E33: What It Takes to Be a Revenue Leader in the AI Era with Mike Donohue, CRO of 11x

Hello and welcome to the Revenue Leadership Podcast by Topline. I'm your host, Kyle Norton, CRO at Owner.com, and every Wednesday we dive deep into the strategies and tactics being used to drive success by the best revenue leaders in the world. So join me as I sit down with revenue operators to discuss actionable frameworks that you can implement in your business today with no fluff, no sales pitches, and no platitudes.

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Today's guest is Mike Donahue, who is the CRO at 11x. And 11x, for those of you who don't know, they build digital workers for go-to-market teams, one of the leading companies in this AI evolution. So really excited to dig in on all things AI in the future with Mike. And Mike's had a very exciting career. He started at Square, sub-100 employees. Where he was in sales leadership for 3 years. Then he joined PayPal to start the go-to-market team for the shopping product and was there from basically zero all the way through $350 million in ARR and was the head of commercialization. So that was a super exciting stint. And most recently, he was the SVP of global sales at Gupshup. Gupshup? What's the pronunciation? Gupshup. Okay. That's a mouthful. And he's joined 11x in the last few quarters as CRO to grow their team. And so I'm really excited for this one. You know, it's a really varied, interesting career that we can dive into. And we're going to talk all things AI and how you see the market playing out. We'll get into this concept of the forward-deployed engineer within go-to-market, which is really fascinating, and get into the details of how people can evolve, because if they don't, I don't think the market's going to be particularly kind to them. So let's start there. What is your sense on where people are at in this go-to-market evolution? Like, there's the commentary on LinkedIn, which would make you feel like everybody's doing all of this AI stuff, but you guys are an AI startup. You talk to a bunch of CROs. Where do you think adoption is today for the average Series B, C SaaS company?

Yeah, awesome. Yeah, thanks for having me, Kyle. Really excited to speak about this. I always— there's like that curve that you see. About like, kind of new markets and new technologies. And I think like very much now we're in this like new, like early adopter phase. And it's really exciting. I was actually listening to one of your earlier podcasts, you had this quote of, you know, it's much— it's about experimenting with AI tools and how valuable that is, and how it's much riskier to— it's much riskier to like, not experiment with multiple different AI tools than to have like one of them not work out. And I'm really, really seeing that in like this early adopter phase. Like the companies that I think are, are really winning are trying like 5 to 10 different products. And some of them like very like regimented of like trying 5 different AI products on a quarterly basis and really keeping the ones that are working. Um, and just like, like it's really changing the organization. I think like 6 months ago we were in this phase of I mean, like 6 months to a year ago, we were in this like phase of like creative, like Claude and ChatGPT prompting of building, you know, reports, um, you know, personalizing emails. And then now we're really entering this kind of like application phase where there's a number of companies that are building specific, uh, AI-native tools for go-to-market teams. Solving roles of SDRs, AEs, revenue operations. And yeah, it's really, it's really exciting to see these products and how they can change a lot of the operation flows.

Yeah. And so when you talk to the average CRO and 100 out of 100 being everything is AI native. They've got, you know, digital solutions engineers on calls and an AI SDR on their website. That, that being 100, and 0 being like, I don't have a single AI workflow in my company, and I, I maybe, uh, look up some recipes with ChatGPT. That, that's like a, a 0. Where are most folks today on that spectrum?

Yeah, I'd say around like 20. It's really interesting. There's a, there's different groups of I think there's like 3 tiers of companies. There's like the really like, you know, mature, really large tech companies. Um, there's kind of like these, you know, mid-stage growth companies, and then there's these early, uh, new startups that are coming up. And I'm seeing the most adoption from these early startups, and they're kind of like, okay, clean slate, I'm building, you know, a new company, I'm building a new go-to-market, you know, organization, and I want to build it, you know, AI first. And I think they have like the least amount of debt. So it's easier for them to do that. And I see these companies, like foundationally being built in a different way. And then I see kind of this like mid tier of companies, you know, adopting a lot of different tools, kind of experimenting. And then I see like, like really large, like, large, large, you know, companies like wanting to be AI native, but like wanting to use AI, but they're like very much at like kind of the zero. And I think you see a lot of like, I think like those types of companies, you see like a lot of, I like love that like post from the Shopify CEO.

Yeah, yeah, yeah.

Really like pushing the org and like this, it's like just, it's, you're really moving like thousands of people to operate in an entirely different way. And I think that's why it's harder for some of those larger companies where when you're just building with a team of 5, you're like, hey, this is how we operate. These are the tools that we use to grow our business. It's— we don't have to like change and displace everything. And there's a lot, a lot of— they're getting a lot more speed on that side.

And so If, um, for the CROs that aren't adopting, you know, they're like, oh, RevOps is doing some stuff, but like AI is the domain of RevOps, and, uh, maybe they're a little more hesitant to, uh, dive in with two feet. Do you think they can still be CROs in high-growth companies in 24 months?

Yeah, I, uh, yeah, but yeah, I think so. Um, I mean, like, let me just like rephrase the question back to you. Like, if, um, like, if, uh, like, CR is— CR is like, don't adopt AI, they're no longer—

there's a basket. Yeah, there's a basket of resistant folks who are either taking a wait-and-see approach or don't think that they necessarily need to make that a core part of their job. Like, my approach is, I mean, I think this is one of the most important things for a revenue leader to be able to figure out. I'm in the tools every day myself. I'm like vibe coding apps in Windsurf just for fun. And I'm like all in. So I'm on one part of the spectrum. And because I believe this is, you know, the single biggest platform change any of us have ever seen in our careers and potentially the biggest one in like 100 years. And, but then there's some folks that are just like, I don't think I need to be that level of sophistication. I don't think people need to be vibe coding and windsurf as a CRO. I just think it's fun. But the folks that are like, you know, AI, like RevOps will figure out AI, that doesn't need to be a core capability for me individually. Do you think the way the world is going, to move that that person will be no longer relevant in 24 months? Or is there a way to be a CRO and not make this like a core expertise?

