E255: How to Hire the Top 0.1%

0:00So Chris, you run a recruiting business. Give me a sense for the scale of Quantum today. Today, we're about 36 people. We partner with about 250 technology startups concurrently. We've built or helped build about 300 technology companies to date. Been around for a little bit less than six years. And we partner with 80 % of the tier one venture capital firms out there. 80%. So last time we chatted, you said the AI founders are at war and we're the arms dealers. that's what you mean by that great metaphor look i think we're in a talent war and there's always a talent war of some sorts but right now it's probably the most competitive one we've ever seen which is why you see zuckerberg spending a billion plus on individuals which we've never seen in history and so effectively wherever technology is accelerating and there's innovation happening there's going to be a war for a very small subset of talent that can produce asymmetric outcomes and so while these ai founders are at war with each other we are the arms dealers where the talent dealers, because once you have capital, once you have your idea, your main constraint is talent.

1:03And so we specialize in helping founders build those 0.1 % teams that can actually outcompete and produce remarkable outcomes. You mentioned 0.1%. Some people refer that to S-tier engineers. What's an S-tier engineer? And give me some indications that somebody's S-tier. So when we're looking at recruiting, I think you want to have a simple mental model for how to evaluate both the clients and the candidates, right? It's like, if I'm, you know, an 18 year old guy working at Starbucks, I'm not gonna go pull some crazy supermodel. It's just not gonna happen, right? So you have to understand how attractive am I as an employer and my opportunity and how attractive of a candidate can I land.

1:43And so when you're looking at tiers, if you will, it's basically a mental model to assess someone's pedigree or caliber, right? So an S tier individual is somebody who has exceptional traits. They have very clear evidence of greatness. And so if you look at engineering, for instance, an S-tier signal could be they were a 4.0 from Waterloo, which is arguably the best university in the world. Or it could be they were a Y Combinator founder and hit series A, and then you bring them back in as an IC in your company. But they've been an ex-founder, they've been a founding engineer at a notable company, they've won math Olympiads.

2:15Like, what is it about this person where they're so spiky in a particular area, where their resume just oozes greatness? And the reality is very few companies can actually land those individuals. You have to build traction and become worthy of attracting those people. It's very challenging. But more or less, the idea is when you're building a startup, the thing you care about is talent density. Talent density is king. If you run a service-based business, your team literally is the product. So the caliber of the people in your company determine the fate of your company. If you're building a product company, it's the people that are building the product.

2:51So again, the quality of the product that you can build and sell is determined by the quality of individuals that can build it. And so everything at the end of the day, if you simplify it, it comes down to talent density. Why was PayPal such a legendary company? They had 14 barrels, as Chief Reboys says. They had 14 monumental S-tier people that, after PayPal, all went on to build billion-dollar-plus companies. In some case, Elon might be the first trillionaire, but they had insane density of talent, and that's what allowed them to solve all these novel problems at scale. And so when you're building a company, that's the main priority, is how do I build the most talent-dense team?

3:25It's not like 21, 22, where everyone's bragging about, I managed a thousand-person company and we did this, this, and that. It's about good business. It's about revenue and profit per employee. That is the key metric. When you look at Mercore, when you look at Surge AI, who has in between 50 and 100 full-time people doing over a billion in revenue, that's impressive. And so you don't need a billion people anymore. You need better people that can leverage AI. And again, talent density wins. the best, most talented, nimble team typically wins in business. And AI companies don't seem to be constrained by capital.

4:00They seem to be constrained by talent. And that's obviously what you work with. But there's this new paradigm of talent over capital in the marketplace. How do startups incorporate that into an operating mechanism? Capital is almost a commodity at this point. If you're remotely talented and you're building an AI, you can probably raise capital from venture capital firms. And so the problem is, is not capital. You have to look at the system and say, where's the constraint? Capital is not the constraint. We have billions and billions flowing into AI. The constraint is there's not enough talent. It's very new technology.

