In short
Podcast Notes: Grit - Building High-Impact Sales Teams with Dan Lee and Nooks
Episode Overview
- Title: Building High-Impact Sales Teams
- Guests:
- Dan Lee - CEO and Co-founder of Nooks
- Leigh Marie Braswell - Partner at Kleiner Perkins
- Host: Joubin Mirzadegan, Partner at Kleiner Perkins
- Key Theme: The importance of human connection in sales despite the growing role of AI in automating routine tasks.
Key Concepts and Discussions
The Role of AI in Sales
- Automation of Busywork: Nooks automates time-consuming tasks like research and dialing, allowing sales reps to focus on meaningful interactions with prospects.
- Human Connection: Despite advancements in AI, the effectiveness of sales still relies heavily on personal connections and conversations.
- Increased Productivity: Sales reps can triple their daily call capacity with AI assistance, from 50 to 150 calls per day.
Dan Lee's Approach to Growth and Management
- Do More with Less: Emphasis on prioritization while maintaining a high execution pace without overextending resources.
- Ruthless Prioritization: As a startup, it's crucial to identify key areas for investment and focus to prevent burnout among team members.
- Relentless Curiosity: Dan's pursuit of understanding processes deeply, often through the "five whys" framework, reflects a commitment to excellence and customer needs.
Company Culture and Dynamics
- Team Collaboration: Dan's partnership with co-founders Rohan and Nikhil, emphasizing the importance of friendship and shared learning experiences to foster a positive work environment.
- Feedback Loops: Direct communication with sales teams using Nooks enhances product development and allows for rapid iteration based on real user experiences.
- Empathy Through Experience: Founders' initial engagement in sales processes helps them understand customer pain points and refine product offerings.
Vision for the Future
- Redefining Sales Tech: Transitioning from traditional sales tech tools towards AI-driven solutions that reshape how sales jobs are executed.
- Innovative Entry Points: Starting from automating the mechanics of sales to eventually owning the human interactions, facilitating more effective sales conversations.
- Customer-Centric Growth: The mission is not only to enhance sales productivity but to develop a deeper understanding of customer needs and behaviors through data.
Challenges and Future Directions
- Navigating Competition: The podcast discusses the competitive landscape in sales tech and the need for differentiation in a crowded market.
- Recruitment and Team Expansion: Hiring across various departments as the company scales, emphasizing the importance of finding individuals aligned with the mission of customer impact.
Key Takeaways
- Human Element: Sales remain fundamentally about human connections, even in an increasingly automated environment.
- Impact Over Work: Success in building a company is tied to delivering tangible customer impact rather than viewing tasks as mere jobs.
- Iterative Learning: Continuous learning from customer interactions and product feedback is crucial for growth and innovation.
Conclusion The episode encapsulates the journey of Dan Lee and Nooks as they navigate the complexities of building a sales tech company that prioritizes human connections while leveraging AI to enhance productivity. The discourse offers insights into management philosophy, company culture, and the forward-looking vision necessary for scaling success in a competitive landscape.
For more insights and episodes, connect with the podcast hosts and guests via their social media links:
- Dan Lee: [Twitter](https://x.com/_dan_lee_), [LinkedIn](https://www.linkedin.com/in/dan9lee/)
- Leigh Marie Braswell: [Twitter](https://x.com/LM_Braswell), [LinkedIn](https://www.linkedin.com/in/leigh-marie-braswell/)
- Joubin Mirzadegan: [Twitter](https://x.com/Joubinmir), [LinkedIn](https://www.linkedin.com/in/joubin-mirzadegan-66186854/)
Written by AI. May contain mistakes. Listen to the episode to check what was said.
Transcript
Automatic transcript. May contain errors.0:00AI is not going to take your job. someone using AI will. People use Nooks right now three hours a day. You watch The Wolf of Wall Street. You know the scene where Leonardo DiCaprio is making calls on the sales floor selling penny stocks and then everyone kind of gathers around and listens. The sales teams are using similar features to be able to make calls together. In sales that little tip above the surface on how reps spend time is talking to prospects. But all the stuff beneath is you need to find their phone number, you need to go look at their LinkedIn, update the CRM. And AI can do most of this job.
0:27You used to be able to make 50 calls in a day, and now you can make 150. Naturally, we tend to move really fast and have a ton of ideas and trying to be executing in a lot of different directions. And part of that is like ruthless prioritization, too. As a small startup, you can do anything, but not everything. And you need to actually pick your bets. Otherwise, yeah, everyone just burns out.
0:58Welcome to Grit. I'm Jubin, partner at Kleiner Perkins, a show where we go beyond the highlight reel and explore the personal and professional challenges of building history-making companies. Today on the show, we have Dan Lee, co-founder and CEO of Nooks, the AI-powered sales platform that started by helping reps book more meetings and today has ambitions to do much more. Joining us today is my partner, Lee Marie, who gives some extra color on why we decided to invest in Nooks, what it's like working with this company and what we think about the future of this space. Enjoy the episode. I thought an interesting place to maybe start was when I first met you, it was pre-us investing, maybe right around investing.
1:47Have we invested yet? No, I think - It was on the phone, right? It was on Zoom and it was before you guys invested. Okay. And I remember I was on Amin, who you know, my cousin. I was in Montana for his bachelor party and you and I were on the phone. And it was like supposed to be a pretty quick call, like get to know each other. And the next thing I know, it's like full on, like we're like built, like he's like asking very detailed questions about sales leaders and go to market and company. And we're talking about what other people could potentially be involved in the round. Next thing I know, it's like an hour and a half.
2:29And I'm like, oh my God. And he's like, by the way, like I have more, like, I have more, like, can we keep talking? I'm like, we should, like, I think we're going to keep talking for like the next 10 years or something. But like, I realized right then and there that Dan is insatiable. Like he will, he has this, I can't be the only person that tells you this, this like understated relentlessness. It's like cloaked in a very soft demeanor that underneath is just relentless. this people tell you this right yeah yeah my um my elementary school teachers my uh uh my team they tell you this yeah yeah yeah one of our values is ask why and you keep you keep digging in you want to understand exactly how things work from you know kind of from the ground um and you know it means you're approaching some first principles right so that that that means you need to understand and dig in really deep.