Yeah, yeah. Here's my prediction that we're like in this like early adopter phase right now and the companies that are adopting, you know, AI are just getting like massive efficiency. And if you look at like, you know, really high growth, you know, companies, there's like, there's like standards of growth that develop. Like there was like rule of 40, like rule of 60. And I think, I think like AI is going to really set new like performance growth efficiency standards. And I think the CROs that are like hesitant are going to, they're not going to know how to really implement you know, those types of like efficiencies. They're not going to know how to hit those metrics. Um, you know, I'm seeing like, you know, if you look at like companies like, you know, 11x, um, or like Clay or like, I mean, we're like optimizing like entire SDR teams, um, you know, and really changing the, the workflow of, um, of really changing the workflow of really large SDR teams to move from hundreds of person SDR teams at large companies to having a single go-to-market engineer or a single person that builds a workflow for outreach. And it's really changing. It's moving from having large teams of like massive headcount to having, you know, 2 or 3 people sometimes within a marketing org like manage a team of agents and just the efficiency that you get with very similar or even greater results is like pretty, pretty amazing. I think this, I absolutely think this is like something every like CRO should be paying attention to is really the efficiency gains and how you can just grow faster with, with AI.

Yeah, I think it's existential. Yeah, I think, like, I, I think, and I was saying before we recorded, I just got off the stage with Jason Lemkin at SaaStr, and we talked about go-to-market, um, AI. And one of the things I shared was, like, I think the competitive advantage of, of being AI native is so great that if you're a company run by a CRO who really gets it and is, like, all in, you're going to outcompete everybody in your market that isn't adopting. And I truly think that, like, people will get left behind in a way that is even more profound than if you were resistant to the sales acceleration boom. Like, if you were using Salesloft and your competitors weren't, you were booking way more meetings on a per BDR basis. And I think it's going to be even more profound and a bigger competitive advantage.

Yeah. And I would even go as far to say like there's like two categories of like kind of like AI CROs. There's ones that invest in like copilot solutions, which I think gives you one level of efficiency. And then there's like fully agentic solutions that are coming to market. And I even think that like the copilot solutions that are coming out are like, it's like merely a stepping stone, like the rate of change that, you know, foundation models are you know, getting better and the capabilities of like agentic, like software, like I really think like there's going to be like a wave of like 2 to 3 years where like these copilot solutions are, you know, really viable and they're more efficient than, you know, just, you know, really large, really large teams individually managed. Um, and then I think kind of like the next wave is like, like when you just operate fully agentic workflows. and you really don't even, you know, need, uh, like, you know, need, uh, yeah, like kind of these copilot, you know, tools. Like, so like as a CRO, that's like really how I think about it is like, okay, you know, for the last 10 years, most of us have operated, you know, with really just managing like really, you know, large teams of different, you know, different functions within a go-to-market organization. Okay. That's if that's like your current state today, how do you like get from there to like a fully like agentic workflow and really like think about making that stepping stone. I think like, like a natural progression is being like, okay, first step, I'm going to go from like, you know, leveraging AI to do like Copilot, you know, messaging. There's like a number of like pre-call research products on follow-up stuff. Yeah. Yeah. Where you're essentially like using, yeah, AI for research. Yeah. And like getting scripts, etc. And I think that's like phase one. And then I think like phase two is like really investing in fully agentic workflows. I really see that as the future. Yeah. And so that's actually like by and large where like the internet is going to. My last role I worked like we were the leading, we had like about 80% of the market share for WhatsApp business messaging. I really see the internet as like itself as like becoming conversational or like moving from these structured workflows to like these unstructured workflows. We're moving from like clicking and searching on websites to speaking with like natural language. We're moving from, you know, computers speaking. We're moving from humans speaking computer language to computers speaking human language and I think, you know, we'll like a lot of the way that we interact with like the internet will be, will be through agents and will be, be conversational. And I think that's something revenue leaders should like really think about is, okay, in this dynamic that, you know, buyers are used to speaking with, you know, agents to make transactions or to navigate the internet or to research and look up things like How can we, you know, build revenue teams and customer-facing sales teams that really, yeah, really, you know, mirror that?

Yeah. And so I want to get into what the org actually looks like at 11x, but just explain what a digital worker is.

Yeah, a digital worker is essentially, you know, it's also called an AI agent. We have two digital workers. We have Alice and Julian. Alice is an email agent and Julian is a voice agent. And essentially what a digital worker is, both Alice and Julian are conversational interfaces, one's through email, LinkedIn, or WhatsApp, and the other one's through voice. And what these agents do beyond speaking with ChatGPT is they they perform really complex workflows. They, you know, do identification of prospects, they do personalized outreach, personalize the messaging, and then they do all the updates of the system of record. So upon having a conversation with a prospect, they'll go into, you know, your CRM, Salesforce, update that lead, update the contact information with all the research that they've done. It will record the call and log that in the CRM, or it will provide the, it'll provide the email, email transcript as well. So that it really creates a new marketing qualified opportunity, and then books a calendar invite on that sales person's calendar. So that salesperson shows up, they have a meeting that was booked via this digital worker, and they are ready to go. It's fully qualified and they have all of the research and information that an SDR would have typically done and they can begin their sales process there.

Okay. So how much is— so actually, first question, how many BDRs and AEs do you have today? Human ones?

We don't have any BDRs, um, and we have— okay, we have about 17, uh, salespeople in the company.

Okay, full cycle, they're doing some prospecting.

And, and the most impressive thing is I've never been at a sales organization where the AEs have not asked for more SDR support. And I know someone on my team will probably listen to this, but I haven't heard anyone say, you know, we need, we need more BDRs here. Um, it's really interesting.

And so how much of their funnel is coming from digital human outreach versus their own outreach?

Uh, over 90% is coming from a digital worker outreach.

Okay. And, and are— is that centrally orchestrated or is each rep running agents that are doing outreach on their behalf?

We will, we have plans to, you know, move, move more towards that. But right now it's centrally, centrally located. And that's how I see most, most organizations, you know, running, running these workflows. Like, you know, I just want salespeople to be really good at selling. I want them to have really qualified meetings and, you know, run those customers through a great sales process. And, you know, really be focused on closing. And I see that these workflows are really being, it's kind of like we've seen this trend of like SDRs reporting into marketing, you know, which has emerged. And I think with these like agent workflows, you know, it really makes sense, you know, for, they're almost like managing like campaigns through agents. It's growth marketing. It is growth marketing.

At the end of the day.

