought to be alone, we will be with all the world. And if I turn anybody to Joseph Campbell's work, my job is done. And I hope that maybe caused a few people to lean into that. Okay. But we can get to business now.
- [05:06]
John McMahon
Well done.
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John Kaplan
Well done. Real quick, though, I would like to. I love how you start these off like that. Tell us. Just synthesize at the, at the top level, from the heart. What's it mean to you?
- [05:18]
Alex Verrill
Well, McMahon, I told you to sit at a dinner table. A long time ago when I was at MongoDB, I. Much to the dismay of my. My, My dad, I decided to shift from being an economics major to an.
- [05:30]
John McMahon
And my dad was like, very well, especially. Remember the Cadillac in the driveway?
- [05:35]
Alex Verrill
Yeah. He made me move The Cadillac that I bought right after I graduated, I brought, I brought it to the house. I pulled up in the driveway. I was so proud because I had this job in sales and I was making money and I was going to take on a big car note and I had the Cadillac in the front. Just real quick for your listeners. I came in, I was like, yeah, I was like, dad, Dad, I, I bought this Cadillac and it was the big Cadillac DTS sedan. It was black and, and it was on these really shiny wheels. And he says, let me take a look. And I throw him the keys and he goes out to the front, he looks at it, comes back in like five seconds later, he throws the keys back to me. He goes, son, you're 23 years old. You have five seconds to get that car out of my driveway and move it somewhere down the street. And I was like, oh, okay.
- [06:21]
John McMahon
Alex went into sales. What his dad used to always ask him is, okay, you're going into sales. All right. Yeah, just tell me what restaurant you're going to bartend in.
- [06:29]
Alex Verrill
That's right, that's right. What with this English major, what restaurant are you going to work at? I'll try to get your table and tip you from time to time. He was really nervous. But I, I, you know, have an appreciation, I guess, Kaplan, to answer your question, for literature and for escaping a little bit in that way and slowing down this motor. And it helps to, I think, offset my obsession with work. And so reading stuff like that and thinking on those things quiets the motor a little bit. And it's helpful for me, kind of like exercise is this, this gets me out of myself. So that's, that's the reason behind it.
- [07:09]
John Kaplan
Love it, Love it. And so this, in the spirit of reflection, you spent your career at big powerhouse software giants like Mongo and zscaler, and then you made a highly reflective pivot. So when I first started talking to you about like, what did you do? Like, you had been thinking about this in the spirit of your reflection, you had been thinking about this for quite a while. So tell us a little bit about the pivot that you made and why you're excited about it.
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Alex Verrill
Sure. So I think I was fortunate to have really good timing and intersection with great talent at MongoDB and Zscaler. And then I had really cool exposure
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John Kaplan
to
- [08:01]
Alex Verrill
the upskilling of human capital through a couple of venture backed companies in that space. I found that to be really fascinating. In 2016, there was a book written by Kai Fu Lee was written in 2018. In 2018, there's a book written by Kai Fu Lee that talked about the AI super wars and like the battle between China and the United States and AI. And this is 2018. And the story goes quickly, sorry, because this is the reason that the spark or when the spark occurred, maybe in 2016, Alpha, Google's DeepMind, a company, they acquired an AI company, built a piece of software, a piece of AI called AlphaGo. And in 2016, that piece of software, that AI beat Lee Sedol, the world champion of Go, which is an extremely complex game, far more complex than chess, and it's configurations and possibilities. So this piece of AI beat the world's most popular, most complicated game, go, and it woke China up. It was like a massive event. In 2016, the number of viewers that watch this match is like hundreds of times what we would watch in a Premier League game or many thousands times more than what you'd watch in a certain super bowl game. And China woke up and they started throwing an unbelievable amount of money into developing AI and new economies focused around AI. And I remember reading that story and then I watched the video of AlphaGo beating Le and how everybody freaked out and I was like, this is really cool. So I started to lean in there and I saw maybe with the human upskilling that, that was a really important thing so that we could coexist and augment ourselves with AI and supervise AI. And then I got a phone call about this opportunity to be at the, the compute layer of this world and what's happening right now. And the more that I understood what was invented and what was being brought to market, the more I leaned into it and, and I think that agentic velocity, agentic AI and its velocity will be the biggest creator of GDP growth versus any, any sort of software company or training of individuals and things like that.
- [10:42]
John Kaplan
So you wind up at Cerebras and I'd say your timing's pretty good, brother, with the sales apocalypse. And you know, I think the way you were describing it to me, like, you know, the software only world just set the, set the agenda for the topic that, you know, that we're going to talk about, like, you know, and why it was good timing in your mind.