3:36I'm curious. Do you like, do people after five whys give up? Like, are they like, all right, all right. Okay. This is enough. Well, the, the elementary school teacher that, you know, she called me the thorn in her side. Actually. Yeah. Yeah. What did you do in elementary school? I just, I just wanted to understand like, you know, when, uh, this was, I don't know, like an English class and like, Like there's some analysis, but I'm like, sure. Like why? Like we want to understand really deeply. And I think she wasn't prepared for that. Did you guys know each other? Like from MIT? So you went to Stanford.
4:16I went to Stanford. Right, right, right. So you met here? We met at scale. Met at scale. Yeah. So he was doing ML at scale. Right, right, right. Yeah. Did you have that observation at any point? Oh, for sure. And it's like very, it was very clear, like quite early on. I mean, you know, extremely talented ML engineer. And there's like some really thorny machine learning problems to solve at scale at that time, because we were just really getting the pre-labeling system set up, which is basically our way of using ML to dramatically reduce the amount of work that like a labeler has to do on the task, was just kind of the whole thesis, right?
4:53That you're able to slowly create like a human plus ML system on our end. And yeah, I mean, Dan was clearly just relentless in his sort of, you know, ML development capabilities, but then also separately, way more than any other ML person that I interacted with, had this sort of deep urge to really solve problems and a deep care about the customer. Like he was just more than anybody else that I worked with or almost anybody else that I worked with just asking questions about like, you know, where this is actually going to be used and the other things that we should be considering and wanting to talk to the customer and things like that.
5:27And that same sort of like drive and sort of relentlessness definitely, you know, is one of the reasons why I wanted to get involved in Nooks because that applied, you know, combining like, you know, being one of the very few people who can kind of really understand what the technology can do, plus being one of the people that's just obsessed with solving customer problems. I think if you point that in the right direction, it's really powerful. There's like this, not to linger on this point too long, but like Ali Godzi, the Databricks CEO, has something similar. And I like explored this concept with him of like deposits and withdrawals, meaning like he's very good.
6:06Like he's relentless, like he's relentless. And he's very good at taking withdrawals from the organization through like curiosity. Like it is not in his mind, he doesn't think of it as a withdrawal. But like every time you ask a question across the org over and over again, five layers deep, eventually you're just like taxing the system. Yeah. Right. And it like creates the output of that is like really good. It's like a good byproduct of rigorousness and all that. But like it does tax the system. Yeah. And he was like, yeah, you know, I've been told like I should probably put more deposits back into the system because his natural state is just withdrawals.
6:50Yeah. It's like the company is an organism. Right. And you need to know when, you know, sometimes stress is good and you want to push it and it's going to grow as a result. And you're going to explore new ideas and people are going to get better and, you know, the organism gets stronger. But then you also need to know when to support. Right. And, hey, we're doing all the right things. Let's just kind of keep forward on this path. And that's maybe more like a deposit. Do you feel like you have a good instinct on that? Like naturally? Naturally, I may be similar to Ali in that sense on I think I push I push hard.
7:23And I think one thing that I am actually personally working on is the supporting the deposit, I think, is a good way to put it. Or what? Like everyone's just going to fry out, basically. Yeah, I think like, for example, like, naturally, we tend to move really fast and have a ton of ideas and trying to be executing and, you know, in a lot of different directions. I think one other, you know, core value that we have is do more with less. And part of that is like ruthless prioritization, too. You need to combine them, right? Where, you know, you should generate all the ideas, but then you should pick which ones are actually going to make the impact.
7:57And as a small startup, you can do anything, but not everything. And you need to actually pick your bets. Otherwise, yeah, everyone just burns out. Yeah. And like, I don't know, you're pretty young. Like you've never, this is, like how long were you at scale? I was at scale for a couple months. A couple months. Yeah. And then before that? Was studying at Stanford. Okay. So like first real job. Yeah. First real job. Nooks is, in the next couple of months, going to be the biggest company I've worked at. Explain that. I've interned at companies that were all under 150 people. Okay. And so you're going to cross the 150 mark.
8:39There's some fancy name for it where you stop knowing the names of everybody. What's the Dunbar's number? Yeah, it's like 130 or something when you stop knowing everybody's names. Yeah, we crossed the 130s. Yeah, so you're like about that point where people start showing up in the org and you like don't know exactly who they are? I know who people are, but I think it will become harder. Are you going to like try and define them? Yeah, Dan's definitely going to know who they are. Way into the hundreds. Yeah, I will try, yes. Yeah, and so like maybe going back to like this instincts point, right?
9:13Of like you've like, forget about managing people. Like this is like all the first time, the first time for all of these things. Where do you like how do instincts get developed in an environment like that? You're right. Many things are happening for the first time. I think there are some positives and there are definitely some drawbacks. For example, like probably if I were to have done things again, I would make fewer mistakes. But I think on some of the some of the advantages that we get from from doing everything from the first time, it's similar to like this ask why principle. It's like understanding things from first principles.
9:51We're building in a space that is completely new. Sales tech in general has been around a while, but the opportunity now is completely new where sales tech companies of the past have competed by taking budget from each other. And today it's actually this new opportunity where instead of software being like a tool that people use, AI can now help you do the work. And I think this actually means reimagining not only like kind of the assumptions that are backing like the bets that we're taking, but how you build the org, the people that you hire. And I think, again, there are some definitely some drawbacks, but I think a lot of advantages in doing it for the first time and, you know, building our own company, not someone else's.