4:33How many people have commercialized successful LLM agentic applications? Not that many companies. And so there's a very small subset of talent that has proven they can do these things. And so everyone's fighting over a much, much smaller pool of available talent. And then the salaries because of that demand go through the roof. And so companies, if you want to compete at the highest level, either you have incredible investors and incredible founding team, and there's a clear story you can tell just from the investors and the founding team and the idea, or if you don't have an ex-unicorn founder, you don't have 20 million from Andreessen, you have to figure out how to tell a damn compelling story and then get as much traction as fast as humanly possible, right?

5:12That is what's going to allow you to attract that next caliber person. One of the difficulties of the space is that AI keeps on improving, that LLMs keep on improving. What are the second order effects of recruiting in the space where AI keeps getting better? It's an interesting point. When it comes to AI getting smarter, my common sense says you're going to need less engineers in the future since one person with AI can do much more. So you need much more sophisticated people and companies with great design taste, great product sense, commercial aptitude, architecture skills. But the actual AI can do a lot more work as we continue to progress.

5:49If you have today mid-journey that has, you know, worth billions of dollars, has dozens of employees, in the future you might have somebody with billions of dollars with five employees. And is this software genius? Well, if you look at like the probably best in class model right now, it's the Enterprise 4 deployed model, that Palantir coin. Every company is repeating the Palantir playbook right now. We are forward-deploying engineers as vertically focused on specific customers and customizing workflow. And they're using AI. But I talked to a founder last week. He's trying to disrupt the entire forward-deployed model.

6:22Where he's saying that these forward-deployed engineers, it's still 80 % engineers, only 20 % actually using AI. But he's saying when we improve reinforcement learning, and these machines actually get really good at learning from each other and from themselves, eventually even you know forward deployed engineers 80 90 of their jobs can be automated so i don't know how far the rabbit hole goes or where things will evolve to i think what's interesting from my angle being a recruiting firm is we don't specialize in one particular technology we specialize in the future so wherever the puck is going no matter how technology evolves there's going to continue to be a refined and constrained set of individuals that are capable of innovating and pushing the future forward.

7:04And so that's the game that we play is how do we always know where that puck is heading so that as these technologies and skill sets continue to evolve, that we have those relationships and we can uniquely place those people within startups. Tell me about the Sequoia founder whose company you fired as a customer and what happened there. Yeah, I mean, this happens all the time. I think with early founders, you usually have to have a little bit of reality distortion where you think you're the hottest chick in the bar. and then you realize there's a lot of hot chicks in the bar and that your company is not the only amazing mission and so you're able to recruit a lot of early founding team members really competitive rates and it worked really well and then you know you realize at some point that doesn't always keep trending so at some point what got you here won't get you there and you have to completely reshift how you look at things and the biggest mistake i see a lot of founders make is they're very constrained on cash and compensation and equity and you've got to just you have to understand the realities of the market.

8:02And so there was one company in particular that was looking to hire a lot of people. And we said, you have to basically be here in these ranges. They said, no way we're going to figure this out. We said, okay, we'll try it out. Seven offers later, seven offer declines. We had no results in three to four months. We said, look, you have to come up to these bands or otherwise we can't help you. So we ended up parting ways with the client. They came back three months later, hadn't made a single hire yet. And we said, hey, are you ready to change the bands? And so they did. And we were able to place about 17 of their next 20 people that ended up unlocking a billion dollar valuation.

8:38And so for them, they had distribution. They had a great founding team. They had it all figured out. But engineering and velocity of product building was their only constraint. And so we were able to help them maneuver through that by very simple things, just fixing recruiting processes to accelerate time to close. So we have a faster recruiting process and obviously making sure the comp bands were in alignment with the caliber of people that they were targeting. And then once that problem was solved, it was unicorn status for these guys. It was an interesting A-B test where it was upstream, they already had where Sequoia backed.

9:11And then it was upstream, they A-B test their own strategy, which is paying up for talent or not paying up for talent. They got to test both in one company. Yeah, it happens all the time, man. I think a lot of founders get very bottlenecked. Well, I recruited this guy who was a founding engineer from Uber at 200k base. It's like, you probably knew that guy, you had a relationship. So people think because they're able to land a couple incredible hires at really competitive rates that they can somehow scale that strategy. And what you do initially just does not scale. So you have to change your mentality and your approach as you continue to grow your company to ensure that you're going to win.