Absolutely. I really think this is the future of, you know, marketing in a lot of ways. I mean, if you look at this, like, I always like to like think of like kind of like the future and like what 10 years ago looked like, what 5 years ago looks like and what things might look like, you know, today. And like for sales, 5 years ago, if you wanted to explore a new market, you would hire a new BDR team, place them in a new city, wait 6 months for them to ramp up and see if it's working or not. And continue to invest more or less based on that. Today, you can hire a team of digital workers, place, target a very specific geo, very specific vertical, and send like really personalized messaging there overnight. And then on the marketing side, like, you know, today or 5 years ago, you'd send an email from like marketing at, you know, genericcompany.com, like marketing@dell.com or marketing at, whatever, no specific company, and you just send a lot of like updates about your company and hope to book meetings off of that. And it's like really personalized and everyone ignores those messages. And then today you can have, you know, marketing team really manage a team of agents and, you know, manage Alice and, you know, Matt and a bunch of digital workers that work for that company have really highly personalized messaging that reflect your brand, reflect the markets that they're selling into, reflect those specific verticals and have much higher conversion rates. That's really interesting.

And so what type of volume is Alice doing every single week? Or is like, do you put in a certain number of accounts that corresponds to the capacity of the sales rep? base that you have, or are they making determinations? Like, what, what's the coordination that the, that the growth team or growth engineering or whatever you're calling it is doing to get the right volume into funnel?

Yeah. Yeah. It's, it's the exact same way that you'd manage an SDR team and really thinking about pipeline. Like we have, you know, we have partner qualified leads, marketing qualified leads, sales qualified leads, and we really think about, um, you know, digital worker leads being a part of the marketing qualified lead. And we expect, have a predictable ACV. We have a predictable close rate that comes from that channel. Um, and it develops over time and we track it and we, every month based on our targets, you know, really look at, you know, the volumes that we anticipate from those digital worker campaigns.

Okay. Could you turn it up 2x in like a week if you wanted?

Um, yeah, we could run more, like more, more campaigns. Like, absolutely. I think there's like a lot of different ways to do, yeah, to do outbound. Like we, uh, like we absolutely have done that in the past. You know, we'll like look at like closed lost deals and run some additional campaigns there. It's like, it's actually really interesting. Like it formally with like SDR teams, it's really hard to run multiple different campaign types.

I've really seen that with us.

It's like, you know, you're kind of doing outbound and you're like, okay, well, we're doing this event next week. Let's do that. Like if we see that we're, you know, short on pipeline or want to accelerate a given month, we can get together and, you know, create a strategy on a new campaign type to run with digital workers. And we don't have to teach a team of, you know, 20 people to stop what they're doing and start doing it. It really is a team of, you know, you know, 3 to 5 people, um, who are, you know, coordinating these campaigns and running them to a specific segment of our business that we weren't necessarily marketing to before and trying to get some pipeline acceleration out of it. I also see this like these kind of like rapid iterations with, you know, releasing new products, new pricing. Um, it really enables you to move a lot faster in that way.

Hmm. Um, are you doing any outbound calling on top of the digital worker campaigns?

We do speed to lead campaigns. So if someone, um, calls in, uh, or someone completes a lead form, then we reach out to them with a digital worker and qualify them, uh, and then book a meeting via voice.

So that's not even a rep. That's Julian, the voice agent.

Yep. And that's really interesting. We see like a significantly higher conversion rate on speed to lead based on when someone who fills out a form is contacted. So like if someone fills, if someone is contacted within a minute of filling out a lead form, they convert like a 10x multiple higher than if someone is reached out after 5 minutes. And, you know, with AI, we can predictably do that like like every time. Like, and it's, it's really interesting. We're placing like things as rudimentary as like a voicemail. Like there's like leading media companies that like after hours will have like a voicemail if you call their sales line. And, um, or like, uh, you know, or if you fill out a lead form at, you know, 10 PM on a Friday, um, you know, you won't, you're not gonna hear it till Monday. Um, we can have digital workers like call 24/7 based on when someone completes a form and we can get a lot more information than someone would fill out in a form as well. Like, you know, this is like kind of like the structured to unstructured workflow. Like just candidly, like no one wants to sit and like fill out like, this is why I'm contacting you. Like it's like name, email, phone number. But when an agent calls you, you can have a conversation. And it's a lot easier to share information and answer questions. And it's very relevant because you just filled out the form a minute ago. And these types of workflows are really, really interesting. It's like one of the biggest insights is like you can absolutely capture more information in a more natural way. You know, with, with like a voice interface than with filling out a random lead form on a website. Mm-hmm.

One of the things I think folks struggle with is, you know, they look at 11X and using digital workers makes so much sense because you're selling digital workers. So like when I, when I'm contacted with like pretty good outreach from a digital worker and then I have a voice agent, it's going to resonate with the buyer because they're trying to buy that category of solution. And I think the question is, you know, how much can you apply that learning to other markets where, like, we won't use owner as an example because like SMB mom and pop restaurants are like probably a trickier category. But if I'm trying to sell HR tech to like CHROs or VPs of HR, Like, how do you know, how do you know what level of AI is going to resonate with the buyer versus how much human touch? Like, you guys doing no outbound calls makes a ton of sense. But it would surprise me if other non— like, if you're selling, like, you know, non-AI solutions, if no outbound calling is the right fit. Like, what's the process of figuring out Are there particular markets that you guys are dialed into? Are there buying types? How do you go figure out, can AI work for me?

Yeah, that's such a great question. I spend so much time thinking about this as well. Okay. Yeah. It's really like everyone is in this experimental phase. And what we focus on are use cases that we know consistently work. Like the speed to lead after-hours use case, like the alternative, you know, is a voicemail or someone calling you back multiple days later. Like that, you know, those use cases like very specifically work. I think verticals are really interesting. We like see like even a mix of like non-tech and tech, you know, verticals that, you know, that have success with digital workers. Like it's really like if you have like a Salesforce you know, you can really automate it or automate definitely a portion of it through digital workers. I think the biggest determinant that I really see, and I think this is like really interesting of companies being successful with their AI, is willingness to like, and like excitement almost to learn like AI, best AI go-to-market best practices, like, you know, learning how to prompt, um, learning how to create, uh, templates that have fixed text and AI-generated text, you know, within them. Um, there's like actually a much deeper level, like we were talking earlier about like companies that experiment with AI tools, and then it's companies that understand, you know, how to use AI tools, especially building, like, focusing on customer success. This is something that we're really, really focused on. There's really— I think the companies, the AI-native companies, or the companies that build AI products that are going to be really successful, are, are like experts in really educating their customers on how to use, uh, AI tools, how to, you know, do basic level prompt engineering, how to understand how to, uh, you know, set up agents to integrate into, you know, CRMs. And great products make that, you know, as easy as possible, um, and really understand these like agentic workflows. I think that like determines, like, that's like what really determines like good from great, uh, clients is ones that are like, oh, AI, I should try it, versus like, oh, I really believe in this, this can transform my organization. I really, you know, our customer success teams are really educating them on like AI GTM best practices. This is how I should think about prompts. This is how we can work together to build prompts for specific markets, specific verticals, specific use cases. Um, and I think, uh, that's like really the future of like companies is like, uh, and I think that like gives us like an advantage, like everyone who works like at 11x is like really AI oriented and like knows how to like, it's like really like knows how to use these products and tools and build them. And I think the companies that really succeed in this era of adopting AI software are the ones that are really focused on, you know, teaching their, you know, workforces like how to, how to use AI effectively. Something I'm like paying attention to like, like Like every day, like, like that's like number one interview question I ask people is like, how do you use AI in your workflow? And I'm always trying to learn from, you know, different salespeople of how they're, how they're getting better and leveraging that.