- [11:08]
Alex Verrill
I'm really fortunate to get the phone call from Alan and then to get introduced to Cerebra Systems and I'll, I'll set the stage for the listener to understand kind of what's going on here and realize that I don't have any great. I have to have this moment with you all of a little bit of imposter syndrome and humility, because I'm going to describe the inception of cerebral systems and why that matters and how important that is. So I report to Andrew Feldman, who's the CEO and co founder. He's one of five co founders of Cerebra Systems, and I talked to him many times per week. And if you all sincerely haven't watched him on podcasts with all in or with Harry Stubbins and the various ones that he has time to do, it's, it's pretty phenomenal. Like the way he explains the AI landscape, the world that we live in, its complexities, he breaks it down and simplifies it and makes it relatable and understandable unlike any way that I ever could. Right. And like, and I'm surrounded by him and the co founders and our engineering team and our product leads and these scientists, and I get to watch them go to work and talk about this stuff. And so for me to describe it is like it pales in comparison to what they have. But go back 10 years ago, in 2016, the same year that OpenAI was founded, the same year that Cerebra Systems was founded, and Gary and Sean and JP and Michael and Andrew saw that AI was fundamentally a different workload than traditional computing. Okay, this is 10 years ago. And they saw that the math was simple, but moving massive amounts of data required for the mathematical calculations was really hard. But they realized that that was going to be something extremely important. And so they set out to build the world's largest chip. I have it down here. This is the world's largest chip. Okay, this is the entire silicon wafer. It's like the size of a dinner plate if you can't tell by the scale of my large hands here. And so why who cares? What does it matter if it's the world's largest chip? It matters immensely. When you have a chip of this size, you can co locate the memory and the compute next to each other so you can move data between the two extremely fast. You're not leaving to go off to thousands of GPUs over a wire. And so what? Who cares? Well, the world has shifted. And by the way, this was attempted by the world's best and brightest scientists for 70 years to do that, to use the entire silicon wafer and not have any failures across that wafer and be able to get yield out of it. They did it. They cracked the code. And the reason that that matters now and the reason that their foresight is so brilliant And Alan and I and the rest of the company are really lucky to represent this. The world has shifted from AI training to AI inference, right? Massive amounts of resources have been thrown at training the models that all of us use right now. And it's like every week you read about one model beating the other, and then you get open weight models out of China that come out that were apparently trained for pennies on the dollar that are far more intelligent and beaten benchmarks. Now the world's pivoted to using those models and everyone's using them now. Our grandparents, our pets, our kids. And the requests are happening more frequently by more users, and the complexity of the requests are much greater. And the whole bottleneck with AI inference is memory bandwidth, because you have to move. I'm really nerding out here, but stay with me. Just to generate one token, one word, one part of a word on a small model, a 70 billion parameter model that is moving 140 gigabytes of data from compute to memory for just one word. And you got to move all the weights and all that data again just to generate the next word. And inference is all about memory bandwidth. And the way that they architected the world's largest chip, it solves for that. It has an incredible amount of memory bandwidth. They eliminated the memory wall bottleneck. And I started to learn about that and learn about these AI supercomputers that contain these chips. And I leaned into it and I was like, I gotta do this, I gotta do this.
- [16:03]
John Kaplan
Well, Johnny, you remember when we first started our. Well, you started the journey first and then you were kind of bringing me up to speed on stuff and you shared with me something on like, where the cost of all this was going to go. And you told me about, like, I remember, like just how many billions of times somebody responds to a model that says thank you. And the billions of dollars, like I couldn't comprehend it when you first were sharing with me, like the billions of dollars because I do it when I use the models. I'm like, hey, that was great, thank you.
- [16:36]
Alex Verrill
And like you're wasting money in electricity.
- [16:38]
John McMahon
They say, good morning ChatGPT. Right? I mean, that's a cost organization, a lot of money.
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John Kaplan
So what Alex just shared with us, like you were talking about, hey, John, you don't understand, like how much that costs and how much that, you know, electricity that uses. And then when I started to dig in with Alex over, you know, the last few months or whatever, he's telling me about the, you know, the speed that is required and what did you say to me about latency? You said there's no. What did you say to me?
- [17:09]
Alex Verrill
Oh yeah, Andrew talks about this. This is why we believe, the world believes that. I talked about the shift from AI training to AI inference. Right. Like you're using the models, building really cool applications on top of the models and using them. And it's like the broadband shift. That's what's happening in AI right now. The real engine behind the experience, the speed of that engine is really what matters now. Right. And like, there's no market for slow search. Right. What is the market for slow search? There isn't one. And the same will hold true for agentic AI and agentic reasoning. Our expectation as humans, just like we expect with fast Internet and fast search, our expectation is to be able to interact with, with AI in human clock speed, responsiveness. And that's what we do. That's what we do best. And no number of GPUs stitched together can match that.
- [18:12]
John Kaplan
The reason why I like where we started here is because I think the average listener, including me in my journey a couple of years ago or what have you, would be. I don't understand what's going on behind the scenes and why. I love the way you shared this is. When you're sitting there listening to this, a lot of people are enamored with models. And I think, how many times did you get a phone call and go, Alex, what are you doing? You going to a hardware company? So you go from software company to a hardware company. And the thought process behind that is, why is Alex going backwards?
- [18:54]
Alex Verrill
Yeah.
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John Kaplan
You know, and it's not even, it's not even close to being. This is where the real pain is in AI and the solvable pain right now is huge right here.
- [19:04]
Alex Verrill
I don't mean to be controversial, but I think that if, you know, if we used to look at like compute storage and networking as commodities and, and then, I don't know, I used to knock hardware sellers. I don't know if you all ever did, you know, like box pushers or whatever.