9:45Rank tier, what S tier engineers, the top 0.1%, even higher than tier one, what they look for and what they prioritize. Give me a rank rankings of their preferences. When you're looking at S tier individuals, they're looking to join S tier companies. And so they're probably, there's a myriad of things that could be, but when I look at the tiers and how we evaluate that, one is their backing, who are their investors? More importantly, who is the founding team, right? If the founding team is all from tier two companies, they're like, ah, we want S tier companies. I had this problem actually with two founders that had raised$20 million and they're really smart guys and they're building a foundation model, but neither of them actually came from research backgrounds.

10:21And it was nearly impossible for them to recruit an ST researcher because the researchers didn't respect any of their backgrounds, even though they had great business sense, amazing founding. So the caliber of the team they're going to assess, they're going to say, am I really inspired by the density of talent here? Do I feel like this is a privilege to work alongside people? That's going to be very big. I would say the market size, the opportunity, the traction, look, they're going to want to be excited about the mission. Some people have a very particular mission they're excited about, a domain space, a problem space they're excited about.

10:49And a lot of people are more practical. They're like, I'm really good at this particular skill set. I want to apply my skills to a company with the greatest commercial upside where I can have a giant win. So each person's going to have different core motivators, but the DNA thread that connects them all is A players want to work with A players. S tier people want to work with other S tier people. So they want to work with people that are really fucking impressive, really obsessed of what they do where they can have giant outcomes. And because of this talent density, you mentioned probably the most famous case of the PayPal mafia where these dozen of people have become so successful.

11:22Does it sometimes make sense to overpay for the first couple of hires, knowing that it's not sustainable so that you could create this talent density? Or is it something that you have to keep on paying up for? I think you are fine overpaying. My perspective is this, you can't afford, nor do you need S tier people in every category from top to bottom of your business. It's not possible. And so the way I think through this is figure out which areas in your business that you need to compete on and be the best at. What areas in your business that if you spiked the hardest in would allow you to dominate that much more.

11:54And so for some companies, it's going to be product. For some, it's going to be design. For some, it's going to be engineering. For some, it's going to be more backend, high throughput, low latency, like hedge fund type stuff. You don't need beautiful UI work there. So you don't need the front end engineer from Figma or linear, right? So figure out what areas of your company are truly critical to you becoming the leader in the market and then over index there. And then anyone who's in leadership roles, who's leading your backend, who's leading your design, you want to try to have the leader or the barrel who's kind of scaling and owning that division.

12:26You want that person to be as high caliber as possible because it's highly unlikely you hire a tier two or tier one individual that's somehow able to recruit these S tiers. So the density upfront really matters. There has to be somebody's standard bearer in every single part of the business, every function. Yeah. You need someone leading each function. That's truly the best at that function. And then figure out where you are going to need to out-compete people and make sure you have the absolute best in class people there. Like for ramp, for instance, they definitely, I would say they compete more on product than engineering.

13:02They've got some damn good engineers. don't get me wrong, but there's, I think, deeper talent density and other companies in sharing, but their product is amazing. And I would say they're underwriting their capital markets team that does all these creative financing deals. I think that's a big wedge they compete on. And so those people have to be extremely elite. And so, again, you don't need to be remarkably elite in every area. Like a lot of these companies that have PLG products that just sell themselves, like they don't even have great sales teams. They can get to hundreds of millions at ARR without even bringing in big sales teams because the product itself is where they need to spend that time making sure they have the absolute best people in the world.

13:38So bottom line, I think it's just really important to try to optimize for density, hire the best people you possibly can early. You want to pay attention to pedigree. You want to pay attention to what are the signals that make this person truly elite? Schools can be overrated. I would say they're very important if it's a junior candidate, not as important later on, but like do they come from exceptional backgrounds that they've done exceptional things that companies we respect? it de-risks you because you know they've seen greatness before. But then don't over-index on pedigree. Over-index on the human being.

