E4: How AI will impact the role of sales with Zack Kass of OpenAI & Jake Saper of Emergence
40m 22s
The conversation, led by Alex Levin (CEO of Regal.io) with Zach (formerly OpenAI) and Jake (GP at Emergence), explores AI’s impact on sales. Zach recounts his early AI career, from Crowdflower’s data labeling to Lilt’s translation models and OpenAI’s first sales role, noting that the field’s rapid growth surprised even insiders, though Ilya Sutskever’s 2012 paper predicted it. Jake shares his path from consulting and a solar startup to venture capital, where he developed the “coaching networks” thesis—using AI to augment workers in human-centric tasks like sales—and highlights his career framework of breadth vs. depth and agency vs. risk, which led him to Emergence’s enterprise software focus.
On AI’s role in sales, Zach predicts the technology will handle routine sales processes within 18 months, driven by advances in speech, listening, and contextual data. He argues that consumer benefits—lower costs, no downtime, and consistency—will drive adoption, despite policy and trust hurdles, drawing parallels to mobile commerce. Alex pushes back, emphasizing that human empathy and trust still boost conversion, especially for high-value purchases, so humans will remain valuable as long as they’re slightly better. Zach counters that most salespeople underperform, so AI will likely surpass the average experience quickly, though top performers retain an “X-factor.” Jake suggests the interim period will see AI elevating poor reps’ performance, benefiting companies broadly, rather than immediately replacing the best. The discussion concludes that AI’s integration will be incremental, with humans and AI coexisting for some time.
This is Alex Levin, the CEO of Regal.io, and I'm here with Zach formerly from OpenAI and Jake, the GP of Emergence for AGP at Emergence. And I'm going to let them introduce themselves in a second. And then after their introductions, we'll get into a discussion of AI and specifically how it's going to impact sales, both in B2B and in B2C world. So Zach, thank you very much for joining us today from sunny California. Maybe you want to give us a little bit about how did you end up at this behemoth that famous company, OpenAI. And what are you up to now? Yeah, so I was lucky enough to start my career in AI at a company called Crowdflower, working for now a very prominent CEO, Lucas B. Wald, who at the time was just sort of like an entrepreneurial data scientist, this is 2009. And data labeling was sort of an emerging trend, albeit to a very small niche market, which was data science of which there just weren't many. And I didn't know it at the time, but I was really lucky to get involved so early in the category. I spent six hard years at Crowdflower, to be honest, it became figure eight and then sold to Appen. The market was too small, we were too early. And scale AI sort of came in at the tail end of our journey and took off. And that rest is history. But I stayed in AI and went to a company called Lilt, which was founded by two researchers, building large language models for the purposes of translation. They started that company in 2015, actually the same year that OpenAI was founded, which was an important year because it was just as neural nets were gaining popularity again. And the power of the technology was exploding. And then when it came time for OpenAI to hire their first sales leader, I happened to be one of the few people in the world that had done this. And yeah, and now the future is, I'll probably, I'm going to move to Santa Barbara, I've moved to Santa Barbara and I'm going to spend my time consulting with companies on how to build a future around AI. And eventually I'll run for Mayor Santa Barbara in 2026. In large part because I think that physical communities will be the most important thing we can invest in in the future. Liveable walkable cities is how people stay connected to each other. Otherwise they're just going to plug into VRAR headsets and tune out. And I think the world will bifurcate those that get on the wally bed and those that don't. That's a great introduction. So, if I can ask, when you think back to starting an AI repression, did you know this was going to be so big, so fast, or was this lucky that you applied to 20 companies and that was the one that said that? To be very clear, first of all, it was 2009 and I had, I was a volleyball player, so I had no fungible skills. And outside of volleyball, and there are hundreds of dollars in men's volleyball. So I don't recommend it to career to people. And I applied to three companies, Square, Airbnb and Crowdflower. Those were the three companies hiring at the time and I got a job at Crowdflower, actually is an intern at first and then Lucas just kept investing in me. I wasn't even impressed until, I didn't feel like I saw the future until 2017 when opening AI started launching the large language models. You know, they moved from Dota and Robotics to like GPT and it was very clear that we were at the base of a J-curve and it was clear to the smart researchers at LILP, which is how I got exposed to it. And then it became so obvious to me I couldn't understand why the market wasn't updating. And then as soon as opening this job, I was like this is, I do this for free and give them an arm in the process. But yeah, it all happened so fast and Andrew Eng is honest. He talked about it recently at a Sequoia event. No one