10:43you just brought on a new CRO. And when she and I were talking about her experience going through the interview process with you, and she's like seen this story before and built companies through like from zero to a hundred million. And I was like, so how was it with Dan? Like, what did you, what did you think? And her first response, I don't think she'll remind me sharing this is he knows way more than I would expect about a lot of non-engineering things. Like he speaks incredibly, credibly to like sales stuff, which like founders that have been doing it for a very long time don't do. So anyway, kudos to you.
11:28I don't know how you figured this stuff out, but it's probably by asking a million whys. By asking a million whys, by doing it ourselves. You know, in the early days of Nooks, Rohan, Nikhil, and I, we picked up the phone and started calling people saying, hey, please use our product. So I think asking a lot of why is building like the customer empathy, doing it ourselves, right? We're building, you know, we're building a sales team, selling to other sales teams. So it's important. We're the best at it. Yeah. Can I tell you? So I'll give you a relentless story about Dan. So I was at their new office.
12:03New office. Have we moved in yet? Not yet. Soon. Beautiful. Touchy subject for the team. Okay. Very soon. And I like, I don't know, do the normal, like, just give a talk about whatever. And then Dan and Hannah, the new sales leader, are like, all right, like, we're thinking of getting a small group of us together and just like reviewing stuff with Jubin. And immediately I knew because of Dan, like what that meant. which I said, what did I say? I said, for those of you that aren't invited to this session, don't worry. I don't think you're missing out on anything. This is the part where Dale takes his entire pipeline and then interrogates me about who I know within any of these existing accounts.
12:50That was a good read. Yeah, it was a pretty cool. When the company is like, now it's a series B, like real revenue, like you're doing, like you're solving real customer problems for a lot of people. You have a team of call it 150 or so and growing. Like, do you feel like you have something to lose? Meaning like it's not really house money anymore. Like you got this big office, you got this huge lease, you have all these people working for you. They have like families, they're making bets on you with regards to their family. I don't know, does that even cross your mind or not really? Oh, 100%. I think on one hand, we're very far from our goals.
13:37We're very far from the outcomes that we expect to achieve. But at the same time, of course, I have 150 people who work at Nooks who believe in the mission. And it's really important that we can't let anyone down. We have even thousands of customers that depend on Nooks. They make more money when Nooks works better. And earn customer love, again, another one of our values. This is our most important value where if what we have to lose, there's the team, and most importantly, there's the customer. And I think the opportunity cost of not executing on our goals would be letting them down. Yeah. Leigh-Marie, how do you manage a personality like that?
14:28We could be sitting here in five years, hopefully we are, and you're at like 500 million of ARR. And we'd be having the same conversation. You'd be like, Juman, we're not even near our goals. I suspect that will go forever. How do you, I don't know, how do you think about that? So, I mean, I think one thing that's really important to underscore when it comes to KP and the partnership with Nux, KP, we are, I think, over 52 years old. And in the whole history of KP, we have not invested in a sales tech company until Nux. And, you know, why is that the case? as well as kind of Dan was saying earlier, you know, historically, it's been all about tool use, like the tools, the really crowded stack that salespeople use in all the parts of the different job to become more efficient and to make better decisions.
15:14And Nooks is just from the start and from the first pitch with Dan for the Series B, that's not the way that he framed it. He's framing it as, no, we have an opportunity to totally rethink sales in the future and all of the work that AI can do to make SDRs, AEs way more efficient. which has historically not been an area that sales tools have been able to really do. And so I think that sort of ambition, viewing this as like a new market with fresh eyes, with, you know, we are ML experts, we are technology experts. You know, no, we have not done a ton of sales in the past ourselves. We work with some amazing salespeople and we partner with them to build the best product.
15:52It's also, I think that's a very ambitious vision, because especially when you're going into sales tech, you know, the first thing any investor is going to tell you if they're not really listening is like, hey, this is a red ocean. There's so, so many companies that have tried this before and failed. And then, you know, what Dan and the team and Nooks is doing is saying, we see all of that, but like fundamentally the ML technology of today is going to totally reshape the seller job. And so we're going to go and like build new products. So it's tough for me to really push somebody when they're already that ambitious.
16:21They're like viewing this red ocean as like this new category with this new wave. But, you know, I do like think, you know, VCs can bring a perspective of like, okay, well, here's my vantage point. And that's, you know, seeing the mistakes of the companies in the past and what other companies have done well. And so just like trying to not reinvent the wheel and learn lessons from, you know, being around our fund being around for 52 years. Yeah, I think that's fair. I wonder like double clicking on the go to market space. It seems to me that all of the founders of the previous big go to market companies, let's take like we could start with like Salesforce and maybe Siebel.
17:02And then you kind of like move it forward to the gongs and many of these like big go-to-market companies. Most of them are started by folks that are more like sales oriented, like that have been in the customer side of the shoes. Whereas Dan is like, not that, right? Like it's like the, it's just a hardcore engineer. Like to the point where when I talk to him about like, what are you excited about right now? Almost always. The answer is we just did a hackathon at XYZ location with our engineering. Yeah. Like that's where like the juices get flowing and it's like product and engineering. I don't know, maybe like open question for either of you, but just like that is a stark contrast from the types of companies that would get built in this space in the past.
17:51I guess we'll see, like jury will tell like how that profile plays out here, but like, it's certainly different than what we're used to. I think a lot of sales tech companies of the past, you know, were built by a salesperson. And when you, when it's built like that, you know, you go out solving a problem that you've experienced yourself, uh, the ones that are successful, you know, you build something that can solve that problem. And then you focus on selling a lot of it. Um, and I think that has resulted, uh, in, in part in a fragmented stack, um, because you're, you go out solving a specific problem that you encountered in the past.
18:26while, you know, today AI, I think kind of flips it upside down where solving problems of the past is just a very different paradigm because the job is going to change in the future. And I think, you know, what we're talking about, like the ask why, like the first principles thinking because we know the job is going to change. How do we build instead of, you know, solving problems of the past for the job of the future? Yeah. It's the thing that I loved when I of first started talking to you, Dan, was that it had the same feeling of Glean, which I describe as the grandma test. You can explain what the product does in 10 words or less to your grandma, and they just kind of get it.