14:06Like, do they genuinely get excited by the work? Are they going to be pulled by the work? Are they just here for a commercial outcome and their heart's not really in it, right? Do they fit in with your work style? Do they fit in with your energy, your culture? Those things are equally important. But the key here is that, like, you want to build a great team. You have to have great human beings, and you're better off hiring fewer people that are truly world-class. one of the reasons i wanted to get you in on the podcast is you're in the eye of the storm there's an ai storm and you are at the eye and upstream of everything which is talent yeah and one question is it's almost a thought experiment for most people but for you it's actually your lived experience and what percentage of times can somebody have this s tier talent density and not find a product and not be successful from a product side if they have the right talent in the room is that even possible or is that common great question i think it's still common i still I think it's still common.

14:58Look, I don't think any amount of talent can find product market fit. Right. Like the founder, in my opinion, is still responsible for finding PMF. I think the team is an accelerant. I think that's really on the founding team to find PMF. Now, I still think that talent matters, but I think there's plenty of remarkably talented teams with the most insane people in the world. The products just don't hit. And just because I've worked with a number of people who've built billion and decabillion dollar companies that assemble great teams and build their next product, it just doesn't work. Because what you did in the past has no say in what you do in the future.

15:31And so I think talent alone isn't the answer, but if you do have a good idea and you can find PMF, the fruition of your potential is gonna be almost entirely dependent on that. But again, if you have a great founder, that founder is the tip of the spear when it comes to the talent density. And so good teams, I will say, even if the product sucks and they like they'll pivot right twitter from odio pivoted into twitter cursor was a pivot sigma was a pivot all these companies are pivot so great teams i think pivot if they're not in the right model and can usually figure things out but again venture is a very risky bet it's a gamble no matter how smart you are no how many billion dollar companies you built so it's just a matter of probabilities and i would say your probability of success dramatically increases based off the caliber of your team is the opposite true which is no matter how good of an idea or maybe you've gotten early product market fit that with a bad team, you just can't go the distance?

16:28I think a bad team, you're probably screwed. But I think, in my opinion, an average team in a really hot market can still crush it or an incredible team in an average market will be average at best. So I think the market matters a lot. Like, let's take what we're doing right now. AI is hot. It's not hard to bring in business if you're a good recruiting firm right now, right? It's, there's way too much demand. So I see companies that are very average actually doing pretty good and we're doing exceptionally well. But again, we have a fantastic team and we're benefiting from this incredible wave.

17:01And we just happen to have a big boat to ride that wave, but average teams can still win and perform now long-term. I don't know if they'll ever, you know, I think they're, they're less defensible, but they can still win. I think the market you're in and the directional correctness is actually more important. Support for today's episode comes from Square, the all-in-one way for business owners to take payments, book appointments, manage staff, and keep everything running in one place. Whether you're selling lattes, cutting hair, running a boutique, or managing a service business, Square helps you run your business without running yourself into the ground.

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18:10And when you make a sale, you don't have to wait days to get paid. Square gives you fast access to your earnings through Square checking. They also have built-in tools like loyalty and marketing to your best customers keep coming back. And right now you can get up to$200 off Square hardware when you sign up at square.com slash go slash how I invest. That's S-Q-U-A-R-E.com slash go slash how I invest. With Square, you get all the tools to run your business with none of the contracts or complexity. Run your business smarter than Square. Get started today. And to continue the analogy we started with, we're AI recruiting wars and you're the arms dealer.

18:49What are the weapons that are available to you to recruit the top talent? From a weapons standpoint, like we use basic technology. We don't have any technology differentiator, but the way I look at it is if we're going to war and you've got machine guns and grenade launchers and I just have pistols, you're gonna have a huge advantage. even if I'm a more skilled operator. And so the arms for me, again, just goes back to the quality of the talent, right? If you're trying to build a foundation model, it's gonna go compete with one of the big dogs. And I can pull you a researcher from OpenAI or Anthropic that's an expert in this field that you're gonna dive deeper in.