predicted it. Like not even the people close to it predicted it really except Ilya. I mean, Ilya wrote this, the Chief Sciences at Open AI wrote this incredible paper in 2012 that sort of predicted all this, but very few people in the world cared about it or believed him. Yeah. Great. So Jake, a full disclosure, you know, you're an investor in Regal, you know, you're now taking in emergency. I mean, maybe tell us a little bit about your journey to being a VC and now into being an expert on AI. It's really fun to do this. I care about you a lot. It's cool that we're all together. I grew up in Austin before Austin was what it's become. So in the initial tech boom of Austin in the 80s and 90s, my parents are tech entrepreneurs. They started a bunch of companies together as co-founders. And I was sort of sitting shotgun for them growing up. I didn't realize that that was a job opportunity going forward. But in many ways, the role I play Alex with you in Rebecca at Regal is not wholly dissimilar to the role I play with my parents and their companies growing up. I have like more legal rights in Regal than I did with my parents' businesses. But I've done a lot of coaching founders and problem solving and trying to help out right now since I was a kid. So in some ways, I was raised to do this. I also find it really meaningful and joyful. I started my career in consulting. I'm a superstructured thinker. I love frameworks. Consulting was a very good fit for me. As a result, I see the world in two by two's. I then did a startup myself. I helped start a company that was developing solar power plants in India and Africa. Very different type of startup. It was very hard. It was very enterprise salesy in the sense that we were selling very, very large seven-figure contracts to governments that lasted 15 years. After about four years of that, I came to California for grad school and then transitioned into venture and have been doing that for almost a decade. In terms of my path into AI and AI investing in particular, I started to spend a much of time on this in 2016. My partner Gordon Ritter and I started to develop an investment thesis that we call coaching networks. The core idea behind that is a lot of the AI energy and automation energy back in 2015 to 2020 times almost around how can we use technology to help automate tasks away. That was the rise of RPA companies like Automation Anywhere and BluPrisM etc. We saw that as commoditizing over time because once the task is gone, it's gone. We were thinking more about how can we use these technology breakthroughs to help coach workers in real time and how to do the jobs better. The core idea was that the highest value tasks are human to human tasks and those are going to be the ones that are hardest to automate away over time. How can we use the same technology? It's automating some tasks away to help augment folks doing it. Our first investment with this thesis is a company called Corus in the sales space. It's sold to Zoom Info a couple of years back. Many of you are probably familiar with Corus plays a similar space as GONG that helps coach folks, sales folks, somehow to have better conversations. We then invested a company called TEXIO which does augmented writing. They coach specifically writing in the HR domain. We've invested in all sorts of companies using AI to help workers do their jobs better. If you think back to your decision to go to VC, to your point, you had a lot of fun at consulting. You were in a place that sort of emphasized the values that you care about. Why did you decide to switch to VC and what advice would you give to people as they're thinking about as VC right for me? I have a two by two day answer that question. Is it a video? Should I draw it or should I just describe it? I can also draw it real quick. There's two dimensions along which I thought about my career, which I think you can plot a lot of careers. You've got, on one dimension, the X-axis is breath and depth of content. There are some jobs where you go super deep and you have a world expert in a very specific thing and there's some jobs that are very broad in terms of the content that you're doing all sorts of things. In consulting, for example, I worked for Novartis, I worked for Shell, I worked for Campbell Soup, I worked for all sorts of companies trying to help them solve all sorts of problems. That was the definition of breath. Whereas when you're starting a company, when you're leading a company, when you're an executive in a company, you're really thinking about how to solve a very specific, your world's expert in a specific thing. There was a time, there was a moment time where I was probably the top 10 world's experts in building utility-scale solar photovoltaic power plants in Western India. That's a very specific thing and I'm definitely not that anymore, but there was a few years where I was top 10 the world expert in that very, very narrow specific topic. The polls of the breath versus depth. Any other access I think about when you plot careers is high versus low agency and high versus low risk, which are kind of correlated. There are jobs where you're taking a lot of risk and you generally have a lot of agency and you also have a lot of upside. Then similarly, there's jobs where you have little agency, little risk and little upside. Consulting is that as well, at least in the way I practice it. Consulting was kind of lower left though, like if I've got this too.
