On starting and scaling Bloom Institute of Technology

All right, so today we have Austin Allred. He is the CEO of Lambda School, which was in the summer 2017 batch, and Lambda School is a CS education that is free until you get a job.

So, Austin, what I wanted to ask you about, you mentioned this on a few podcasts that I've listened to you on, and basically there's this core idea in Lambda School that you have to be kind of confident enough to even apply, and this is a great opportunity for many people, but what I'm curious about is, how do you encourage people to do something that's probably good for them that they might just be scared to do or they make excuses about?

Yeah, I mean, I think that's actually the problem we grapple with the most, and I think Patrick Halson said something along the lines of, if you think about it, the highest leverage activity any human can have is inspiring other humans to do what they're capable of, and in many ways I see Lambda School as like the realization of that.

So, we've had a lot of students, you know, in the past you would graduate and then whenever you felt ready you would start applying for jobs, and we'd have students that would just wait and wait and wait, and we'd be like, what, you know, why are they not working hard? What's going on? And you talk to them and you realize it's massive imposter syndrome.

They're just not confident or comfortable with the idea that they're now a software engineer, and so they're just kind of procrastinating that. So now we have some mechanisms that get you to start applying earlier, but yeah, like the minute they start applying they get interviews, they get hired, they get a six-figure job, and it's like, what were we waiting for, right? You're totally capable.

And what about the people before Lambda School? A few of the questions that came in from Twitter were basically like, isn't this just an opportunity for rich people, you know? Like being able to leave your job and commit full-time to a seven-month program. Yeah, my first answer to that would be we have part-time programs as well, so you can do it evenings and weekends.

We have experiments running where we pay people living stipends. That will be expanding greatly. We'll be announcing something in the near future along those lines in concert with a few other tech leaders here in the Valley. But yeah, I mean, the number one problem we have to solve on the admissions side is getting the people who are qualified to actually apply. Yeah.

It's kind of a, you wouldn't think of it as being a problem. It's a YC problem too. Yeah, no, it totally is, yeah. Some of the best companies are just like, yeah, I just don't know if I can get into YC. And that's the difficulty of having a good reputation where a lot of people want to go there. You just, there are people who assume that they won't get in, which is not the case.

Right, I mean, so your acceptance rate, maybe it's changed, but I heard you say it's 25% of the people who make it through that first initial test? Of the people that make it through the pre-course work, it might even be higher now. I mean, the pre-course work is more difficult, but the vast majority of our selection mechanism is the pre-course work, how well you do on it, if you put in the time.

Sometimes I wonder if we could just make the pre-course work really long and have that be it. No interview, no nothing, just the work. Yeah, I mean, because that's obviously, like your business hinges on you assessing that risk, right? Correct. If you could make it sufficiently difficult, it would work. Yeah, in theory. I mean, you run the risk of false negatives, or false positives, I guess.

But yeah, all that we need to find out is are you of average mental intelligence and will you work really hard? Yeah. And I think YC is similar, right? When I got into YC, I felt super intimidated.

And there are brilliant people all over in the room, but just because you have a PhD in computer science from MIT and you got a 1600 on the SATs as a freshman doesn't necessarily mean you'll have a successful company. It's not directly correlated. I think in the past, it's possible that YC was fooled more often by fancy degrees and PhDs and stuff like that. Possibly, yeah. Not the case anymore.

I mean, in my YC group, there were a couple, like a 15 and a 16-year-old kid. Oh, you were in that group? Yeah. Yeah. Yeah, that was a fringe case. So I'm curious about, there's this core insight with Lambda School, which centers around what if we didn't have to charge $10,000 for this dev school? How did you reach that point? So I was living in rural Utah before I moved to San Francisco.

And when you move to San Francisco from a small town and you see just the discrepancy in opportunity, I guess. So it was easy to look around rural Utah and be like, look, that guy is just as capable and intelligent as that guy in San Francisco. But in Utah, that guy's making 30K. In San Francisco, that guy's making 150 and he's leading a team. So how does that work out?

Is it just what jobs are available? And I mean, if you talk to people, you realize it's more about opportunity than anything. So to tell a guy that's making 30K, hey, just drop 10K on an education and there's a 7% interest rate on the other side and hopefully it works out. That's actually a really big ask.

So I have to put it in terms for VCs sometimes and say like, imagine spending half of your annual income on an education on a bet, right? You have, most VCs are very well off and you have that kind of risk that you can take. So you have to kind of put it into that similar psychological context that people just can't afford that risk.