I've mandated this for management and sort of leveraged IC roles. I said that I've told my senior leaders, I'm like, if you're hiring managers, I need you to ask about AI, and if somebody has no answer to it, then they are disqualified. Yeah, because— Yeah, I would imagine you do for sure. But it's the level of importance that I think this has, and I think you just need to drive the adoption. I loved Toby's letter. Yeah. Shopify. There was another one that was just written by the guy from Duolingo. Like it's now a theme.

Yeah, absolutely.

So you mentioned teaching AI best practices. So I wanna unpack a couple of those. So focus on teaching your workforce how to use AI. So making your organization fluent is obviously one. What else are sort of the AI transformation best practices? If you're, and let's focus on if I'm like AI curious, I've only done a little bit of, I've only like dipped my toe in the water. I've used ChatGPT a little bit, but I'm not, I'm not deep in it, like, where do I start?

Yeah, yeah. I would even like zoom out. Like, I think like a lot of organ— like sometimes in companies, like company culture of like AI, using AI is cheating. Like sometimes people feel that way and like that is like one of the most like harmful things that you can have within your company. Like you really need to like encourage everyone to like fully embrace this and share the way that they're the ways that they're using AI. Yeah, get in the weeds, like use everything, like experiment like 4 to 5 AI products, like talk to other CROs, ask them what products that they're using, try them out for yourselves. Like have a really experimental mindset. If you rely on your teams to use these products and don't use themselves, like I love that you're like, you know, vibe coding on Windsurf. Like really get in the weeds and like really deeply understand that. I've always seen the best— that's like the one trait I feel like is always the like really consistent amongst like the best CRMs is they use their products, they use their tech, they really understand, uh, like how their tech relates in the ecosystem, like why it's better than other competitors at like a really like, like a user level. And I think like, like You know, this is like a time where like CROs like really need to lead from the front in terms of, you know, teaching teams how to use like AI tools, like teaching teams like how to like, how to prompt, um, teaching, you know, teaching teams like really like how to think about, how to think about this tech, like using ChatGPT and like Claude to like do basic research is like, that was like, that was like new 6, 12 months ago, but like it's there's like, there's like so much, so much deeper levels. We're using this product recently, like called like, like Quilt, and it like automates like full security questionnaires for our engineers. And it saves them like, like hours of time. And then we're looking at using like Glean for our CS teams. And yeah, it's just like, it's like really like getting in and seeing and like really like starting to think in this, you know, in, in this way of like these product workflows. It's really, uh, it's, yeah, it's, uh, it's like an absolute like necessary skill to have.

And you got to take the demos, you know. It's, it's, it seems overwhelming and it seems like the last thing you want to spend 2 hours a week on, but this is advice I'm giving to people. It's like you just got to take the demos as much as it seems like, uh, not the best use of time. You got to figure out what's out there, what's, what's possible. And whenever I take these demos, one of the things I say to the founder, I'm like, I don't really want the product demo. I want you to show me like live use cases. Like show me what customers are doing and the art of the possible. Because really what I'm trying to do is, yeah, I want to see the product, but I'm trying to see like what is, what are the most sophisticated companies doing and and how can I, how can I mimic it?

Yeah, that's such a good point. Like, the way that I learn about how our products work is I go to our most successful, like, customers and I impersonate, like, their workflows, and I look through them and I am like, wow, this is like, this is why you're successful. And yeah, and it's like, it's really interesting. There's a high correlation with the companies that have, that are building AI products and the companies that are successful using AI products. Yeah, yeah, for sure. It's, it is like, it's like a night and day correlation there. And I really, it's a cultural thing, you know, it's these organizations that are operating in this way and thinking in this way and building in this way. And then they're using all of these different products and tools in this way. And then it's, it's really interesting. I can look at two companies in the exact same vertical. And one is, you know, has like an AI mindset, same like TAM, same, uh, you know, ICP and just the way that they're, you know, building workflows. Um, the way that they're, you know, prompting is, um, it's, yeah, really, really interesting. And like, that's why I'm like really so focused on like, you know, for AI-native companies today, like educating, having like really great like education practices on like how to teach your customers about AI even outside of your, the scope of your, you know, products is really, really important.

Yeah. So what are those primitives? Like you mentioned prompt engineering is one. If I'm a CRO and I'm trying to go sort of fill in my mental model of what is AI and how can I use it, like what would be the baskets of things you would tell somebody to go learn?

Yeah, absolutely. Yeah, that's a really good question. If I were like a CRO and I'm like really like trying to, you know, I'm not using AI products, I'm really new to this. Like I would like, I think like first I would like really look at like, I would go to all my leaders, right? I go to like RevOps, I go to my SDR leader, I go to my AE leaders, I go to my sales managers and I would ask them, to each come up with like 3 to 5 different solutions in ways that they can leverage, you know, AI within to optimize their teams. And I actually wouldn't have them go and pick specific products. I was saying if you could have like a single product or like what is your team like, if you could like build like any specific like, you know, product to like really make your team like 10x more efficient, what would it be? And I think then like within each of those teams, we would do like a mix of like, okay, let's pick like 3 of those 5 use cases that we feel like are most important. Let's, uh, let's see if like we can build like, you know, through like through LLMs or through like, or through like discovery of like products on the market, like how we can really solve that. I think it's like, it's as that, that type of like leadership is as important as hiring. I think that's the new way to hire almost in a lot of ways, is like instead of like finding people that are really specialized and can find solutions, like really great leaders can go out and identify, um, identify products or identify, um, you know, workflows with like Claude or ChatGPT that can like really make their teams more efficient. And I would like hold all my leaders like really accountable to, um, to building, yeah, building those different solutions. And that's not— we're a pretty small org, I mean, but that's not too far off the way that I speak with my leaders, you know, today. It's like we're really like all focused on, you know, identifying and bringing forward like 3 to 5 different AI solutions a quarter that can really help us, you know, grow and scale as a company in addition to what we're, we're, you know, building ourselves.