- [19:20]
John Kaplan
I don't know, I was one back in the day.
- [19:23]
Alex Verrill
Okay. And you know, I mean, look at the, look at the models. They're reaching, like reasoning parity, like they're, they're converging onto each other and their intelligence and accuracy and reliability. And so. And then you have a ton of AI natives that are building all these applications. Things are kind of crowded right now. And you know, I think it's really interesting if, if that reasoning parity is being reached. And these models and all these applications have a lot of overlap. To me, the real differentiator left is the speed and scale of the engine and the sophistication of the workloads it can support. And so I found the prospect of that to be really, really interesting.
- [20:10]
John McMahon
You talked about memory bandwidth. What about power consumption? That's a big issue right now with AI. Does the chip from Cerebras help with minimizing power consumption? It is.
- [20:22]
Alex Verrill
The power draw is significantly more efficient, significantly reduced. Imagine that you don't have a requirement for thousands of chips that are stitched together, you know, running a bunch of data across, across them, back and forth. Yeah, the, the efficiency savings are very real and very material for sure.
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John McMahon
What about cooling?
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Alex Verrill
Another efficient benefit to the way that this was architected. It's liquid cooled. And the world is, is moving to that. From air cooled data centers to liquid cooled data centers. You know, you can have that water more or less recycled constantly through the data center and chilled to the appropriate temperature. That, that is far more efficient as
- [21:08]
John Kaplan
well as the new data centers that are being built. Just for the listeners and all the arguments that are going on on power consumption, like it's a little bit of hype in some cases because they're all being built liquid cool, right?
- [21:22]
Alex Verrill
Yeah, yeah, I think, I think that's a definite benefit. And you know, it's. I don't think there's a shortage of power. It's just, it's getting the power to the data center locations in doing so in an efficient way. I mean, there's plenty of power to be extracted from multiple sources. There's lots of power and energy that's wasted every day. The infrastructure's got to be modernized and efficient and brought to the data center locations. But I'm going to outline companies like
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John McMahon
ge, Vernova, Bloom Energy, Vertiv, all those types of companies, Constellation Energy, all our, all their stocks are taking off.
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John Kaplan
Thank you, John McMahon.
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Alex Verrill
That's right. That is right. Yeah, I do my.
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John Kaplan
I listen to you, buddy. I listen to you.
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John McMahon
All right.
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Alex Verrill
Yeah.
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John Kaplan
Hey, you, you were talking about getting controversial. Can I get a little controversial?
- [22:14]
Alex Verrill
Yeah, please. I love that.
- [22:15]
John Kaplan
A little controversial. And there's a provocative idea circulating that I hear. People say that a significant percentage of software sellers today are really at risk, whether it's a year from now, two years from now in this new world. Like, first of all, what's provocative about that? I know that it's, you know, for somebody like me, it catches my attention. Where do you think that's coming from
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Alex Verrill
one example right now? Like Jimmy Lee, my Rev Ops guy, this is our third company together. You met Jimmy in London a while back and you know he trained like five or six agents over Easter weekend while his family was asleep. He gets up at like 4 in the morning and just goes down a very curious path. And he trained four or five agents that are looking at. He's got one for voice of the customers, so product feedback, going through Jira tickets and things like that. He's got one for some forecasting, he's got another one to monitor solution architecture work and he's got six that are in the works, right? So think like 10 inside of a week. That is going to augment his productivity immensely. They are going off and conducting tasks on his behalf. I'm going to build and train a few this week myself. Get hands on keyboard and I think the understanding how to augment your own productivity in your profession matters no matter what, especially for sellers. And if I can imagine like my daughter who's a sophomore in college in two years time I would really encourage her to go into an interview and almost like an artist would lay out a portfolio of work that they've done or if they're a model, they show like the shots that they've done. I want her to come and show the agents that are multipliers of herself, extensions of herself and show what she can bring to the table that equals the productivity of I don't know, five or ten humans plus her agents. And I think sellers have got to get really curious about this space. Those that are potentially at risk are those who don't have hands on keyboard experience and don't know how to augment their productivity or supervise agentic AI in their job. Right? To just make them more capable. The great thing is though, I think humans are going to crave. I just got back from London and Stockholm, meeting with prospects and customers. By the way, the tech in Stockholm is incredible. I don't know, the minds there are brilliant. I don't want to call it specific logos, but what's happening in Stockholm is fascinating. Humans are going to crave sellers interpersonal and intrapersonal capabilities and communication skills and just being face to face with them. The email is dead. It's just been taken over by AI slob and we're going to crave some human fallibility and some misspellings and custom made emails and in face to face meetings. So I think it's two parts that really matter. Getting hands on keyboard, knowing this is
- [25:47]
John Kaplan
where you wound up today. But you've had discussions with me in the beginning where you would say, you, you called it, you said imposter syndrome, you said, cap, I'm feeling exposed. Like, walk me through that experience and how you had to level set yourself because if you stayed in that exposure world, then you would have just gotten, you know, and the people that are funding this and the people that are, you know, they have certain ideas about playbooks and the way software sales was done. Just give me your perspective on that. And you're, I, I think you're calling it like a technical athlete is really what we all need to become.