do I have crudely drawn? I don't know if you can see it. Like consulting is here because it's very broad and very low agency low risk. I didn't have really any impact in terms of I couldn't control the outcomes of what I was doing. Starting companies up here, high agency high risk, very focused, you know, depth of content. Joining a company is kind of depending upon the stage you join in. It's kind of somewhere here where like you've got you're more specifically focused on one thing and you have some agency some upside but depending upon how early you are, you may not have a ton. It depends. And then this quadrant I found to be more venture investing. I started my venture career in turning at Client & Perkins while I was in grad school and this is this resonated with me. So meeting, you're doing a fairly fairly number different, a broad number of content focused areas and you have a little more agency a little more upside way less than you do as a founder. So I realized that for me this was like most authentic. Like that quadrant felt best for me. There is no best quadrant. It's really a self-awareness question. And then if you want to get super nerdy within that quadrant, you can actually draw a nested tube by tube and plot all the different types of venture investing because there's lots of different types of venture investing you can do. And for me, what I found is that being in the top right quadrant of the venture quadrant was most authentic meeting, doing it with a fair bit of depth and doing it with a relatively high degree of agency and upside. So that means an emergence all we do is enterprise software investing. That's all we've ever done. So we are very narrowly focused just on B2B software. We don't do consumer, we don't do hardware, we don't do space tech, we don't do anything else. We just do this. And we're very focused in terms of how we invest. Each partner makes one investment per year. As Alex knows, when we backed when we backed regal, I and we more broadly, our full team went super deep. We were really hired to hire the first VP of sales. We worked really hard to hire the first VP of customer success. And that's about like having some agency and really caring because we have meaningful sake in the company's outcome. Yeah, I think it took a great way of thinking about what each of your points, which of the boxes do you want to be in and knowing yourself all enough to know which box like you're going to be happy in and then following that? So as a transition, you know, you obviously invested in us. And so, you know, now regal is a, when you invested in us, we were a smaller company. Now regal is a little bit of a larger company, taking advantage of building software for B to C sales specifically. So a much more transactional, much higher volume sales model than traditional B to B sales. And with that volume of data, it comes all kinds of fascinating things we can do from, you know, machine learning to AI to, you know, sort of lots of great stuff. So I think the meat of the conversation today was to be around AI and sales and, you know, what's going to happen. So, you know, I know Zach and I were talking before, you know, Zach is sort of a proponent of like all the things AI will be able to do. So maybe we start there like how quickly, you know, Zach, do you think that, you know, AI will come for roles in sales. Let's put it in the most extreme. How quickly will AI be selling instead of a human? And, you know, will it sort of happen in certain parts of sales? Will it be good for the customer or not? Like what do you think the second order effects are going to be as that happens? Yeah. So I'll start by saying I think that there's a, we should distinguish between what it will be capable of and what it will actually do. And what it will actually do is a function of the policy that gets passed around it. And, you know, the, the, the overt and principle sort of applies here, which is like how much do people, where do, how much does the public care about AI? And that's accelerating really quickly. And there will be a lot of regulatory capture here. So a lot of industries will just not adopt AI because we don't want, you know, in at least the United States, we may not want doctors being automated, things like that. Although I, I, again, I would take the other side of that. But sales is one of these categories where there's actually a lot of, there's a lot of reason for the consumer. And therefore, the average constituent of a politician to want their experiences to be automated, not least of which is probably that their costs will, will come way down. And the other thing that's actually going to control whether or not this, this stuff gets adopted is whether or not the companies that are driving sales, you know, actually want, or doing sales actually want to, want to take the first leap because it will be a domino effect. Industries will sort of topple us as, as the leaders adopt this. I think that it will be capable. I think that the technology will be capable of running the average sales process. So like pick a, pick a widget somewhere, you know, large in the shoebox, smaller than a car, a price, you know, less than $100,000. I think the technology will be capable of running that sales process in 18 months. I don't think that it will. I would take the, I would take the over on will it, but it certainly will be capable. And there are a lot of reasons for that. The speech technology is getting really good. The listening technology is already there. Thanks to vector databases, the contextual lookup is remarkable. And frankly, it's probably better than the average salesperson. I think the trouble that companies are going to have is, is one, again, being the first to take that leap. But more importantly, getting their consumers comfortable with it. And, you know, the idea that you're not talking to a human is going to, you know, I think it's going to follow the same trajectory that mobile did. Everyone's like, no one's going to buy a car on their phone. You know, that's, you know, that's always going to be protected. That's always, people are always going to go to a dealership. And, you know, you fast forward, mobile has taken over purchases of every size, including homes at this point, right? And so I think consumers will update quickly. And it's just a question of how fast. And without terrifying salespeople, I do think it's