Yeah, that makes sense. It— so fill in the blanks for me here. So if, if I was going to tell a CRO, like, these are the baskets of things you need to figure out. So I think it's the tools, like, go learn the tools, figure out what are the foundation models, what are the core things in a market. There's prompt engineering, there's something around architecture. You got to figure out how some of this stuff like plugs in and works with one another and not as deep as like you got to go learn Python and figure out how APIs and webhooks work. But like you have to think through the map of how all this stuff is going to work.

And then I would say it's like—

and the last thing is like, and the art of the possible. And then just go figure out what the coolest use cases are out there. What else would you say are like the categories of education or learning people need to do?

I think like agents, people really like, I think a lot of people like nod their heads when they like talk about AI and like agents and they're like, this is really new and like, like really understanding like what agentic workflows like, like really mean. Um, yeah, it's actually a question I like ask a lot of people. I'm like, oh, do you know what like agents, you know, like really, really do? And cause it took me like a really long time. Like I was totally that person at first. I was like, yeah, I kind of know what an agent is. It's like an AI. Person, but it's actually so much deeper than that. It's like, it's a conversational interface that connects— that is like an application layer that really connects to all the systems, like all these different systems of record, and, you know, does like— does work, like makes, makes updates, makes purchases, you know, processes returns. Like Claude and ChatGPT are like not— are not agents. They are just in today's form, the way that 99% of us, you know, use them, like, you know, it's really just, you know, using it as an LLM to have, you know, conversations and, you know, maybe build like a chart or graph. But like a lot of these, you know, new products that are coming out are like fully agentic workflows that automate multiple, you know, different connected systems and really replicate, you know, a lot of different workflows and I think doing a lot of research into this, like, into like agentic software is really interesting. Like, if you— I think that's— there was like this Satya video I watched like probably 6 months or a year ago. And like, this like agentic software truly has the ability to replace like traditional B2B SaaS. It's an entirely different way of building. Now we're moving from business systems that are built on like SQL databases and rows and lookups to like full, like, you know, LLMs that are connected to multiple systems of record and, you know, making updates. And by the way, those LLMs are consistently getting better each month. And it's just a really different way of building software. And I think being in touch, in tune with the market and, you know, how these companies are being built and how, what new products are coming to market is really is really critical for revenue leaders.

Yeah. It's tough too, because everybody's calling everything an agent now, you know, anything that's AI, it's like, oh, this is my AI agent. And I, my definition, which is more of the like old school definition is it has to be able to reason, take action, and then, and choose from different paths and access other tools. And if you're Agent takes in input and then does a thing. That's an AI workflow. But I think agents need to make decisions about how to solve a problem, then be able to access multiple tools to solve that problem. That's a much higher bar than I think people are using the word agent for. But Sam Altman has that same 5 levels of AI. There's sort of the chat is level 1. And then like vertical SME. So it's, you know, it's a tailor, it's a, it's an AI that's tailored for something like quite specific. Then there's agent that can execute, like decide and execute. And then the fourth and fifth start to get into like AGI, ASI, like kind of, I don't even know.

I'm not there yet. Yeah, yeah, yeah. I'm sure someday that'll be Yeah, more, more, more relevant. Yeah, it's just like, like, what work is it actually doing? Like, I, I really think like the conversational, like, you know, chatbot interface is like, is, is, is like really phased out, and it's really like, what, what work is— like, what work is the agent actually doing and automating?

Yeah, yeah, for sure. Um, a question I get all the time is like, okay, cool, so you— I got to go learn about these things, like, where do I go? There's no course. There are courses and most of them suck. I, I, sorry to anybody building courses, but they get out of date so fast. And, and, uh, you know, there's no book on it. Nobody's written like the book that's going to be topical for more than 60 days. So like, where do you direct people to, to try to start learning this stuff?

Yeah, it's hard. That's a good question. It's hard because there's so much noise out there. Yeah, I think the best way to learn is like you said, demos and exploration, like having, talking to other revenue leaders, understanding what people are using, understanding if they're having success. I think there's also a large part of understanding like, like, yeah, like understand like why companies are being successful with, with like really specific tools. Because I think like there is like something I was talking to, I was talking to, I was having a call with Gokul Rajaram the other day and he was, he referred me to this article that was really like talking about like buying agentic software as like being like the early days of buying like SaaS or cloud-based software. And like companies, like, you know, really don't know how to— like, like in the early days of software, like teams didn't know how to use cloud-based software. They were like, yeah, totally new and novel to them. And, um, you know, it's— I think we're very much in that same age now where, um, I really want to find, like, I really want to find the companies that are being successful with, with AI. Because I think that's like, I think being successful with this type of software is, it's like two, it's like two, two factors. Like one, like embracing the idea of buying it, but then two, like embracing the idea of like operationalizing your teams to like use and invest in it. And I think the, I really want to like learn about and speak with like revenue leaders who are, yeah, built like building like Yeah, like AI-native operational teams, like, like really like leveraging like AI across, across like multiple parts of their revenue organization and are having success across like multiple different products because that's like the difference of like, that's like someone who like really gets it versus like the difference of someone who like has had success with like one, one individual, you know, product or tool.

Yeah. Yeah. I tend to agree with you here. Like, you really have to find a group of people that are also on this journey and spend time like figuring out what they're doing. You know, Kevin "KD" Dorsey is a guy that I spent a lot of time texting with. Like, he's doing— he's seeing demos, I'm seeing demos. We're like trading articles and X posts and that is where I get a lot of exposure.

Yeah.

I think like finding that group of, of other people in the same role to go along with, I think, I think is good. Pavilion's pushing big into this right now because everybody's trying to figure it out. But like community, I think is a big part of it.