- [26:25]
Alex Verrill
I think that's it. I mean, there was a tweet, I don't want to, I don't want to name names, but there was a tweet that kind of rocked my world from a highly influential person who love and admire. And he basically said that, like, I'm seeing these traditional software leaders go over to AI native companies or AI centric companies and they're trying to transfer their playbooks and they're just getting creamed. Like I'm paraphrasing. And so I think there is like a adaptability and situational awareness when you, when you come into an AI native company or if you make a big pivot from, you know, being a heralded software seller into something like representing, you know, the world's fastest inference, the world's fastest compute. There's a lot to learn and you have to, and you all encourage this in your work and, and you know, in John's book, like, you got to come in and really assess the situation. You know, it's like, John, when McMahon, when you talk about coming in and, you know, you assess the talent, right? Assess the situation around you, have a really good understanding of strengths and weaknesses and vulnerabilities around you. What can you affect? What can you not affect? And I, I came into the company, I'll never forget the first executive meeting. It's like four of the five co founders, or they walk in, I'm just sitting in this big kind of room and four of the five co founders come in. And then there's Natalia, there's Angela, there's Jessica, these unbelievable product leaders and machine learning field leaders. And it's just really quiet. And I'm like, oh my gosh, this is, this is really intimidating. And I realized that there was a steep learning curve that was going to be required and that I didn't want to jump to conclusions too soon, right. And that I was going to have to go out and try to scale this thing and attack the market. And I was going to have to hire sellers for sure, but the sellers were going to come into the same situation as me because this is novel territory. I went and pillaged Snowflake and I, I, because, I mean, what an incredible company. Like they, you know, they had a very different novel architecture and they, they trained elite sellers. I'm like, I love that profile combined with emc because I love killers from Boston. I think the whole EMC sales cultures and like, you know, the, the, the, the folks that have come out of emc. But I found this sweet spot. I'm going off on a tangent of like Snowflake plus EMC and then get in here because they have, they have the intangibles, they have the skills that are transferable. Five pillars have to, no matter the technology, we're going to have to go out and attack the market and generate pipeline. We're going to have to have the courageous ability to qualify the pipeline. We're going to have to stay on top of mastery of messaging. We're going to have to manage the icp, which is extremely dynamic in this space, by the way. We can talk about that. But I have to manage the territory and prioritize the territory. And then fifth and final, no matter where I'm at, I'm going to have to deliver an accurate forecast. Right. But I knew I was going to
- [29:41]
John Kaplan
bring, which is thousands of years old. So I love. Johnny and I have these podcasts and we say the more things change, the more they stay the same. But explain to us the nuances that basically if you, if you have a static playbook with all of those things and you try to bring them into an AI centric company, you're dead.
- [30:03]
Alex Verrill
Yes.
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John Kaplan
You just have, it's almost what you're selling. It's the speed of adaptability.
- [30:09]
Alex Verrill
That's, that's right, that's right. Those are constant. Those five pillars, they, they, they persist. No, no matter where you are. But the customer and how the customer buys is different. And you're coupled with a machine learning solution architect. And so you have to understand how you're coupled with that person. And, and I don't know if that's terribly different from partnering with a solution engineer across a different piece of technology. But the way that these models come out every week and the way that companies are formulating compute strategies and the way that they're formulating how they're going to leverage new models and what they build on top of Them the funding that is going around to these AI native companies that are disrupting traditional enterprises. You know, you have to think about like am I going to need, you know, the software capacity model where I've got to have this many bodies in the northeast, this many bodies in the west, this many in North Central, etc. Etc. And EMEA and APAC, you know, where really is my ICP? Granted all the dynamic constant changing in this AI landscape, my inclination is just to go attack the enterprise market with this crew and attack the Fortune 500 and the Forbes 2000. But what's really interesting are the extremely well capitalized AI native companies that have just emerged in the last 6 12, 18 months have really come out and disrupted the whole scene. And so we have to keep our ear to the ground on the innovation velocity around different companies that are very well capitalized and determine where to invest our time in them versus a Fortune 500 that's scared for their life but maybe moves a little bit slower.
- [32:11]
John McMahon
Let's get more practical. So I mean whether you work in your company, which is like on the leading edge of AI and things are changing every week and people are getting funded different ways, all of that stuff AI can help with, whether you're in something moving as fast as the company you're in, or some traditional software companies, or some companies that are just now starting to accept, you know, what AI is doing to the to sales. Because at the end of the day today still only 25 or 30% of the time people are actually selling face to face or selling to the customer. The other 75 to 80% of the time people are not selling. They're in non productive activities, they're doing admin, they're updating the tech stack, they're researching customers, they're researching use cases, they're doing homework on what's the latest and greatest news of the customer. They're coordinating calendars, I'm coordinating information with my internal and external stakeholders. I'm spending 80% of my time doing that crap that AI can help me at least cut in half, maybe even more to help me spend not 25 or 30% of my time selling, but spend 50 to 75% of my time selling. That's where I think the leverage comes for anybody that's in sales and is trying to understand how is this going to affect me. I think it's going to affect you in a very positive way and give you a lot more time in front of the customer. And if you use the tools that really help you with these non productive
- [33:45]
Alex Verrill
activities 100% like the, the rev Ops team that I thought that I was going to need to build out McMahon like 14 months ago versus what I actually need right now by using tools or training my own agents like Jimmy did this past weekend. You're right. And like I think that's the evolution of sellers. As long as like the agents that they train are you know, sponsored and approved by their company and able to connect to the system of record and the, the artifacts that the agents would sit on top of, they can get a significant amount of time back now through, through great technology and specifically through agentic AI. Like that's a, that is a, that's a big point. That's something that I highly encourage folks to lean into. I don't have nearly, not to spook anybody and I don't have all the, I don't have nearly the software stack or the rev Ops staff that I traditionally would have because we've, we've found automation and agentic workflows that are really helpful.