19:09And the initial use case that's really spreading right now is enabling folks to make dials more effectively and do cold calling. And that's like a, that's like, there's been movies made about that stuff for like a hundred years, you know? But I'm curious, like the vision is so much broader. And like when you and I were having lunch the other week, the question that you posed to me was like, Hey, if Nooks was on a billboard, how do you communicate what we do today and what we do like five years from now, where it's not pie in the sky five years from now, because it's going to sound like every other billboard that you would see on around like all these fake AI sales companies.
19:58Right. But if we only focus on what we do today, that's not like really capturing our ambition as a company. I don't know. I had no idea how to, I was like, that's a, that's a tough question. It is a tough question. I think because you need to be specific on like, you know, you need to pass the grandma test and solve a very clear problem. I think the space is really noisy, right? You drive down the 101, there's this and that. I think the ways that we try to stand out from the noise today will look different from the ways that we stand out from the noise kind of going forward. Today, this calling use case, the reason why we're able to grow quickly is because we can show multiples in productivity in a week-long or two-week-long proofing concept where you used to be able to make, you know, 50 calls in a day, and now you can make 150.
20:58And I think, you know, it's a very, like, it starts with, like, the really mechanical, okay, you should skip ringing and you should skip answering machines because you don't need people to do that. And, you know, once we built that, then it's like, oh, okay, we should start finding phone numbers And we should take notes on the call and we should help prepare you for call and coach and train and build the list of who to call. And I think like kind of what what's represented there is if you own the human part of the job, which is the call, then everything else kind of follows naturally. Like an analogy I give, you've seen you've seen in like the pictures of icebergs where there's like this little tip above the surface and then, you know, this big mess underneath.
21:40And I think in sales, that little tip above the surface on how reps spend time is talking to prospects and customer-facing interactions. But all the stuff beneath is you need to find their phone number, you need to go look at their LinkedIn, update the CRM, go make a bunch of calls, write the emails. And AI can do most of this job. And I think calling is actually the key part that requires a human. It's why it's actually right now the most effective channel in Outbound. And starting with that, I think, gives us this wedge where people use Nooks right now three hours a day. And that's only going to increase because AI is going to write their emails.
22:22AI is going to do their research. And they're going to spend more and more of their time actually talking to prospects on the phone. Then how do you answer the question of what are we and who do we want to be when we grow up? And then how do we speak that to the world? And by the way, this is like all being figured out now. But like, what's your real time? Like, if you answer that today, how do you think about that? And it's confined by like a billboard. Like, that's the challenge, right? Like, it's not like go to a website and you have a bunch of surface area that you can that you can use. Yeah.
22:51It's like you have five seconds to capture someone's attention. Yeah. One one idea we're playing with is AI is not going to take your job. Someone using AI will. Um, and I think it is actually nuanced, um, because sales, I think is actually very different from a lot of other applications of AI. Um, if you think about AI for self-driving cars, for customer support, um, you know, sales is maybe more like recruiting. Um, and, uh, I'll explain, um, in, in support, you have a customer trying to answer a question, uh, or in self-driving car, you have a passenger trying to go somewhere. And actually the ideal outcome is probably end-to-end automation, where you can answer a customer's question faster or deliver a passenger to their destination.
23:36And sales buyers are not normally trying to buy something. And they can only buy one thing for a given use case. So if AI lets you scale something to infinity and do it end-to-end, then the result is you end up spamming a buyer. So I guess we view sales, it's more of a grow the pie type of use case, where when AI lets you do more with less, it's like a parameterization question. do you do the same by cutting? Or do you actually do a lot more by investing the same or even investing more? So as a result, sales has both kind of this art and the science component. The art is what's the tip of the iceberg, right?
24:14That's the customer-facing interaction. That's where you're leveraging EQ and building relationships. And the science is more kind of what happens beneath and the mechanics of it. So with Nox, we're trying to automate the science so that humans, the sales rep, can focus on the art. In the iceberg analogy where AI can do whatever, 95 % of the stuff, I guess like in your day-to-day with you and the engineering team, can AI do 95 % of the stuff? Like today, like, is that like, hey, assuming X rate of progress, we believe that by the time we get to this point, the AI will be able to do it? Or are you like, no, no, no, like today it can do 95 % of the stuff that a salesperson would otherwise do?
24:56Yeah, I think the stuff beneath the surface, AI is already smart enough to do most of that. You actually don't need much progress. There are five to six million sales reps in the US outside of retail. And if you think about the jobs that they do today, they spend time closing deals and they spend time sourcing deals. Closing, this is the human part of the job, right? This is where you're taking someone to a steak dinner, you're meeting a bunch of different stakeholders on Zoom, and AI is not going to 10x your productivity there, right? Because you're limited by the time in your day. But on the sourcing side, that's where, you know, you're writing emails, you're making calls, you're doing research, building lists, and AI can do most of those jobs today.
25:46and you know you you use chat gbt claude gemini it's smart enough to write every sales email clearly right and i think the challenge um in part comes like it it's it's actually a product challenge um one of one of the biggest pieces is um because there's a fragmented stack today it requires human glue to be shared context across it um so for example when you're writing an email it means a seller needs to know what happened in the call. They need to understand, you know, pull the notes from the CRM to understand the full context in order to write that email. But now that AI is capable of writing emails, it's a really big bottleneck for a person to need to remember all that context.
26:27So, like, this is an example where ChatGPT is smart enough if given the context. But there's this product challenge in kind of pulling in the right data and context and making sure that the outputs are kind of human acceptable. And I think it informs how you build a team, how you hire, and also the types of problems and kind of sequencing that you start with. Do you think, maybe a question for both of you, Dan, I'll start with you and then Blue Marie. Like there's a very trendy thing happening in Silicon Valley right now where everybody's basically saying like, Like, oh, you can build a billion dollar company with like 10 employees or whatever.