important that people prepare for a future, at least where they are very augmented. And probably a future where the work that they do is at the edge. Why is it good for the consumer? Well, automated salespeople never go to sleep. They don't have bad days. They don't lie to you or they shouldn't lie to you as long as the technology is aligned. And they should lower your cost structure, right? Consumers who buy from salespeople, they're paying a 10% tax just on that person, right? It's got to come from somewhere. And the deflationary power of AI is the most exciting thing to me about the future. The cost of goods is going to plummet. And therefore the price of goods should plummet too. And we will all just need to make less money to live, we shouldn't need to make less money to live the same or better standards of our life. And it just depends on, you know, where in the value stack we find that value. Let's take your position. Whether it's 18 months or five years or 10 years, there is an endpoint at which the technology will be able to as long as we allow it to do the end end job and not need a salesperson. But I'm making a bit of a straw man, which is not quite when you set it. Let's just pretend that for a second. Yep. So I think before I turn over to Jake, why do I know I was like some frameworks, two by two majorities about like certain jobs where maybe you know you'll still need oversight. I think what we see in our role in sort of B to C sales, at least, is there is value to the human in that it creates a certain amount of trust and a certain amount of empathy that results in higher conversion. And so the one argument that like I would push back on is sort of the cost argument. You know, if having a human salesperson gets you even one more, it doesn't need to get you many more sales for it to pay for itself to have a human. And even if your cost structure is high for the company, it's going to be worthwhile to have that human. So yes, for sure. If eventually the you know, technology is 100% as good as a human, yeah, then there's no difference. But as long as humans are better, especially in higher dollar items, you know, if you're selling a $50,000 right now, your salesperson tells you one more thing a year, it's always going to, you know, be a situation where you're going to want the salesperson or having nothing. And maybe, I mean, maybe, you know, it is a better experience for a customer. You know, at some point in the future, if truly you're saying Alex, assume that it becomes indistinguishable, sure, I agree with you. But until that point, I actually think there's this long, I would posit, there's this long middle period where it's going to go exist, where because the human salesperson is just a little bit better, tiny bit, it's going to always be needed, there's a way to be needed. And the technology will be sort of living flat by side with the human. I think that the best salespeople will be a little bit better for a long time. Like if you ask, if you ask Andy Sabrstein, the president of Morgan Stanley, what makes his best wealth advisors, it's an X-Factor. Like what makes the best partners at a law firm? It's an X-Factor. What makes the you know, pick a professional service, it's an X-Factor, it's hard to replicate. That's what separates, you know, that's the genius zone. Most salespeople aren't good. And that is like something that we all know, but don't talk about.
about very often. The average salesperson doesn't actually add the value that the company thinks that they add. And on the margin, most people don't actually talk to a terrific salesperson when they are purchasing a good or service. I think that we should, I will take the under on the whatever limit we're approaching when AI is much better than the average experience today. Yeah, so let's question James specifically. So like in this interim period where the AI is not as good as the best salespeople, but you know, to the point like there's huge variety in the quality salesperson. Like what happens? Like where does this get used and where does it fall down? The way I view the next few years is that this should lift all boats in terms of the quality of sales reps, right? If you have bad sales reps today, first of all, they're not going to be able to hide as well because the data we're collecting is so much better. And when you have recordings like, you know, regals releasing a call, you know, recording and coaching product that allows managers to coach their BDC sales reps and how to improve. Like this technology should help us upscale workers. And so the bad sales reps should be coached and the ones that aren't going to be coached well with this technology and conjunction with humans will be let go. And hopefully the baseline will raise in conjunction with this stuff. That's also hopefully true of the best, the best reps because in the ideal world, this technology recognizes like, Hey, when this rep used this phrase, this type in this context, the deal closed 15% more frequently. And it may be the case that rep never really realized what he or she was doing that convert that led to those improved conversions. But if we have a system that collects that data in a closed loop manner, that actually gives the insight to the best reps is like, Oh, yeah, I guess that is working. And I should do more of that. And oh, by the way, that same insight is shared with all the average reps as well. And hopefully they can start to use something as well. So I view that at least in the the medium term, this technology should raise all boats on terms of sales quality. Yeah, the metaphor I sometimes like to think about and I exactly was going to ask you, you think this is an app metaphor is is Uber. And that I can't imagine how a delivery person, you know, I know I'm sort of talking Uber in general, but how delivery person or a taxi driver 20 years ago knew what to do. Somebody jumps in the car or you get an order and says, you know, this street name in 15 minutes, like how could you possibly do that job? You know, maybe in London where it's a, you know, literally it was like a year long training program, you could figure it out. But it was impossible. And with the aid of Google maps and the Uber app or delivery app, all of a sudden it turned every driver into somebody who always got it right, always took the best route, always made sure that you were going around the traffic. But you didn't