- [34:55]
John Kaplan
So for the listener here that's listening to you, you said, you know, the kind of EMC background, the kind of snowflake background, I want you to go a little bit deeper. A couple of days ago you and I were talking about, and you were talking about the intelligence and the common one that we talk about a lot is curiosity and you started to talk about multiple levels and layers of intelligence. When you think about you really need to have as a seller today in this type of environment, could you expand on that a little bit?
- [35:30]
Alex Verrill
I think that there could be an argument at least traditionally in this industry and even with some of the folks that have been here for a while, like I don't really need the ae. Just give me, give me a really sharp technical solution architect and we'll go close the deals with like product leaders or we'll just do kind of more founder led sales. You know, with the profile of AES that I hired, I knew that, that no matter what this is universal, that we're always going to have to translate the technical capabilities of the technology into value for sure and that we were going to need to be really strong value translators. You know, we're going to need to be able to whiteboard the tech for sure. But the business win is going to be extremely important. Even after the technical team wins the math to have a fun poor description of how great the technical team is and how important they are. Our essays are brilliant and they're extremely important. But we, we really have got to be able in such a competitive world to understand the buying committee, which is going to be extremely cross functional. You're going to have infrastructure owners, you're going to have product leaders, you're going to have engineering, you're going to have technical experts all over the place. That and they can all win the logic battles. But the AE has got to be an extreme orchestrator that listens and understands where the value is and understands how to command the premium of the world's fastest tokens. And so the, the whole multiple intelligence is thing that helps me get over my imposter syndrome in a highly technical sale. That's all Howard Gardner's framework people can look that up. That, that human potential isn't just like one IQ score, right? Like the AES have got to go out and attack the market and prioritize their territory and beget opportunities, qualify the opportunities. It's like if you have an AE and an essay in the room and let's, let's pretend it's just essays. Let's say that there's a founder led theory that I don't need AES. This is so technical. Sizing workloads and all that stuff is so technical. Just give me an essay, we'll figure out the rest. Customer asks a question to the SE or the sa. They ask like, hey, what models do you serve? Right. What models do you serve? How's the SE or the essay going to answer the question?
- [38:19]
John Kaplan
Black and white?
- [38:20]
Alex Verrill
Yeah. I'm just going to tell you the models that I serve, you ask the question logically. I'm going to give you the answer.
- [38:26]
John McMahon
Right?
- [38:27]
Alex Verrill
An AE is going to have the, the interpersonal intelligence and curiosity. Say, maybe that sounds like that's an important topic to you, Mr. And Mrs. Customer. It sounds important to you. Do you mind? I'm going to answer your question. I don't mean to play games. Can you help me understand why did you ask? Why are you asking which models we serve? Okay, well, because I can't tell you six months from now what model is going to come out. From where? From anthropic or from OpenAI or from Grok or from some model lab out of China. And I don't have a permanent model strategy when these things are leapfrogging you. So I need to know like what do you serve now? And I imagine Mr. Mrs. Customer is probably important what we're going to serve in the future, like what our model roadmap is. Those kinds of things aren't most commonly natural in my experience with ses. And pure sellers are kind of born and raised, you know, or at least the ones I like to hire to really qualify these things and go down and listen for that opportunity, listen for that intent. I think that's something I see quite a bit in that sense.
- [39:43]
John McMahon
Qualifiers and their skeptics, the ones that pure maniacal qualifiers and genuinely skeptical of every question the customer asks, they want to qualify it. Why do you ask it? How come that a threat to me? Should I answer the question? Should I answer partially? Should I answer the whole. And that's what's running through your mind?
- [40:05]
Alex Verrill
Yeah, that's right. And we're, we're taking on an 800 pound gorilla, right? Like this is high stakes stuff. We're taking on a massive incumbent and, and we've gotta, we've gotta have that awareness and, and we've gotta have, we gotta have some really good judgment and, and making sure that we understand pain and we understand the implications behind that and we're really good value translation.
- [40:29]
John McMahon
Okay, so what tools have you put in that are AI, that are you've. That you've bought off the shelf and you've put into your sales to help your sales force's sales process?
- [40:38]
John Kaplan
These are his, these are his partners that he's selling to. Go ahead.
- [40:42]
Alex Verrill
No, no, no, no. There's no circular stuff going on here.