19:22And, you know, the other person's competing with some random researcher that's unproven from a random university. It's like, what's the probability this person is gonna win? So you just, you wanna be as stacked as humanly possible going into war. right? You want to make sure you're stacked with the absolute best equipped team to solve your business problems. And so I just look at it as a very rudimentary metaphor of like, yeah, you just want the best people. The people are your arms, right? Because the people are going to be the ones building the product and selling it. And so you just have to be ruthless with your standards for who you are.

19:55And then again, you need a right partner who, if you can, if you can produce this yourself, awesome. If you, if you can't, you need to pay for a partner. You need, like there is almost no amount of money. There's certainly an affluxing point where it stops making sense, but there's almost no amount of money that you could overpay for the right people. If they can create billions and tens of billions of enterprise value with a small team given the leverage of AI, you can't afford not to try to find those people. And so that point, you're willing to pay Navy SEAL teams to come in there and help you land those people.

20:27And perhaps this is a dumb question, but you gave this example of the open AI researcher and anthropic researcher and some random researcher at a university. Let's say that random researcher is at a Harvard Stanford, similar IQ. Why is it that this open AI and anthropic researcher has such a leg up on that person? Is it because of their learnings and unpack why that very specific experience is worth that 10x in call? Look, I don't want to oversimplify it because this random researcher from this random university could have some really in-depth experience or a mental model of the world. They could see something.

21:01Oh, again, there are these outlier hires you don't want to overlook and simply pedigree hunt. Oh, just because they're from OpenAI, they're going to be fantastic and they're going to make me win. That is not how talent works. But in general, you want people that have seen greatness before. It de-risks you, right? You want people that have evidence that they have built something equally complex that you are looking to build or more complex. You want to see that they've been able to thrive, get promotions. You just want a story. The more experienced someone has, the clearer the story is. And when we're hiring people, we're trying to fill in the end of the story.

21:36We're trying to assess what we have in front of us and write the end of the story, but we don't know it. And so the more story there is, the more data we can actually start to read and see patterns. Okay, this person went here. Every place this person goes, they seem to find the hardest problem and solve it. That tells us something. When someone's not as experienced, you're really betting on future potential. It's riskier. They can pay out big, but there's just less evidence to make a conclusive decision. And they have less experience. they're going to come in. And in some cases that might be better because you need to completely reimagine something and experience can actually be a bottleneck.

22:05But in a lot of cases, having experience, having seen multiple different environments, you understand the problems that you're going to face. You understand where this company needs to be at 18 months. You've already seen the future because you've lived it at another company. And so that company is buying that experience. They can accelerate their guarantee or probability of, of solving that as fast as possible. So experience is just beneficial. But I always say, look, if you're building a startup, hire for two people. One is an expert that brings deep expertise in a particular area. And two is high slope, 20 something year olds.

22:37Like either find people that are the best, their particular craft that bring in an intense amount of specific knowledge that you need, or hire really smart, really high slope, 20 something year olds that can work 80 plus hours a week and just muscle your way to victory. Right. And those are two great archetypes of people. Which is essentially the same thing in five years, right? If you have somebody starting high and still with a nice slope and you have somebody starting lower, but with a high slope in five years, they'll cross. Yeah, exactly. What does it mean? Why is it so important that that engineer has seen greatness?

23:09What does that mean? And why is that important? Look, I think in general, if you're trying to build a great team, you need great people. How do you know if you have a great person, right? You have to look to the history, right? My odds of picking a great person, if I can see and evaluate their history versus me going and blind without knowing their history and just evaluating a human being in an hour, it's going to be way harder to do. And so I just want to look for any signal. If it's a junior candidate, right? Maybe I'm looking at everything in their life. Were they a D1 athlete? Were they an immigrant that came from nothing and had to start working when they were 12 years old to take care of their parents and their family?

23:46What qualities does this human have that shows me they have asymmetric levels of grit, tenacity, ambition, sharpness, et cetera? Now, if they're more experience, I'm trying to build a core banking operating system for a new company, right? I want to hire someone I know has done that at a high quality because if I fuck that up and I hire someone who hasn't built something as beautiful and complex and sophisticated, I hire someone who's done it at a little shitty startup versus like a company that did that at successful scale, I'm in a huge, I'm in massive levels of risk. There's a very high probability that person doesn't know how to do that.