have to say anymore, oh, like don't take for that. Because I know there's something happening. Like it knew and so maybe simplistic. But I think about that in short, in the medium term to Jake's point, where could it just all of a sudden turn every salesperson into somebody that is doing this phenomenal job for the customer? Yes. And I don't think that simplistic at all. I think it's very analogous. The gap that you're missing is that Uber would love for all of their vehicles to be autonomous. And moreover, we're almost there if not for policy like driving. So let's take the driving example. So this is one that I think about a lot just from our business. Who's going to win when it goes autonomous? Is it Uber who has the distribution that they managed to get while they were using the drivers or is it the companies that went straight to driverless? I've never got any distribution in events. The best explanation I've heard on this is a former Uber exec who remained unnamed, who told me that they keep, he predicts they'll protect his identity that there will be a bifurcated platform world, much like Android and Apple, where it's probably Tesla and Tesla has a bunch of cars on the road and those cars run on a closed network. And then another, maybe Google, who knows, maybe you know, where you can plug your car into an open network and those are the winners. But I just just to go back to this. They think so to be clear, they don't think that the distribution advantage Google has is worth anything once it goes to drop. Sorry, the distribution that Uber has is worth anything. I don't know. I shouldn't speak. I'm true. Yeah. I don't forget their opinion. What's your opinion? Do you think the distribution advantage helps? I think it, I think distribution will remain king, which is also why I think AI on the whole universe, the incumbents, if you can move fast enough, but if you cannot, like, if you have too much technical debt and you can't update to the new world, like the bet, the most valuable currency in the new world is, uh, is ability to change your mind, like, like updating, updating the new information as it, because it's just going to accelerate is the thing that's going to separate people and companies in, in the new world. And that's like a combination of courage, envision and confidence and other things. But just to go back to this, your point is so good about Uber and the only reason that we are not driving around an autonomous vehicles is because of a, it is really a policy issue. And there's an infrastructure problem sort of, but cruises is taking people around town. If, if the government let us, Uber would quickly start to eliminate drivers. Here's where I think the analogy falls down. Um, I, I agree with that point, Zach, and like in, in my neighborhood in San Francisco, there are, for every, you know, three driver cars, there's a fourth non driver car. Like it is very standard here now. Um, but the difference between delivery and driving and sales is empathy. Like ultimately sales and the best sales people have insane EQ. They're like able to inspect themselves into the brains of the person they're talking to, understand what they're feeling and thinking, and then understand how to represent what they're, the product service they're selling to actually get them to buy. And that I think will remain at the highest level, like the top of the game, a very human experience for a very long period of time. It's very hard for a bot to say like, Oh, yeah, I feel you. I've been there. Bob, blah, blah. I agree, Jake. And so let's assume that the world's best black car drivers who drive up, like the important people around will remain because those people don't want to get in a robotic vehicle. But most people are like, yeah, I'd love to spend 50% less to get around. Yeah. And get and get an autonomous vehicle in the same way that most people who, the use car, the use car salesman became such a trope for a good reason. Yeah, but that's, that's your conflating metaphors here. Like it's not, it's not about selling the car. It's the service that you're providing to transportation. I agree. And all I'm saying is I think that you're giving credit to an industry that doesn't deserve all the credit. This is coming from sales leader. I know I just said, I just, this is coming from sales leader. I think that the best salespeople are, are, are, you know, operating in a genius zone. And it is a power law rule. If you ask most people who buy software, like the average person who buy software, were they impressed by their salesperson? People are going to say probably not like they're being on it. And I think that is, and, and, and software attracts some of the best sales people in the world. I'm not, I'm not trying to be inflammatory here. I just think that like, I think we're kidding ourselves. If we think that like people are not, wouldn't be interested in saving 20% on their good. And, and talking to them, moreover, I think that machines will, will learn empathy in the same way that depends on the good. It depends on the good Zach. Like in my mind, like what an Uber is providing a commodity, which is getting you from point A to point B. If you're selling something that is less commoditized and particularly has more of a service is element to it, that's like, hey, I'm selling wealth management. And that, a lot of that is like the experience you have interacting with me. Like that's, you just know the point. Well, management is a command. Like at the limit, most things commoditize. And, and the limit in this case is not that far away. Yeah. I don't know. I think, I think that, just this is a lag like one thing that surprised me in, in, it's sort of the sort of industries moving online retail came online first and retail like quickly did away with customer service, right? They hit the number. They took the number away. Like there wasn't a number. You couldn't contact the human being because they thought to your sort of general line of thinking that the more that you took away the cost, you know, it would save you money and it wouldn't hurt your conversion. And I think in some industries that sort of became true, like selling CDs online, that probably became true. And that industry disrupted itself and then went a whole different way with, you know, Spotify and other things. But when I think about industries like healthcare, you know, where you're sort