- [40:45]
John Kaplan
Okay.
- [40:47]
Alex Verrill
It's. John, it's really limited. It's really limited. Like I don't have the stack that I used to have everywhere else because now I don't think, I don't think that'll stay this way.
- [41:04]
John McMahon
But the reason not going to stay that way.
- [41:07]
Alex Verrill
Right. I mean I think there's some tools that I want to take on. But you know, like the example I gave you. We are training agents, the ones that have access connected to our systems to pull from our systems of records and do some ongoing research and analysis and surface patterns and risks to us. So I have a traditional CRM and I have content management. I have some automation in our outreach. But everything else, I'm using agents that we're training to pull the information and do tasks for us.
- [41:54]
John Kaplan
I wanted to just follow up on this one. We'll come back to the stack in a second because I think that's very interesting and how we all agreed that for now and maybe what you think that's going to look like, but I wanted to make a point on this imposter syndrome because I've been there before in my life and I try to put myself in positions as much as I can. To feel like an imposter, it means I'm growing and I'm learning and I'm, you know, if you're not growing, you're dying, so to speak. And however my experience is, when people get into those types of environments, they try to learn as much as they can about the technology. And I've always felt like companies have the responsibility to really help you with the knowledge of what that is, how it works, why it works, why is it a problem? How do you do it differently than anybody else? Companies owe you that. What you should bring to the table if you're listening to this is this intellectual curiosity, which is when you have an imposter syndrome, you have a tendency to try to be more interesting on a sales call or with people in a room versus being interested. And somebody said that to us, Johnny. I think it was our selling DeVito friend. You know, the best sellers on the planet are the ones who focus on being interested, focusing on being interested in what the customer's saying versus trying to be interesting to the customer. And I just want to kind of highlight that I find myself in that scenario where I'm trying to learn as much as I can about the new world that we're all in and still going back to the basics of what problems does it solve? How specifically do you solve it? How do you do it differently or better than anybody else? And where have you done it before and allow people to go on a journey with you? Have you met anybody, Alex, that's expecting you to say, you should understand? Like when you went to Stockholm, did anybody say to you, you should understand my environment, you should understand exactly what we're doing? Or did they expect you to be interested in what they were doing and then from that interest have a hypothesis about what you might be able to do for them? Does that make sense?
- [44:24]
Alex Verrill
It does. I mean, the really cool part about the folks that I met with in both London and Stockholm, and I think even here is like, I get down, you know, my strength is, I think in the business acumen and understanding that if I, for example, provide the only engine that's fast enough to allow agents to self reflect and collaborate in milliseconds, then I'm enabling products that were physically impossible two years ago or a year ago. And so, you know, when you think about like latency, so I get to ask some really simple questions. But when you think about latency in a product, right, imagine you're on with the pharmacy and they've built a new conversational bot or app. In fact, There is one right now that is extremely frustrating to me. It's like a 2 second SLA. I call into the pharmacy, I have low thyroid by genetics, so I gotta take a thyroid supplement. Violating HIPAA on the show. And you call in, and you call in to the pharmacy and, and they're. The whole goal of these big pharmacy chains is to like reduce the number of people like me calling, trying to talk to the pharmacist for basic things like a refill. Right. So they built this conversational bot and it's, it's on a 2 second SLA. I know, I can tell. And it's just, it's way too slow for conversational. You need to be like 500 milliseconds or less. Right. But anyways, we empower instant AI, especially for conversational use cases, for agentic coding, for deep search. And so I get to talk to people in Stockholm and London for example, about not just how much greater that is for the user experience, but what do you do to pack in value and revenue opportunity with that latency savings? Like how much more sophisticated is your product get? I ask him just point blank, if I bring it down where you're responding to human in 200 milliseconds and your SLA is 500 milliseconds, imagine the tool calling this the sophistication. You can pack in between 200 and 500 milliseconds with me, can you help me understand where that might have an impact on your customer satisfaction, your revenue on and on those two worlds.
- [46:44]
John Kaplan
What I love about what you're saying here, and I just want everybody to hear, you know, go replay this story from Alex. There's a mindset that would say I can do that faster and talk about all the things that you can do to do that faster. And you will be talking to people that are responsible for making that faster. You also need to be talking to people to talk about what they're going to do as business outcomes for that speed. And those that as old as dirt. That's Egypt old. It's like technical requirements create business outcomes. And it's just a little heads up because I think when I've talked to people that go over to AI native companies, they spend so much of their time trying to not feel, you know, and I think what like you said, you just put the right technical people in the room and you are the value orchestrator. You're like, okay. And I say this a lot sometimes I'm like, okay, let me just ask the, you know the dumb question in the room or whatever. So what? So you can do it 500 milliseconds or whatever. What does that do? Who cares about that in the organization? And depending on who you're talking to, you'll find that they might go up a technical chain and they'll talk about the technical people and SLAs and that. But there's a line of business that is. It's as old as dirt. And so I just, it's kind of. I'm not saying you don't have. You have to be on your game, but don't get overwhelmed.
- [48:08]
Alex Verrill
That's right.
- [48:10]
John Kaplan
Bring your A game.