27:12Like that's going to happen. Right. That's like that is like if you listen to Dario at Anthropic and like like there's a lot of people that are saying that right now. I have a school of thought, but I like Parker Conrad's the most, which is like everybody says that. And then your competitor goes and raises a huge round and then hires like 50 salespeople and like 30 more engineers. And all of a sudden, like, guess what? You're going to go do that. You know, I'm curious, like, is that, I don't know. What's your reactions? I totally agree. Yeah, it's been interesting. I mean, you know, as an investor, just kind of in AI broadly, it has been shocking how quickly consumers have like taken a hold of just using chat GPT for search, You know, really sort of gen AI becoming this integral part of a lot of consumers' lives.
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28:07But then on the flip side, another thing that has surprised me a ton is just how slow the intake of AI is into the enterprise or into larger organizations. Because as Dan was saying, like there are all these, even if the models are very intelligent and they continue to get more intelligent, there are all these product challenges to actually sort of close the loop in making very reliable agents. And so it's one of these things where, yes, eventually you'll probably see some team sizes potentially go down or roles changing in a certain way. But at least in the short term, you're absolutely right.
28:40And there's this urgency right now because there is this moment in time when these huge companies are going to get built. And, yeah, you're going to see your competitors hire more people, especially in a human-dominant field like sales, a relationship-dominant field, especially when you're dealing with enterprises. And so, yeah, it's a little, it's definitely, you know, encouraging to see teams seed strapping and they raise some funding and they're able to sort of surpass people's wildest expectations in terms of how far they can get. But I think ultimately these markets are so competitive or going to be so competitive that you have to, yeah, still take some lessons from building SaaS companies.
29:15Yeah, I think there's this also interesting question of value creation and value capture. I think you're able to create a lot, or a smaller team today is able to create a lot more value than a smaller team in the past because they're enabled by AI and a lot more efficient. But I think that the question of value creation today is very different from in the past because of AI, where most of these companies that are very small are AI companies and able to add orders of magnitude more value that way than traditional software companies. um then then I think the value capture question is can they meaningfully differentiate from the nearest competitor uh because if you know if these companies are not able to meaningfully differentiate from the nearest competitor then they're not going to be able to capture that value and they're not going to be able to be a big you know a big company in the long term um so that's where you got into okay you need you need a competitive advantage um you need in you know you need to invest in in the team uh and to your point right then that's when you see okay, like our competitor just raised a lot of money and hired a lot of people.
30:22Probably you should be doing that too, if you're going to stay competitive and capture the value. Another thing I'll say is I would be thrilled if any competitor of ours at Nooks or any competitor of any of my portfolio companies replaced any of their SDRs with the AI SDRs on the billboards. I would be thrilled because in practice, it is just, yeah, it is totally, you know, maybe in very small certain use cases, you can sort of automate some amount of SDR work today, but certainly not, you know, it is nowhere near sort of the power of a AI charged human SDR. And so, yeah, I think all of that is a bit, you know, marketing fake news.
31:00Yeah. Yeah, that's fair. Dan, when you were leaving scale, did you know that, like, did you know that you were going to start Nooks? No. And you dropped out of Stanford? Yes, gradually. I can share kind of the story there. Gradually dropped out. Do your parents think you graduated? Yeah, exactly. No, I can share the context there. So at Stanford, studied AI, computer science. I met my co-founders early freshman year. I think Stanford was, I think, a really interesting time for me. In high school, I was really into science, lots of science experiments, science research. Actually, I took AP computer science in high school and really disliked it.
32:00I came into Stanford and actually met folks like Rohan and Nikhil, my co-founders, a bunch of other really impressive friends who were top 10 in the country at something or another. And I got major imposter syndrome early on at Stanford. Rohan and Nikhil had been building apps and computers since they were in middle school and others were winning the random science Olympiads. Another thing that I had seen is everyone was studying computer science. All my smartest friends were studying computer science. And I was like, oh, I think I'm missing out. They were talking about all these AI concepts. Rohan and Nikhil, they got first prize at the final projects in the computer vision, machine learning classes at Stanford.
32:53It was mostly PhD students. And so I see all this going around and I'm like, shoot, I think I'm missing out. So I ended up speed running the computer science courses. I tried the first one, really liked it. So I kept doing it. Define speed running. I don't know. Taking like four or five classes. I finished. So for context, I stayed at Stanford for about two years and I finished the computer science degree for the most part in that time. Without having taken really any computer science courses up to that point. Yep. Okay. Um, and, um, did it come easy to my mindset changed in at Stanford? Like I was surrounded by just much smarter people than myself.
33:39Um, and which you weren't used to, which I was not used to at all. Um, and I think it really kind of shifted my mindset. I think I started thinking a lot more logically, whereas before that, uh, like, you know, classes, it's more like memorization, right? You do your flashcards and pass the tests. But I think while not everything is super practical, but it gets you into this frame of thinking, this problem-solving frame of thinking that I think really unlocked a new way of doing things for me. But anyways, we were talking... You speedrun through it. Yeah. And was that the goal? the, the goal. No, I, I never, um, I never thought nook started as a project, but was, was speed running your, your CS degree, the goal?
34:34No, I tried, I was trying to catch up. Like, you know, um, my, my friends, they were taking these grad level classes, like early freshman year. And I was like, Oh shit, I'm behind. But did the call, like when you were like, there's a kind of poke at this a little bit. Yeah. When you're like in class doing double the workload of most other people to finish in half the time. Yeah. not genuinely actually that interested in the subject, or maybe you became interested in it, but like that wasn't your calling growing up or whatever. Yeah. Like, did it come easy to you? Did the concepts come easy to you?