I think there are two groups. There are like people that are kicking the tires on it. And then there are people that are like really operationally investing in it. And I think like, yeah, it's always trying to find those like leaders and those organizations that are like in the latter camp that are really are investing in these tools. Like, yeah, like I, I see like, you know, organization, cause like when you make these operational and organizational changes, it doesn't happen overnight. You know, like you're not going to have success the first like time you use one of these tools. It's going to take— there's a learning curve for sure. And there definitely are the organizations that embrace these tools, try one or two use cases, and are like, oh, this didn't work. Um, it, it doesn't work for me.

And then, oh, it hallucinated. It's no good.

Oh, it hallucinated. Yeah, it's not good. And then there are organizations that are like, no, this is a different way of working. We are going to make this work. We're going to like really operationalize our teams around it. We are you know, going to look at it from a lot of different angles. We're going to learn how to, you know, prompt agents in the right way. And those customers are really, you know, really successful. And, um, yeah, I think there's like a really, yeah, really large part around, um, yeah, around like, you know, like committing to this, uh, like AI operational workflow and like, and recognizing that is a really significant change from the way that you're teams have interacted with, you know, previous software. This is very different than like buying Slack and implementing it or buying Gong or buying Clary or these like, you know, simple tools that, uh, you know, just plug into, you know, Salesforce and provide a forecast report.

Yeah. It's, I mean, Slack in the early days was a big change going from like email to this that I would say that's, that's actually a sort of a good example. Of like the scale of transformation. And so, um, you, you mentioned before we recorded, you know, this, this like, uh, we wanted to dig into first principles thinking, you know, how do you, how do you solve problems from a first principles approach and not get caught up in just like doing what everybody else is doing or reasoning by analogy? So Uh, maybe you can answer that question more generally, like, what is it about first principles thinking that's so important and how do you do it? And then let's get into how do I, from a first principles perspective, think about my AI journey in my, in my company.

Yeah, absolutely. Yeah, I've always like been a really big fan of like first principles thinking. Um, uh, it's like I, I feel like something that's like really important for like a revenue leader is like really breaking apart sales into like very specific steps for all of your teams. Like, I love this like sales stage matrix template that I, you know, really use. It's like, you know, and I really talk to like early founders about this like all the time. Like a sales process is really like 5 or 6 steps focused, like broken down into, you know, activities, gives, gets, exit criteria, and resources to enable each stage. And I think with, this is like a moment, like sales leadership, before used to actually be really prescriptive of being like, hey, in the sales process, these are the very specific things that we're going to do at each stage. These are the resources that we're going to use to really get through a deal and complete like a successful, you know, experience for a customer. And, um, now I'm like very like, I'm like rigid on the exit criteria, but I'm like very, uh, I'm like much more experimental in the operational, uh, operationalizing the stages. I'm like, you know what, let's like really like use like different, you know, I wanna really learn from my team, like, you know, different ways that we're Planning demos, creating resources, how are we using AI within each stage to make a better sales process? It's kind of like, I feel like this is like a time of kind of like, yeah, be like really like breaking down, like, you know, how can we be more experimental as revenue organization? And I think from a first principle standpoint, it's kind of forgetting a lot of what you know in some ways. And 11x, we've been an AI-native company and we've focused on, we just built the company really based on a lot of the early results that we've seen with digital workers. We don't have a standard AE to SDR headcount that really you know, doesn't exist. The way that we plan, you know, quotas and, you know, attainment, you know, is largely based on results that we're seeing with this go-to-market motion. I think, I think sales has been like kind of boring for the last like 10 years where everyone's like copying the Salesforce playbook. It's like a million dollar quota per rep and yeah. This is a time where kind of like building these companies in a new way, you can be more creative and really design a go-to-market org and a go-to-market process in, in a new way. Definitely using a lot of the same frameworks that have always worked, but being like, yeah, more experimental in some of the activities or headcount ratios or target settings that, you know, we've had, we've had in the past and like constantly refining on this because, yeah, I really believe this new operating model is going to create new standards of efficiency for companies. And yeah, there's, I think, a lot of first principles thinking. Yeah, you know, it's a, it's a good mindset to be in.

And so how do you become a better first principles thinker? Because I think, you know, the headcount to, or OTE to quota ratios and the headcount ratios and how do we run sales stages, you know, those were derived from something good. And so how do you delineate between, you know, outsourcing critical thinking to best practices versus like being a first principles thinker? How do you get better at at that?

Yeah, yeah, absolutely. Um, I think just like first being really close to the— being really close to the data, um, you know, being really close to your teams, like, and then like what I really think like first principles thinking is, is just breaking everything down into like really simple steps and like analyzing each, like each individual step and thinking and kind of experimenting if you can make it more efficient. Um, that's actually like, like, uh, that's like a mindset that I've always like really, really had. Um, it's like I used to do like rowing and like you'd like break down like a stroke into like very individual parts and you try to like, you'd really focus and like try to optimize each part of like putting the blade in the water and that made the boat faster. And I really think of sales the same way of like really breaking down like each part of a sales process or each part of a marketer's role or partnerships role and really like understanding what goes into that and being like, okay, can we make this better? Can we optimize this more? Can we do this more efficiently? Can we do this at higher quality? Can we do this with the power of 10 people with 2 or 3? And really like, yeah, breaking things down in that way.

Yeah. Um, so being closer to the data, breaking things down, anything else to become a better first principles thinker?

Making bets, I think, you know. Um, I think this is like a new, you know, this is a like a very like new you know, era of growth for, you know, companies and a really new way of working. And there definitely is a degree of, you know, making multiple bets on, you know, different workflows, different, you know, tools, you know, trying, yeah, trying new, you know, operating motions and just, yeah, being a little bit, being a little bit more, more creative. And like, you're definitely going to fail, you know, sometimes, but, you know, as I think I mentioned earlier that like, I really liked that quote you shared where like, yeah, like 1 out of 5 of them works out, like the results of, you know, one of those 5 workflows is like a really huge win and you just drop what, you know, didn't, didn't work out.