- [48:11]
Alex Verrill
One of the companies, McMahon and Cap, you know, they have a flat subscription rate for their users for their service. It's just, you subscribe, but, you know, again, I get to be kind of dumb and so. Well, if I make the responsiveness that much faster. Do you think there's a market for premium users and you would charge a premium? Could you open up another tier? Right. What's happening all over the place? Right. Anthropic, just to open fast. For example, OpenAI's Codex and then Codex Spark, which is powered by us. And the guy was like, well, we never thought we would get into premium tiers, but we're just kind of one size fits all. And I'm like, well, it's possible, right? He's like, absolutely, it's possible. And I imagine it would pay for what you and I are talking about in droves. And he was like, yeah, you know, you can start seeing me, you know, selling a little bit. So I had to hold that back. But yeah, it's just, where's the value? What's the art of the possible? Stuff like that.
- [49:18]
John Kaplan
Love that. So again, the more things change, the more they stay the same. It's like that didn't change when you were selling for the big behemoth software only companies. That's exactly what you were doing there. When you're going to AI native companies and now at the infrastructure layer, in a highly technical environment, that doesn't change. You still have to connect those two worlds. So tell us a little bit about the playbook side of it as it relates to. You're sitting in the seat, you're a CRO, you're sitting in the seat, you know how to build organizations. What are some nuances that you also have monster customers who are also partners. And so you're feeding. You can't. I can't imagine that you could build an organization with a salesforce that just goes and calls on Those monsters in that partnership relationship. What are some of the big nuances that you had to upskill yourself on how to attack that problem of going and building a go to market in this. I don't want to call it Wild west because it's not Wild west, but it's pretty crazy.
- [50:30]
Alex Verrill
Yeah, it is, it is. I mean, I think again, like the management of who our ideal customer is, our ICP is, is something that we have to like constantly pay close attention to. And I always want to.
- [50:47]
John Kaplan
It's not a once a year type thing. Hey, this year it's this. Yeah.
- [50:50]
Alex Verrill
No, no, no, no, no. I mean, we, we revise this not, not in months, but in weeks. Like, we just stay really close to this because, you know, we've, we have to be very focused with our time and our energy. Of course, I don't know if that's terribly different for others, but like, we've got to make. We have these monster deals for sure. But I'm putting a ton of wood behind the arrow and just generating very healthy pipeline constantly. But there's a lot of companies that have emerged and that have been well funded and it's hard to tell like who's going to survive what. Right. And so in some ways we're having to place bets with who we interact with. Right. Like genuinely, who's going to go big with us, who's going to have durable growing consumption of tokens with us, who understands our value and who's going to do great things and create new categories and new economies and we go and build pipeline behind that. It's different than me traditionally just going up market and attacking the Fortune 500 and the Forbes 2000. It's very different. I'm. I'm watching the emergence of these AI natives and attacking the ones that we think are going to do extremely well for the long haul. I've never had to do that, if that makes sense.
- [52:24]
John Kaplan
Yeah. Are you using any AI or any of your agents that you're building? A lot of people are talking about in this world, the ICP is changing under our feet sometimes. Are you using anything? Could you give any heads up to the audience on you and your smart, Mr. Lee, your smart Rev Ops people. Are you doing anything to stay on top of that more than you have done before?
- [52:55]
Alex Verrill
We are, we're tracking the flow of capital, we're tracking raises, we're taking data from multiple sources and synthesizing it and constantly updating our top target lists. For sure.
- [53:18]
John Kaplan
Tell me how that affects the seller workflow so you Got the ability to do that. What changes for the seller?
- [53:28]
Alex Verrill
I guess the prioritization of the accounts that they attack and put into their, their PG cadence changes. Right. They will introduce new companies into their tier one which commands the majority of their time and attention based on market signals. You have really interesting companies that are attacking healthcare problems that are disrupting what, what lawyers do, what accountants do. And so we, we have data sources and signals that flow in and we have scoring of course. And then of course that'll change the way that they prioritize their time and who they go after to try to create pipeline. I don't mean to be too vague. I'm a little hesitant to give you like exact vendor names. Maybe I can do like a follow on blog or something to tell you exactly what's in my stack but I would just tell you like it is. It is a shorter stack than I've ever had with less, less humans behind it than I've ever had.
- [54:29]
John Kaplan
And you're not buying technology just to buy it or to have relationships. You're, you know what, what I people are going at use cases and they're going at seller workflow. So use cases for the technology that they're interested in and does it matter in this example, does it match immediately to a high value sales workflow that makes sellers more productive? I think if you start there, the advice for everybody out there, the closer you get from ins, the farther you get from inspection to adding value in the engine of pipeline generation and qualification and making it easier for those sellers with these highly intellect intellectual curiosity and the things that we were talking about, the human factor that's going to be very, very hard to replicate. Getting it in the hands of those people seamlessly and less painfully is really the name of the game. I think so I'm looking forward to the blog.