of deciding between, you know, I hurt my knee not too long ago. And one doctor told me I'd never walk again. One doctor told me that I needed surgery today to walk again. And another doctor told me I was a whimp when I should walk out of the group. So, you know, you're deciding between these very complicated outcomes. And, you know, effectively, the doctors were sales people. They may not call themselves sales people, but they're onwarding me and trying to convince me to work with them. Or if I'm talking about life insurance and there's the struggle between do I leave it to my kids or my wife or my, you know, somebody else? Or if I'm talking about an industry like education, where it's a very emotional decision, do I take time away from my evenings while I'm working full time to go to school because I want to have a different career and try to move out of my current career. These things we tried to bring on lots. So, I was part of trying to bring some of these industries online. And I was shocked and I shouldn't have
and no shock when removing the human component from it entirely resulted in much more conversion rates. If that was something that's possible, you were just, you know, to fund the account. So you think, yeah, do I just, you're just early? Yes, so I do I buy it way in the future with truly A.A.I. is the same as a human? Of course, I'm not, you know, there's no, there's no act, if I can't tell them, I'm talking AI, then this is a move point, well, a violent agreement that when the A.I. is as good as a human, of course, it's the same. I think in the short term, though, this is the question, when you have these complex decisions and the AI is not as good as the human, what is the human going to want? What is the business going to want? I think to J.A.X. point, this is where I agree to them, there is something even if the salesperson is not perfect where the AI will lift the salesperson before it replaces them. Alex, do you think it's also possible that you are getting premium premium experiences when you look for a doctor or when you consider a major purchase? As I think about these industries, like I'll pick on one that's famous so that I'm not insulting anybody, like, you know, buying a car, to your point, is not necessarily a premium experience, but conversion rates are higher over the human without a human. Going and submitting, putting money in a bank account, again, not a premium experience, but the rates of funding accounts are double if not triple when you have a human being involved in without a human being. I'm not saying that I'm just arguing the technology is going to get where it needs to go. The last thing, the last point I'll make on the healthcare and just broadly, you know, of the eight, something nine-dillion people on earth, something like 70% have never seen a doctor. And I think it's really important when we talk about the power of AI, it means accessibility to things that are considered lunch or today, turning low degrees into staples. And a lot of that is going to require fully automating an experience because we're just not training enough doctors right now. Yeah, and we're a lot of people who are unbanked still in the United States. And if we can figure out an effective way to bring them into the financial system where they can start saving money, but that has to happen in an automated way, we're going to do it. Like, and it's going to show. So that's where I push you as an example. So let's, you know, I find like the value of the internet is increased distribution per shore. And the value of AI and like the kind of data that we get at regal is that we can offer millions of customers, a 100-million experience. So my wife's friend is an insurance agent. She used to sit in the physical office. She's fantastic. People would walk in. They love her. She's incredible. How do we create that same experience? Or take your medical example? Like, how do we take the experience you'd have with the best doctor in the world? But offer that's millions of people by leveraging all the things we know about how all these different doctors operate, how patients react, how to deliver good news and bad. And so, yes, it's possible that there's going to be more technology, of course. But, you know, we serve, for instance, the diabetes care company where, you know, it's your point. They don't have many nurses, but they use our software to identify the moments in which technology can do stuff. And the moments in which a human needs to get on the phone and say, there's something going on. You need to talk to me right now. Instead of seeing a doctor for four minutes a year, you know, at one point, in that one, you know, wrong point, they're going to make sure that you have a 30-second conversation at the right moment when they're going to see if your foot from being cut off because they identify something that's going on. And I agree that the line is probably asymptotic, that there is always going to be work that is done where a human will be in the loop, always, for some amount of work. All I'm arguing is that the curve to that line is a big more accelerated than you, than you and Jake think. So, Jake, I guess you've talked about sort of some ways of thinking about this particularly in like how critical the function is. And I think your criticism of the technology is that it might hallucinate, not intentionally lied, not unintentionally lied. So like, do you think, Jake, that's that sort of your opinion changes over time, if that goes away, if the technology was not going to hallucinate? Yeah, there's two dimensions thing about this. So the first is accuracy, which is related to hallucination. So like, how bad is like, how often is this thing wrong or lying, the thing being AI? And if they are wrong or lying, how severe is that consequence? So like, accuracy as well as just like outcomes. Like that's one dimension. And the reality is like, that's going to get better over time. Technology will improve, we'll find better ways to fix that. I think we have a long way to go on that. So like, there's a lot of pay to be made if that's the right analogy over the medium term until that gets fixed. But I think until it gets fixed, like people really, like human in the loop is a very, is a much safer way because you can nudge the human and if the AI is wrong, the human can override it. So I do think that's going to be a really important thing