So why are people in these situations signing up for University of Phoenix type programs but not the dev schools? Because it's a similar choice, right? So I think the first reason is honestly because the University of Phoenix is more aggressive in their marketing tactics. They, I mean, they have the, they don't really care whether you succeed to some degree.

If they can, they're backed by, the loans are backed by Uncle Sam and whether or not you're successful, they get paid. So the incentives are fundamentally misaligned and if the University of Phoenix can get you to sign a piece of paper, they get 80 grand and that's it.

But the reason people are, the reason people opt for universities generally speaking versus code schools is they've, my entire life growing up, nobody ever said there's a path to success that's not college. And I'm not a college graduate. My older brother isn't a college graduate. A lot of very successful people I know are not graduates.

But yeah, everybody growing up just said, go to college, doesn't matter what it costs, just get a degree. It doesn't matter what you study and you'll be successful. And I think my generation is now realizing that's fundamentally untrue. It isn't only not good advice, it's probably bad advice, net net.

And the newer generation has the benefit of seeing people with hundreds of thousands of dollars in student loans and working at Starbucks and clearly something was off in the advice that we were given. So yeah, I mean, I went to NYU, so I know the feeling. I graduated with like 50. And that's pretty good going to NYU. Which is okay. Yeah, I got a bunch of scholarship and it worked out all right.

I mean, it's still a lot of debt to be clear. Yeah, dude, I was an English major. So I got all the jobs I've gotten have been through skills I've learned outside of NYU. Obviously I can write fairly well, but for sure. But the real upside was being in a huge city where I could start working early. And I think that was a real competitive advantage. And I'm curious about Lambda School in this way.

Because at NYU, once I started, I never went home again. Every summer I was working and then I was working during the year and then I was realizing that I could cram all my classes on one or two days and work full time. And so I had easily a four year advantage on all my friends who went to Colgate or something like in the middle of nowhere. So how do you take advantage of that at Lambda School?

Like getting people in early, getting them a network? Yeah, so there are a couple of things. One is Lambda School is nine months full time versus a four year degree, which is obviously four years. So the average Lambda School grad, if you had two students, one started a university at the same time as another student started Lambda School.

By the time the student's graduating from university, the Lambda School student has three years of experience and has paid Lambda School off and is a quarter million dollars ahead, at least, of the university grad. So net net, it's pretty obvious. But the network is pretty key. So most of our students are coming in with no network, a lot of students from either inner cities or rural areas.

And we basically have to help them build that and then build a network around them. So we have a full time team that is just bringing in companies to hire students. Part of the school itself is actually, okay, here's how you network, here's how you find other people with similar backgrounds, hired in engineering roles on LinkedIn. Now we're gonna go contact them.

That's actually built in the curriculum. Oh, I didn't realize that. Yeah, can you actually break those down? I'm very curious about how you, you know, tactically explain networking skills. Because I know you wrote a growth book before Lambda School, right? So you're kind of like into breaking these things down. Yeah.

Say I'm a graduate or I'm in Lambda School, at what point do you start teaching me, I guess you could call it soft skills? So now you meet your career coach at week three. Okay. So it's very integrated into, like it is Lambda School, right? It's not a separate external thing. And we have careers lessons every week for the entire school.

So for example, you know, we train students to do informational interviews, which is find someone with a similar educational background to you. So use LinkedIn's advanced search and search for schools that are X, Y, Z, in locations that are this and with careers that are this. Now you have a huge list of people who are just like you. Reach out to them and ask if you can grab coffee.

Just, or jump on a phone call and say, hey, I want to break into this field. What do I do to break into this field? And probably our best job offers actually come through that. Your best job offers always come through networking and meeting people.

We're really close to the point at which we just say, you know, if you have to use an application to like click an apply button somewhere, just throw it in the garbage. Don't do that anymore. Or at a minimum, we'll have somebody else do that for you. So now to help with that, we are hiring right now 37 interview sourcers.

So those are folks that are just going out, they'll take your specific information and they'll go out and help find companies as well and bring the companies to you. So we have an entire team that's dedicated to that. The future we're going to look a lot like a talent agency, basically for software engineers and designers and whatever else. Right, right, right.

So in terms of the other, there are a couple questions around, well, so John Palmer asked, can or what other pieces of the university experience can be unbundled? And the thing that I'm in particular curious about is the way you treat education in the sense of Lambda School is like, hey, this is job training, right? Like this is the goal of making money.