- [55:35]
Alex Verrill
Yeah, I will put, I'll put some thoughts on paper and reveal some of the secret sauce but I would tell you that like I gotta, I'll just give a tip of the hat to the leaders that took a bet on me to come over here that were in really great companies, really great high growth environments. Griff, Paul, Jason, Mark, suv, Jimmy, the crew, others like they, they went out and you know like I learned from you all like you hire great A plus leaders, they're going to go out and hire great people. You know they're obsessed with our work and they are, they were able to recruit people before we had a really large inference business or as it was emerging they made the bet with me And I'm extremely grateful for that and for that.
- [56:30]
John Kaplan
Amazing.
- [56:30]
John McMahon
Congrats.
- [56:31]
John Kaplan
Hey, Alex, before we go, advice to sales leaders and advice to sellers. Thinking about everything we just talked about and then thinking about Alex two or three years ago. Okay, what is the best advice you could give to sales leaders? Listening to this and sellers.
- [56:55]
Alex Verrill
So I would go just April 1st, April Fool's Day, Roloff brother, if I'm pronouncing his last name Sequoia, had a conversation with Jack Dorsey and Jack Dorsey wrote a paper about, I think roughly it's like hyper intelligence over hierarchy and his vision for this intelligence layer that's going to traverse the entire company and that there are three layers of humans that are interacting with that intelligence layer. There's the ic, the dri, and then the coach, conductor, orchestrator. Having an understanding of where potentially the world is going with agentic AI, and having an extreme central brain that traverses the entire company and how you would interact with that. I'd go dig into that thing and listen to that. I would also prompt your favorite model to build a learning path for yourself so that you understand AI training, inference, AGI, you understand prompt engineering, you understand the concept of tokens, and you understand maybe how tokens might be assigned. There might be a token budget per employee in the future, right? There kind of is one now, but it's, it's good. That will be a thing. There's a labor shift, not just a software shift. I would just get really in tune with that and understand it and like have a self learning enablement path and you can shine with that stuff. And the things that are in John's book and the things that are in this podcast are universal truths that will travel no matter and apply no matter where the tech takes us. And I tried to hit on a few of them. And so you know, the level of human talent, the level of coaching your people and developing your people and being maniacal about execution, being extremely curious and driven, like those things are still going to apply. And I think coupled with a really great learning path, you know, you're, you're future proofing yourself potentially in a really good way.
- [59:10]
John Kaplan
I love that. I. What I've been saying, Alex, is, and I've been saying it for decades, but, or a couple of decades at Force Management for me, now more than ever, attach yourself to the biggest business issue facing your customers and influence their decision criteria with your differentiation. Now those are a mouthful. Those are absolutely a mouthful. But if I'm a leader or I'm a seller and I'm looking at those two skill sets. Those for me are at the top of the list right now.
- [59:43]
Alex Verrill
Thousand percent agree. Sincerely. Even in this new world that I'm in, that is 100% still true. And that will remain true. That will persist.
- [59:52]
John Kaplan
Amazing. I feel like I got to go read some so I feel like I gotta go read some poetry. Johnny, what are you reading for poetry? Johnny, what are you reading right now?
- [60:01]
John McMahon
Me.
- [60:02]
John Kaplan
Yeah, Come on. Exposure.
- [60:04]
John McMahon
Leonardo da Vinci.
- [60:05]
John Kaplan
Right now, the biography.
- [60:08]
John McMahon
Yeah. By Walter Isaacson.
- [60:10]
John Kaplan
Oh, that's a big one.
- [60:11]
John McMahon
He wrote about Elon Musk. He wrote Einstein. I love his writing.
- [60:17]
Alex Verrill
Yeah, I, I read two. I don't know if this is going to make the cut for post prod but over Christmas break, Cormac McCarthy, no country for Old Men and the Road and those, those will blow your hair back. Those two are really cool too.
- [60:36]
John Kaplan
For fiction, well done. Mine was my two are. Well my one for sure and I keep going back to reread it is the the founders about the guys that started PayPal. It's fascinating to me. I just found so many and what they did after PayPal and how they built companies and the culture associated with that and how they messaged and created boards and I just found that a great read. And then a personal one that I have is I'm on a big, just coming off the holiday here. I'm on a big investigative path on the Shroud of Turin and we'll have to do another podcast on that one. But the when you talk about technology and technology advancements are actually blowing my mind on what they're revealing on that. So coming to a theater near you, very cool. Well done, buddy. So great to see you. So happy for you. You've earned it and can't wait to have you on again when you're talking about, you know, full scale what this thing has turned into.
- [61:44]
Alex Verrill
Thank you.
- [61:44]
John McMahon
Congrats. Alex.
- [61:46]
Alex Verrill
John McMahon, it's great to see you. Yeah. I appreciate you very much. John Kaplan, I appreciate you very much and I wish you the best. Thank you so much.
- [61:57]
John Kaplan
Yeah, you got it, brother.
- [61:58]
John McMahon
And thanks to everyone for listening to another episode of the Revenue Builders podcast.
- [62:05]
Podcast Intro Announcer
Thanks for listening to today's episode. If you enjoy the content, please subscribe Ray and re review the show to help us reach more people. This show is brought to you by Force Management, where we help companies improve sales performance, executing the growth strategy at the point of sale. Check out forcemanagement.com for more information.