for the next era of software. I think that's a whole era of human in the loop software that's going to exist because of hallucinations in a business context. It matters less than consumer context because like if you're chatting with a dead celebrity, there's no such thing as right or wrong. But to me, even in a world where we get to a place where like this thing is fully reliable, I still believe that in really high value human to human transactions, a human being involved matters. Like, you're not going to close, you know, a really important, really emotional transaction without a human being involved. And I don't think a car is a good analogy because I don't think that's an emotional transaction in the same sense. I, by the way, I think you're mentioning. I don't think we disagree here. I just think that that market is like one moment is fine. So let's go back to the point you're making was that before our distribution. So Jake, I know you've talked about this sort of idea that perhaps the companies that have a sort of a UI already that they're sort of building software for a job to be done already, that have this feature ready, may have the greatest advantage now this new technology in the may be this may be a boon for incumbents. You know, how do you think about like who's going to take the best advantage of this technology? Yeah, so I'm thinking a lot about this right now because to out to Zach's point, in many ways, incumbents are best positioned here. This is different than the the moves from on-prem to cloud when incumbents were in trouble because it was impossible, basically impossible to rewrite your entire stack to be cloud first. This is as easy as plugging in API. And effectively, like most public companies are not playing with this and doing like cool stuff with it. So the question is for startups, like what is the what is the opportunity for all this is the incumbent? And I think there are potentially a few. There are opportunities where what was the job to be done that couldn't have been done before with technology had to be a service before. And there's a lot of examples of that. There's a bunch of interesting stuff happening in legal tech, which is primarily a service before, but it's now being able to be productized more. There's all sorts of stuff happening in the medical space as well on up front. So like, and those are places where incumbents may have an advantage, but in many places, they were services companies not software companies and software companies. A startup may have a role. I think secondarily, there's a bunch of industries that are going to be created by this. Certainly all the tooling infrastructure tooling to support this is new. There's also going to be a bunch of companies around compliance and you know, trying to implement this stuff in a safe way that don't exist yet, they're going to have to be built. So that's another opportunity for startups. And then lastly, I've been thinking and we have been thinking a lot about where is there likely to be an innovator's dilemma issue for the incumbent or where is there likely to be a counter positioning opportunity for the startup. And so examples of that may include, you mentioned before user interface changes, the chat-based interface is sort of a new concept in V2B software. And I think it's unlikely that chat-based interface on its own is going to be the dominant interface going forward, but I think they're going to be elements of chat-based interfaces that become core to many V2B software experiences. And I think that many incumbents may have a challenge of cannibalization of their core business if they try to make that move. So as an example, let's imagine a world where the ideal CRM going forward we realize should be built with a chat-based interface. And I don't know if that's true or false and Alex, you're going to know more than I do because you're building a CRM product. But let's imagine that that's going to be core to that product going forward. If your Salesforce, it's not that you don't have the resources to rewrite your software to do that. It's that you have millions of daily active users who pay you billions of dollars who are used to a certain interface. And so completely changing that risks fundamentally disrupting your core thing, which is unlikely to happen because there's just too much in competency there. So I think there's some stuff like that. I think there can be some pricing changes that happen in software. Companies that got used to charging on a per-seat basis may be more vulnerable in a world where a new startup can say, "Hey, I'm going to charge based on outcomes." Like Alex, one of the things that Regal did that was most impressive to us as we were doing the diligence on the investment is how closely you tie the interventions that you guys have to outcomes for your customers. How much increased revenue you guys were able to show. And in many cases, and this is like a super cool thing that I talk about a lot and maybe I don't know if you'll mind if I share it out. It's publicly. You'll often actually hold back reps with customers. So you'll say like, "Okay, the customer 95% of the customers reps can use our products, but 5% can't. Just to demonstrate the increased ROI that we're driving. What is the real impact? You can imagine a world where as you add more and more AI and that impact becomes even greater, that you start to shift to a model where it's like, "Hey, we're going to charge on a per-seat basis, but we're going to charge on the incremental dollars we lift for you." Which was really hard to do in a world before because it was hard to establish causality. And most software vendors didn't have that much quantifiable impact that they could prove. I think that's starting to shift. I think Regal started with the forefront of that. And I think that if you're an incumbent who's used to charging in a certain way and frankly used to obscuring the value created behind some sort of per-seat or per usage metric, you may be vulnerable. So thank you, Jake. So I think a lot
a lot sort of thing about today. I know Zach you got to run so we're going to stop there for today, but I appreciate you guys apining on how quickly we're going to get to AI replacing sales. And in the meantime, sort of what businesses can do to take advantage of AI in this interesting industry. So thanks Alex. Good to see you Jake. See you soon. Hi guys. Cheers.