35:07I think it came easier to me than some of, like I was able to catch up pretty quickly. Like, do you think you can write, do you think after that you could write code as well as your co-founders? Yes. Would they agree? Yes. Yeah, that's like, it's just like savant-like. That's crazy. Okay, so you speed run through it. And then you get through and you get your degree. You get your degree. No, so I actually would need one more quarter to finish Stanford. So I was, I stopped. I didn't know any of this, by the way. Yeah. I had no idea. I stopped in junior year, like the beginning of junior year and started working at scale.
35:54And I think. Sorry, when you say stopped. Yeah. What do you mean stopped? Oh, I like stopped, stopped going to school, started working at scale. You didn't drop out. I was I intended to go back. OK. Yeah. And. I was optimizing in going to scale in in starting to build Nooks as again as a project. I was always optimizing for learning. where I had done a bunch of the computer science classes and I was like, okay, I'm going to learn more by going and working at a company surrounded by a bunch of other smart people. And then in starting hacking on Nooks, my rationale, hey, I've mostly done AI research, applied AI work.
36:36I'm going to learn more by starting to build a full stack application. And I think until we decided to raise money and turn Nook's into a company, learning was really like kind of the primary and only objective. I think since then, the motivations have expanded to be one, surrounding myself by a team that's smarter than myself in some way, which is, I guess, related to learning. But, you know, just building a great team helps you enjoy what you're working on day to day. And then the third is like the customer impact, where I think in AI research, you're running experiments that take weeks and months and seeing if they actually are valuable on the order of quarters and years.
37:26Whereas in building Nooks to start, the feedback loops were, hey, you ship something and you see within an hour if people are liking it or not. So I think that learning, like the customer feedback loops, those kind of those motivations evolved over the course of building nooks of, you know, I think in that first year. So you're still today one quarter away from getting your degree? Yeah. Yeah. One quarter away. My my parents expect me to finish it. They do. We're like the athlete that gets pulled out of like college early and then the athlete goes back after like a 10 year career to like get their finish their degree.
38:09She'll give you an honorary Yeah. Can't they just take care of you? We'll see. Do you have to become like a, I don't know, like a hundred million in revenue or something before they like give you one? Let's send this podcast to the... To your application? Yeah, to the application. Do your parents like, and then I want to keep pulling this through line of the story. Do your parents like, what do they think you do? Like, do they have a sense of the gravity of what you're really trying to do? They don't live in the Bay, right? No, so they're actually visiting on Friday. I'm going to be able to show them the new office.
38:45Oh, good. Okay, then they'll start to get a feel of like what they're like. No, early on. So early on in Nooks, my parents were like, what are you doing? You're not going to school. And I was able to explain, hey, my friends are taking remote classes and I'm not missing out on much. Because it was COVID. Yeah, it was COVID. And I'm going to learn more by doing this. And they're like, okay, You can try it for a little bit. And I think as I've gotten more and more serious, they've actually been supportive. I think my mom has done a bunch of startup stuff and she kind of gets it. My dad actually, so my family growing up, we had a family sushi hibachi restaurant nearby.
39:28Kind of like Benihana. Yeah. Yeah. I'm going on Saturday. Yeah. Oh, really? Yeah. No way. um and uh growing up i you know spent a lot of time at the restaurant i folded napkins i helped paint the ceiling um in high school um every summer uh my dad um my dad said hey if you don't get a job you're gonna come work at the restaurant uh and i i took it uh more as threats than i should have and i was like oh shit i gotta find a job uh so i actually unfortunately i didn't work at the restaurant, which I really, you know, I really wish I did now. But, you know, kind of found found jobs every summer. So I think like my parents have they having run a small business and, you know, they kind of understand they understand what we're doing.
40:17I think I am very excited for them to kind of see the new office and, you know, see how much we've grown for a couple of weeks. We actually Rohan, Nikhil and I were working out of my parents' house, you know, for another couple of months, we were at Rohan's basement in Virginia and Nikhil's family's house in Cupertino. So I think they've been proud to see the evolution of the company. And so you started jamming on Nooks, built a full stack application in your words. Yeah. It started to get some traction. Were Rohan and Nikhil involved at this point? Yeah. So the way Rohan got involved, I was showing him the very early versions.
41:01This was like a couple months in. And he was like, hey, that button's off. And you should add this feature. And I was like, dude, just help me build it. And that's how Rohan got involved. And then Rohan and Nikhil were roommates. I was like a quasi roommate of theirs, but yeah, they were roommates. They published papers together. I think Rohan joined and started working and Nikhil was like, hey, wait a sec. I'm ready too. So we all got started together very early on. So you all go from one basement to another basement to a third basement. And at what point does the reality start to set in that this is like not just a project?
41:48I think so in the very early days. So our first users were Stanford classes. Like, I guess I can share the original idea behind Nooks. You know, it's evolved a lot since then. But in the early days of Nooks, I was interested in two problems. One was the remote work problem because it was early days of COVID. Everyone's working remotely. And can you build like a virtual office where people can collaborate like they did in person? And then the second problem, if you get that working like this virtual office, then can you make it smart? You have a lot of data on how people work, what are best practices, winning behaviors.
42:26So can you automate the feedback loops and help people get better at their jobs, help actually automate some of the manual parts of the job? And we spent a lot of time on like part one of like, you know, kind of building that virtual office, remote collaboration. At Stanford, I was on the ice hockey team. And a lot of my friends on the team were actually TAs in the computer science department. And I showed them the early versions of Nooks. And they were like, oh, this seems useful for office hours. So actually, it ended up being a lot of the Stanford computer science department used Nooks for office hours during the pandemic.
43:03And that was like one of the kind of early initial use cases. Um, we, we found though that, you know, everyone wanted to go back to, you know, in person classes and we were building the second best solution. Um, so that's when we realized, Hey, actually, um, let's, let's find something where we can actually be ordered, you know, um, how can it be a 10 X solution rather than like a second best, um, and, uh, ended up having a lot of startup teams using Nooks. So product, marketing, engineering, sales teams. And we found that sales teams were actually the most engaged. And that's how we got into kind of where we are today.