Yeah. I, I definitely agree. Like being close to the data is, is so important. I think the other. part of trying to become a really good first principles thinker is like understanding what the heck is going on under the hood from like a human perspective. I tell people a lot, it's like, if you want to get better at building these systems, learn how humans work, but like learn about behavioral economics and psychology. And because oftentimes things don't make a lot of sense until you can understand, like I was trying to teach my— this is a good example. I'm trying to teach my team how to run better SPIFs. And so, I would talk about, I'm like, look, you don't need to SPIF everything. You don't need to make people chase some incentive for everything that we want them to do. And I was having a hard time getting them to understand. And so, I shared these two psychology papers on the overjustification effect. Basically, the overjustification effect is if if you overly incentivize some sort of action or activity, what you find is that it actually lowers somebody's natural motivation to do that thing. And there's a bunch of cool studies in sort of early childhood psychology on it because you're now taking— it's the difference between internal locus of control and external locus of control. What you want to give to people to get maximum motivation and drive and action is for them to want to do the things that are good for the business for their own individual reasons from an internal locus of control. So like, because somebody suggested, oh, like if people dial late tonight, we'll tell them they can expense dinner. I'm like, no, flip it. I was like, tell people that we're grinding, we're going to dial late, and whoever shows up, just be like, hey guys, I appreciate you being here. Get lunch or get dinner on us. And it's very subtle, but you've like allowed somebody to have an internal locus of control, make the decision that they want to put in the work and dial into the evening to hit their number and try to help the company get to their goals. And then we're rewarding them for doing that action. And so it's— and it has a very different motivation effect. And I think like once you— this is what all the research would tell you. And like once you can start to understand like how people, how people work, then you can rederive, okay, how to build a sales process and automation or your customer journey from these like, you know, like very core things that are under the hood.

Yeah, I just wrote that down. Like, yeah, that's, I can think of so many examples and I think like, that's so cool. Like I think the best like sales leaders are like really like like, like really like understand, like deep, deep understanding of psychology.

Yeah.

And how to motivate teams and how to make people feel really fulfilled.

You know, I'll send you the papers.

Yeah, please do. Yeah. That made me think of like, like I was like, I remember, I remember like, but like about a year ago, I was in like Mexico City and we sat in a call center for like like 300 people with our CEO at the time. And I just watched people like, you know, do, do like, do their work. Like, and like, they were like, yeah, like using all these like different machines and workflows. And, you know, just looking at that, and like seeing how we were building that, you know, out, you know, via WhatsApp was just like, it was really interesting. It like helped me understand like just on such a deeper level, like what really like what we were like building with an agent and how, uh, we had like an agent assist platform and was making their, you know, job a lot, a lot easier. And I think, I think it's like very much the same with like sales. And this is like a really unique time for revenue leaders. Like we can sit with our teams and see their workflows and see what they're doing. And, you know, it's, I think that's like a new skillset of like a revenue leader, just like as you described, like this, like locus of control, like you know, see, see like your team's workflows and like really like, like sit with them and analyze them and like, you know, just like come to them with like ideas that you can make their jobs easier. Like that's like just being an amazing, amazing leader.

Yeah, yeah, yeah. It's, it's, uh, fascinating to see how many folks do the wrong things because that's how we've done them And then when you learn about the, a little bit about psychology, you're like, oh, like, of course that's not working. You know, the, there's this other thing that I, that I talk about a lot, which is like fuel versus friction. And it's from behavioral economics. Like we want to add fuel to everything, like more motivation, more push, more, more, more, more, more. And really what you need to do is just like take friction out of the things, take friction out of the things that are unpleasant to do. And so, yeah, like this is nudge theory from behavioral economics. Like if you want people to make dials, make it as like insanely easy to do that as possible and add like, take all the friction out of it and add friction into the places that you like don't want them spending time.

Absolutely. Yeah. There's this quote that we have in our branding that I really agree with. It's like, be more human. And I think there's like kind of this whole like, you know, humans replace like SDR, like agents replacing humans and, you know, AI replacing humans like, or SDRs. But I really think like it's this opportunity to like be more human. Like, I think I heard in like a podcast a while ago, like, you know, like agentic workflows are really going to like automate a lot of like the butter passing roles. And these are the roles that like no one, no one really likes to do. And they're really, they're like really repetitive tasks. And, um, yeah, I think that like it just removes friction and people are really going to opt in to, you know, yeah, like really like removing friction from their like day-to-day workflows and yeah, being more human. Yeah.

And, and like what of a sales process or customer journey can a human uniquely do? And, and I think because a lot of, you know, if it's not complex, if it's not very challenging, AI is going to figure that out pretty, pretty fast. What one of the things that Jason said on this keynote we did today is like the mediocre rep is basically cooked in the next 12 to 24 months. If you're sort of like punching a clock and you're like not that dedicated to your craft, AI is going to basically they take like every single one of those jobs. And what's left is like customer-facing roles with more sophistication. First question is, do you agree with that sentiment that the bar of what it's going to take to be, you know, a sales rep in tech is going to go way up? And if so, what do people need to focus on to be future-proof in an AI era?

Yeah, no, that's a great question. I think a lot about that. I think what's going to be really hard for this next group of folks that go into tech is so much of the— so many of us learned from knocking on doors, like the square, like showing up to restaurants and people telling me to go away and just being really repetitive towards that. Build a lot of callus. And then there were a lot of entry-level roles before of really large SDR teams where you'd come on, you could shadow a lot of AEs and you could open up meetings. And I think those, a lot of those roles are getting automated. Like, so I think it'll be harder to step into these. I think it will definitely be harder to step into sales roles. And I've heard, I've had this conversation with a lot of different like revenue leaders and yeah, for like, you know, just like in that, uh, kind of like in that scenario, the talent density for sales does get a lot, does get a lot tighter. Um, you know, and I think it's, I really look at it like, it's like the A role, like evolving, you know, it's, uh, it's kind of like, you know, 15 years ago, how like, you know, the cold calling sales, you know, person was you know, with a suit was really successful. And then, you know, like, you know, in the last like 5 years, it's folks that like, you know, are really personalized, are experts at their products, um, you know, uh, have like really great outreach, like, you know, really good hunger, hustle, instinct, like, you know, are really great at really like smart and consultative, you know, technology sales, you know, folks. And then, um, You know, now it's evolving into kind of this new era of, you know, sales folks that, you know, use AI. There is like a— there is more of a talent density. And I think a lot of like tech sales is shifting to education on AI and education on the future. I think that if I were to pick like one skill that I think will really separate like kind of this next group of like, we're like future-proof like sales. It's like really educate, like being education-oriented around building like a high degree of trust with buyers about how to use AI, how to build an AI organization, you know, what that, the from-to, you know, what that looks like. And yeah, really being able to like, yeah, teach and educate in that way.