It's not about, you know, being altruistic and necessarily making artists or whatever you want to call it, right? Do you see a traditional, a value in a traditional liberal arts education in like those elements of school? For sure. So I see value absolutely in the liberal arts, right? I do disagree that A, the only way you can learn the liberal arts is within the walls of a university.

So in my mind, a lot of the people that we're talking to, you know, if you're 35 and you've never had a very high paying career, the prospect of let's take out $50,000 of loans to study Shakespeare is not a bad thing per se, but probably not the right thing at the right time. Yeah. So we are, yeah, we're entirely vocational or a trade school basically.

And we want to help you make as much money as you can. And then when you're making a lot of money, it's a whole lot easier to make decisions around what you'll learn in the liberal arts. In fact, that may be an add-on we add to the school later, but not, it's just not the focus right now. There are a lot of people that do a really good job at that and we're okay to leave that to them for now.

Yeah, because I think that's, it's one of those things similarly to signing a student loan when you're 18. Like you don't really know the terms of the day. I mean, like you can read it on paper, but you don't really understand the dynamic you're about to enter.

Whereas when you're say, yeah, you're 35, thinking about switching careers, you're much more practically minded or you might just be interested in indulging. I think we've romanticized it a little bit, right?

Like I went to the liberal arts portion of the liberal arts degree before I got into the specialization and like it was valuable, but I've learned way more by reading books and meeting people and other stuff than I did in the university. So I get the value, but I don't buy the argument that like that's the only time and only place that you can become well-rounded. That doesn't make sense to me.

Yeah. I mean, do you see there are elements of value in unbundling other aspects and like really building that into Lambda School? For sure. Yeah. Yeah. Okay. So there's another question here from Steve Claiborne Noble, who asks, as competitors begin to copy your model, which is, we should talk about, it's an income sharing agreement. What front do you believe you'll be competing on?

All of them. All right. So the way I describe Lambda School is it's, people know Lambda School because of the business model, but the business model is something that's upfront. That's not what makes Lambda School works, right? You can charge whatever you want or however you want. The key is making that successful. So our product, our educational experience is I think among the best in the world.

And it has to be the way we've built it in order to make a free upfront and online education work. I mean, when we started, our dropout rate is what was killing us. Now we're graduating more than 85% of students that start day one. And a lot of the dropout is because of reasons outside of our control. It's financial or life circumstance or whatever else. So we have a product that people love.

They come out on the other side as great software engineers and we have a hiring network ready to hire them. That's all really difficult. Then the admission side of knowing who and how and what to accept, that's not something you can buy, right? You just have to figure that out over time and eventually it'll be very data driven.

We'll be able to tell on before a student begins Lambda School, what they're likely to be hired at and what their likely outcome will be, similar to a lending company. But there's no credit score for people, right? You can't say like, what is this person's potential? There's no inputs that you can take right now that can determine that. So nobody knows how to underwrite student risk.

Nobody knows how to train students online. Nobody knows how to place students nationally at scale. And figuring all that stuff out is the hard part. Plugging, throwing an ISA on the front end is the easy part. Yeah, okay. So you're just hoping that like, you're much further ahead than people realize. Way further, yeah. And I'm sure there will be competitors.

Sure. But the thing that scares me isn't somebody adopting our business model. That probably has happened that I haven't heard about and will happen a million more times. What will make us win is the student experience and how fast we can move in making that better over time. Yeah. And that includes the outcomes that students have. So all of my time and effort and energy is focused on that.

And that's really freaking hard. Okay. It's way hard. Yeah. So yeah. So you were profitable before you did YC, right? Correct. Okay, or yeah.

Maybe not usually profitable, but profitable. We were profitable by any definition. Yeah, there you go. Yeah, OK, cool. So was there an element of fear around being copied that led you in the path of raising money? No. So we actually sat down with a YC partner. And we said, OK, we don't need to raise money right now.

But if we do, we'll suffer x percent. So we modeled it out. We actually created a financial model and said, here's the dilution that we'll suffer. And with that money that we'll raise, we'll be able to grow like this. And therefore, you know, and it came out to something like Lambda School will be 10 times bigger than it otherwise would be. And it will suffer, call it 15% dilution.