43:44You watch The Wolf of Wall Street. You know, the scene where Leonardo DiCaprio is making calls on the sales floor, selling penny stocks, and then everyone kind of gathers around and listens. So it was kind of that use case for how they were using the virtual office. The original features we had, you know, for the Stanford classes, we had a way for students to watch lectures together. And you can kind of like whisper and talk to each other like during the lecture. So kind of like you're actually in person. And, you know, Stanford actually wanted to pay us. Like that was kind of when we realized, hey, actually, let's take a step back and, you know, explore these other use cases.
44:20But the sales teams were using similar features to be able to make calls together. so you could listen to each other's calls, give each other live advice and coaching. And yeah, we ended up spending a lot of time, I mentioned, you know, making cold calls ourselves to, you know, say, hey, please use our product. And that's really how we built empathy kind of for this problem and got into the space. Because if you ask me, you know, coming from an engineering background, I thought sales, oh, that's a dirty job, right? Like, why don't you build products that sell themselves. I heard of Haley every time I heard that, yeah.
44:57Yeah, and I think spending a lot of time with sales teams using Nooks in the sales floor that we had built, trying to sell Nooks ourselves, that's actually how we've gotten to understand the problem as deeply as we have. I mean, I think the background too was helpful in that maybe if you had been a salesperson, you would have thought, oh, well, the power dialer space, that's like already won. Like there's nothing really to do there. And I think coming in, like actually hearing, no, there's actually all these pain points today. You can make something much better for cold calling. And then also organically just like figuring out.
45:29I mean, I didn't know this until somewhat recently, but just the prevalence of cold calling now relative to emailing is huge. And so I think just kind of like figuring out those things. I mean, it makes a lot of sense kind of given sort of the team's very, very strong technical and product background. But yeah, it's like these sort of non-obvious insights that have enabled them now to build this product where I think it's one of the only products of companies that I work with where I literally will go to meetings with founders and they will beg me, hey, Lemurie, can you please, I know we're a small team, but can you please get us on Nooks?
45:59It's crazy. Yeah. Yeah, I think build, like, we were talking about like when AI lets you do more with less, right? Do you do more with the same or do you do the same with less? And I think sales is one of those like grow the pie use cases where you can actually separate yourself from competitors by investing. And I think it's a lot of fun to be building a product like that. Well, this is back to my analogy of like, this is like the Glean analogy. This might be a weird one, but like it does remind me of Glean because at the time, no one is like waking up thinking about enterprise search as like the problem that they can't wait to go solve.
46:41And frankly, like for decades, companies have been trying to solve just that problem, right? Like Google has been trying to solve it. Then there was like a, there's a graveyard of companies after that that have tried to solve it. And I've been doing cold, like I started my career doing cold calls. Like I started my career doing cold calls and a lot of them, like 70 a day. And then at some point, like my startup, like didn't have product market fit. so I was like well I need to do more cold calls and so we like bought I actually I asked Dan if this solution still exists which is crazy it still does like connect and sell it's like I can't like I hope the CEO is not listening or something but like it's terrible it's just like a terrible product and like it's like ancients it'll be like using like like I don't know it's ancients I would make a cold call and then I would hear the click and then the customer the prospect would hear the click.
47:34And it was like over before it started, you know? So my point is like, but like this, the way that you've developed the solution is just like a elegant way of making something old new again. And everybody thought like, oh, sales is dead. Cold calling is dead. Prospecting is dead. Products sell themselves. And like, turns out none of that is true. You know? And I think if you can build an elegant solution the right way, similar to glean, like now you have the right to go do a whole lot more. You know what I mean? Anyway, more of an observation than a question. Yeah, no, I think, you know, to your point, like calling automation, there's a history of like calling automation.
48:17Calling automation is similar to email automation in that like you don't build a sales team today without an email automation tool because you don't want to pay reps to manually bulk send emails. And I think the sales leaders of today are actually realizing you don't want to build a team without a calling automation tool because you don't want to pay reps to listen to ringing and answering machines and finding phone numbers. And this is like very mechanical, right? It's like, this is not sexy. It's not like, you know, most people when you're thinking about AI, it's like, oh, build the AI account maps and the turn prediction.
48:48And it's kind of more on this intelligence layer. Whereas this starts actually more on the action layer, right, and doing the work. But I think the secret is that if you can do the work and that then allows you to own the human part of the job, there are actually a lot of virtuous cycles that you benefit from where if you help people have more conversations, you know then better who to target because you see who's saying yes and who's saying no. If you help people have more conversations, you know what message resonates and you can help coach and train the team. So I think like starting from this entry point has, that's one type of feedback loop where you help other parts of the product get better.
49:28Um, another actually is in, um, because our customers spend three hours a day on average using Nooks, uh, and sales reps make more money when Nooks works better. Um, we have every customer in Slack with us, you know, we have a Slack channel with every customer, every user. So thousands of sales reps, um, that I can DM and say, Hey, please try this. Give me feedback on that. And everyone is super excited to give us feedback because as Nooks gets better, they make more money. So it actually, like, I think product velocity is one of the things that sets Nooks apart in the space where we're able to move way faster than anyone else.
50:08Not only because we have the best engineering team and we're able to build the fastest, but we're able to point it in the right direction because we have those type feedback loops. This is a weird question. When Stanford was trying to pay for the early product, were you embarrassed by the product? Do you feel embarrassed? Like, does that, do you even have that emotion? Um, was I embarrassed by the product? I think in, in retrospect, like the, the product that Stanford was trying to buy. Yes. I would probably be embarrassed by that product today. Uh, am I, am I embarrassed by our product today?
50:43You know, right now? No, definitely not. I'm very, I'm very proud of our product, but if you ask me, you know, three years from now, I'll probably be embarrassed. So I think like, you know, hindsight is 2020. And do you buy this idea that like what you work on should be your life's calling? Meaning like right now in AI, all of the there tends to be like flies going towards lights of products that people want themselves to feel passionate about building. So like the coding one is a great example. Every engineer wants to make engineers more productive, right? And they want to work on engineering productivity tools.