Yeah. I mean, Challenger hit on that 2008. So it's like more of what has always been, always made the best reps great. Yeah. It's going to be fascinating how we solve that early career problem. I don't have an opinion on it now. I don't have an answer. But what do you do when agents can do like 90% of SDR jobs?

Yeah. And then that, you know, that I, I think that pushes, you know, then agents to doing, you know, some of the later jobs as well. It's, it's really interesting.

Yeah. Yeah, we're— I mean, I think you're going to just have to triple down on training and find ways to, to level people up before they can really even talk to customers. And we're using this like AI sales simulator with with this company called Avara. And so because we want to get reps so many more repetitions before they talk to a customer, because the cost of every lead is so, is so great and the opportunity cost is significant. And so maybe that just needs to be like pulled all the way forward. You know, you need to do tons of practice and role play in an AI sales sim before you can let your team talk to customers because customers are going to expect so much.

Yeah, I really think more about sales enablement. I think that is absolutely going to become, you know, more, more valuable. Uh, especially like, yeah, creating, creating like a higher bar, um, sales enablement, I think will be, it's like, yeah, just, just really, really, really necessary.

Yeah. Um, okay. Let's move to our quickfire. I got a couple of questions and we'll wrap. Um, what do you, what do you think separates a good CRO from a truly great one?

Yeah. Um, yeah, great question. Um, I think, um, really like deeply, like, uh, yeah, like deeply, deeply understanding your, like your, your customers and like having an amazing feedback loop between where your customers are today and, you know, the teams, the teams that you're building. Yeah, I think that is like, that is like the number one, number one, like skill set of a CRO is like, like educating and evolving your customers. And that was like, that's like, really like, especially like with when you're, you know, focused on like, selling a new era or wave of technology. It's like really educating your customers on what these new organizations look like and evolving them, and then really educating your team, your teams, and evolving your sales teams. I'm always focused on 3 things with building revenue teams is Really focusing on inputs over outputs. I think that is highly relevant of really focusing on high quality of inputs and really less on end results. I kind of have this score takes care of itself mindset.

One of my favorite books.

Yeah, I love that book. Really hiring A players, Just like building a team of people that love to win, are really deeply interested in the technology, really understand your customers and like love to be on a winning team. Like look for a lot of folks that like post like athlete backgrounds, someone who's like, you know, really pursued like a, you know, creative endeavor, like really high level folks that just like focused on being like the best at something. And then also like having fun. I like, I think it's really, you know, like I have this like concept of like mandatory fun with our teams that like, and we're like, we like all like really work hard together and like once a month we have this like, you know, mandatory, you know, fun where we like really come together as a team. And I think building relationships is really important. I think there's like a high correlation between, you know, being— having, yeah, really, really good, really strong relationships and then like making people be great. And like if you— the stronger foundation relationship that you have with your team, the more trust there is and the more you can really help evolve your team.

Yeah, I think it's a Teddy Roosevelt quote. People don't care. People don't care how much you know until they know how much you care. And that's very relevant with sales management. Like, it's really hard for people to want to listen to you and take your feedback unless they really feel like you give a crap about their career. Absolutely. What's the most common advice you find yourself giving new leaders, like new VPs of sales, people who are newly in a senior role?

Yes. The two skills that you need to build in a senior role is risk-taking and decision-making. I think, I think those are the two most important skills for, you know, uh, yeah, for, for a new leader. And I, um, I think like a really, like really focusing, you know, on those two and like really understanding that's your, you know, responsibility as, as a leader within an organization, um, is really important.

And risk-taking being sort of innovating, trying something new.

Yep.

Okay, I like that framework. Yeah, yeah, this is good. Um, what's the hardest lesson you've had to learn in your career?

Yeah, um, there's a lot. Um, let's see. I might need a minute for this one.

That's okay.

Yeah, yeah. Um, um, honestly, for me it's like personal, but like probably patience. Yeah, to be, uh, um, yeah, probably, probably like patience, I think. You know, it's, um, I think like you've got— and it's like It's, yeah, probably like, yeah, like patience and like really like when something kind of like resilience too. Like, you know, when you, you know, have like a tough quarter or, you know, or yeah, like some type of setback in your, in your career, like really having like faith and, and trust that you, and finding the right like mentors to like guide you out of it. I, um, yeah, I have like this mentor, like this guy Todd Miller. He was the SVP of sales at like Netscape. And I used to think, I'm like, oh my gosh, all these problems are just happening to me. Like, you know, this, this is like so unique. And then I just developed like a network of revenue leaders and I'm like, oh no, this happens to everyone. And all these other people have been through, you know, these things so many times and there's really great ways to go about it. And I think it's, uh, Yeah, I think it's really just like this, like, skill set of like, like, never lose alone. And when you kind of, yeah, when you, you know, have a setback, like, you know, have a really great group of experienced, you know, people around you to help you navigate that. And you really don't have to like, no one wins alone and, and like, never lose alone, I think. Yeah. Yeah, something I really liked.

Yeah. Last question. What's the—

Yeah, go ahead.

Last question. What's the best thing you've read in the last 12 months?

Yeah. Yeah. Best thing I have read in the last 12 months. I pick up this book like once a year. That's really helpful. It's called The Checklist Manifesto.

Oh yeah, Katie is obsessed with this book.

Yeah. And it's just like a reminder that like, and it's, it kind of goes into the first principles thinking conversation that we were having is like any complex workflow, whether it's making your bed or performing, you know, a heart surgery is really just a, you know, series of, of tasks that, you know, deliver an outcome and really breaking like any complex problem down Into Simple Steps. And I pick up that book, you know, once a year, just like, you know, as a reminder to like, you know, really just have this, you know, mindset of like, whether it's something I'm trying to optimize, really look, relooking at the steps and rethinking about how we're going about them. Or if it's like an entirely new problem or something that I want to achieve that feels really daunting. Really thinking about it in like a task or step-oriented way, a book is always a really good reminder.

Yeah, that's great. Well, Mike, this was awesome. I appreciate it. I think this is a great framework for people to use to maybe grok their first steps into an AI world. So appreciate you joining and looking forward to seeing you in Mill Valley soon.

Yeah, likewise. Yeah, thanks for having me on. This is great, Kyle.

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