Podcast Summary
Key Points:
Zach’s journey began in AI at Crowdflower in 2009, later moving to Lilt and then becoming OpenAI’s first sales leader; he now plans to consult and run for mayor of Santa Barbara in 202
Jake’s path to VC started with consulting and a solar startup; he co-developed the “coaching networks” thesis at Emergence, focusing on AI that augments human workers, especially in sales.
Jake frames career choices using a 2x2 matrix
Zach predicts AI will be capable of running an average sales process (e.g., products under $100k) within 18 months, but actual adoption depends on policy, consumer comfort, and industry leadership.
Zach argues AI benefits consumers through lower costs, 24/7 availability, and consistency, drawing parallels to mobile adoption; he believes most salespeople underperform, so AI will quickly surpass the average experience.
Alex counters that human salespeople add trust and empathy, and even a small conversion lift justifies their cost, especially for high-ticket items, suggesting a long coexistence period.
Zach acknowledges the best salespeople have an “X-factor” that’s hard to replicate, but emphasizes that the average salesperson doesn’t add expected value, making AI a strong alternative.
Jake frames the interim period as AI lifting all boats by improving poor sales reps’ quality, rather than replacing top performers immediately.
Summary:
The conversation, led by Alex Levin (CEO of Regal.io) with Zach (formerly OpenAI) and Jake (GP at Emergence), explores AI’s impact on sales. Zach recounts his early AI career, from Crowdflower’s data labeling to Lilt’s translation models and OpenAI’s first sales role, noting that the field’s rapid growth surprised even insiders, though Ilya Sutskever’s 2012 paper predicted it. Jake shares his path from consulting and a solar startup to venture capital, where he developed the “coaching networks” thesis—using AI to augment workers in human-centric tasks like sales—and highlights his career framework of breadth vs. depth and agency vs. risk, which led him to Emergence’s enterprise software focus.
On AI’s role in sales, Zach predicts the technology will handle routine sales processes within 18 months, driven by advances in speech, listening, and contextual data. He argues that consumer benefits—lower costs, no downtime, and consistency—will drive adoption, despite policy and trust hurdles, drawing parallels to mobile commerce. Alex pushes back, emphasizing that human empathy and trust still boost conversion, especially for high-value purchases, so humans will remain valuable as long as they’re slightly better. Zach counters that most salespeople underperform, so AI will likely surpass the average experience quickly, though top performers retain an “X-factor.” Jake suggests the interim period will see AI elevating poor reps’ performance, benefiting companies broadly, rather than immediately replacing the best. The discussion concludes that AI’s integration will be incremental, with humans and AI coexisting for some time.
FAQs
The speakers are Alex Levin, CEO of Regal.io; Zach, formerly from OpenAI; and Jake, a GP at Emergence. They discuss AI's impact on sales.
Zach began in 2009 at Crowdflower, a data labeling company, then worked at Lilt, which built large language models for translation, before joining OpenAI as their first sales leader.
Jake grew up with tech entrepreneur parents, worked in consulting, started a solar power company, then transitioned to venture capital after grad school, focusing on enterprise software and AI coaching networks.
Jake uses a 2x2 matrix with breadth versus depth of content on one axis and agency/risk versus low agency/risk on the other. He found venture investing in the high-agency, broad-content quadrant most authentic for him.
Zach believes AI will be capable of running an average sales process for products under $100,000 within 18 months, though actual adoption may take longer due to policy and consumer comfort.
AI salespeople never sleep, don't have bad days, shouldn't lie, and lower cost structures, which could lead to deflationary effects and cheaper goods.
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