51:20So there's like 50 of these coding companies. Yeah, at least. I don't know. How do you relate to what you're actually working on? How you recruit amazing engineers to go work on those types of things? How do you relate to the problem itself? Yeah. Yeah. Like one question that I ask, you know, every engineer who's considering joining Nooks is, would you rather have really interesting, hard technical challenges, but not understand the customer impact? Or would you rather have really interesting, impactful customer problems, but technically it's not very interesting? And we much prefer people who care about like the customer and the business problem.
51:57We, you know, we have hard, very hard interview process and we can assess for that technical bar. But when the motivation is actually tied to delivering impact, and customer impact, that's actually when you move the fastest, you move in the right directions. And the question, should you be working on your life's calling? Yes. You should work on something that gets you up in the morning. You're not going to build a generational company if you view it as work and it's your nine to five. So you need to build something that you're passionate about. very specifically what that problem is, I think there's probably a little bit more color, right?
52:37Where my core motivations is learning, surrounding myself with a strong team that's smarter than me in some way, and just great people, and then delivering customer impact. Exactly. There are probably several different types of companies you could build that deliver on those same goals. Yeah. All right. I buy that. Um, when we were in the final stages of, uh, Hannah, the CRO, you and I were on the phone late, late for me, early for you. Like it was like 9 PM and you're just like starting and, uh, like your workday is just beginning. And, uh, we, you were like, let me go talk to Rohan and Nikhil, like, let me get their feedback or whatever.
53:22and I was like cool like do you want to just like you know patch me in we can all talk like we'll visit tomorrow he's like no I'm just gonna go like knock on their door and I forgot like that that you live together like that all three of you still live together like you've gone from one mom's home to another mom's home to a third mom's home to now your own home but all together yeah um we uh uh we we like to stay close like uh and and this is a very personal question but like You have a partner, your girlfriend. You've been together for a little while. At what point do you feel like, oh, no, I think me and the boys, I think our run is over here.
54:02I think we got to go get our own apartment. Honestly, working together, I think I feel very lucky to be building nooks with close friends where work doesn't feel like work. And this is probably the case of, hopefully the case of most founders that you work with, too. but I think there's an extra element where I'm doing it with close friends where we hang out together outside of work we're friends with each other's families we've gone on some crazy adventures together once, another story for another time Rohan and Nikhil called the Coast Guard on me because we went on some crazy adventure on the beach and I think at what point do we stop living together?
54:45I think, hard to say um uh i want to keep it as as long as we can but what if like you go into like some intense roadmap session or something yeah and the outcome of that is like you're screaming at each other oh it happens it happens yeah yeah like we i think we each have strong personalities like i had a screaming maybe that's strong but like yeah we definitely like you're pissed at each other yeah there's they're definitely well i think the that ask why thing i keep coming back to that like we all we have engineering mindsets we approach things from first principles and because like we're able to like I think disagreement between us actually produces better ideas because the way the way we're coming you know when we feel strongly about something we back it up with like and here's why that you know this this roadmap is better or this idea this approach is better and I think because we're able to approach things from first principles is you it actually leads to better ideas in the end.
55:47Okay, fine. But like, then if you were like pissed at each other, then you like see each other in the kitchen. Yeah. Is it like awkward? It's like, oh, sorry. I yelled at you earlier. I think we're used to it. All right. And then maybe like one or two more just like top of mind thoughts for me that I've never actually gotten to ask you that I'm just curious about. Yeah. Like back to my billboard question about. Yeah. the constraints about a message on a billboard. Yeah. Like that was actually a serious problem that you're like actually trying to solve. Like you want to put a billboard up. Like, and one night we were talking and I think you like grabbed your girlfriend and it was like midnight and you just like went on a drive down 101.
56:33Is that true? Did that happen? I was in midnight, but yeah, we just scoped out some billboard locations. And okay, so the question that I had, because I was thinking about that after I hung up, I'm like, what a crazy, what like what a crazy life she's living right now she's just like yeah let's go for a drive and like check out billboards like does she is that like at this point this is just par for the course um yeah i think she so um when we started dating nooks was 10 people yeah um and you know now we're well we'll pass that and i think she has seen nooks evolve and you know seen all the crazy things that we have to do uh and i think uh she's been really supportive through it like She's definitely used to it by now.
57:13Do you ask her five wise? I try to limit. Just a few less wise. Three wise. Yeah, three wise. You should ask her what she thinks. Oh, I can't wait. Are you hiring? Yeah, hiring across the board. Hiring everywhere? Hiring, yep. Engineering, sales, implementation, customer success, support, marketing. if you're interested in joining an early stage company that's growing really quickly definitely check us out when you heard the word grit what do you think of probably that those early days of Nooks where we were making cold calls ourselves saying hey please use our product I think that was some of the time when I think being boots on the ground like that And like one, experiencing what our customers experience, but two, experiencing like the failure, the rejection.
58:11Right. It helps us empathize and it helps us also understand what is actually like the real problem to solve and hone in on like the customer problem. Thank you both. Thank you. Thanks to you, Ben. It's fun. That's it for now. If you liked the episode, please leave us a review or go back into the archives where we've done more than 200 episodes with some fantastic folks. This podcast is a Kleiner Perkins production, and I'm Juven. Thanks for listening.
From the publisher
Even with AI, sales still comes down to human connection.
This week on Grit, Dan Lee shares how Nooks automates busywork like research and dialing for thousands of sales teams, letting reps focus on the conversations that close deals.
He also shares his “do more with less” approach, why cold calls still convert, and how to maximize human impact alongside AI.
Guests: Dan Lee, CEO and Co-founder of Nooks and Leigh Marie Braswell, Partner at Kleiner Perkins
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