So that's an easy trade-off if you actually model it out. And that's the reason we have continued to raise. I mean, before we started Lambda School, I was like, I'm never raising VC again. Right. Well, we should tell that story. That was a cool story. Yeah. And now it's a year and a half later, and we've raised $48 million.

And it's not going to be the last we've raised. But if you look at the growth rate of the school and the revenue, if you look at any number, all of those raises were a wise decision in retrospect. And there's a reason VC exists, right? When you have a company that can grow at extreme scale and capture a market and create way more value, that's why you raise VC.

And the realization for us was realizing that Lambda School could be a successful bootstrapped company. But if we raised and used a little bit of fuel, we could just be much bigger and much more impactful. Yeah. Well, I actually don't think it's dissimilar from student loans. Like, there's a dynamic where it works really well for you.

And there are other dynamics where if you don't know the terms of the deal beforehand, there are different incentives. And it doesn't work out well for you. Right. So this is kind of you got burned before with your first company. Yes. Yeah. So this, I mean, if I remember correctly, you were about to raise an A, and then it just fell through.

We had docs done for an A, which is not normally when things fall through. It was a very abnormal story. So it was December 23, and we were waiting for a wire any day. And then the gentleman who was leading our series A called me and said, actually, we're not. Well, he actually had his secretary call me and say, actually, we're not doing the deal. And I said, can you tell us why?

And they're like, well, we're just not confident in the company after a month of due diligence and going through all the paperwork. I mean, our law firm was like, we've done thousands of these deals. We've never seen this happen. And we were out of money. So I didn't want people to go through the holidays planning on coming to work in January, and then the company not being there.

So I called the whole team on December 23 and said, I think it's over, guys. I don't know what other options we have. And we had other people who would have funded us, but it's really difficult to like, hey, you know how we went down a month and a half with that VC? Well, they pulled out, so you should fund us. It's very momentum driven. So that's why I was very anti-VC.

Now, I think there are companies that should raise VC. There are companies that shouldn't VC. It's just dependent on the circumstances and the details and what you're looking for. Yeah. Yeah, but then you left, and you went to go work for another startup, right, after writing the book? So I was broke. I was working remotely in the middle of nowhere in Utah during this time. So we go back home.

It's not like there are tech jobs. I mean, the closest tech job was probably two hours away, an hour and a half away. Out of money, I used all my savings to make employees and contractors whole, because we were burning it down to the wire with the company funds. And then my daughter, who was born, ended up in the hospital for a month.

So we were just like, actually, she's only in there for a week, but it felt like a month. And the bills may as well have been for a month. So we were out of money, trying to figure out how to recover. And I had written a couple of blog posts about growth as we were working on the company that had taken off. And so I said, OK, we're going to turn those blog posts into a book.

And I emailed everybody who had subscribed to my blog and said, all right, we're launching this Kickstarter, and I'm going to finish up this book. And the Kickstarter did something like $120,000 in sales. I mean, that's what I'm good at, right? How many people were on the list? A couple thousand. That's really good.

If there's one thing I'm good at in life, it's growing something quickly, building hype for something quickly. That's kind of my superpower to some degree. So use that in its fullest for the first time. And then a few companies saw the book and said, hey, come work for us, one of which was LendUp, which is a YC company. So it's still interesting, because it's fairly risky.

You lived in the Bay before. You lived in your car, right? And then you moved back to Utah. You could conceive of getting a tech job, right, rather than writing your book at that time. Why didn't you do that? So I kind of did both, right? It was just whatever I can do to get money right now. And a book was honestly faster than a job hunt.

Well, maybe that's not true, because I could have. Yeah, it's actually not true. I don't know. There's not a good reason. I had offers within days. So I imagine the scenario is like, hey, here's something. I've been really interested in this idea and question lately of, at what point did you kind of find your voice?

And people talk about that in the context of art, but I think it's the same for entrepreneurs, in that kind of confidence, like, oh, I'm just going to do my thing. And I could, yeah. So it's funny. As everything was winding down, I went to one of our past investors. And I was like, what? What am I going to do? And I was paying myself.

I'd started out paying myself $40,000, and I'd recently given myself a raise to $60,000. And I went to that investor, and I was like, what? How can I pull this out? I don't know what I'm going to do next. And he said, well, you don't have any marketable skills. You're never going to make more than $60,000 a year. So maybe you should go find an internship somewhere. I was like, OK.

That's where your mindset is, right? Maybe I can make $60,000 a year. So I actually made sure that the first job offer I got was double that, just out of spite. But it took me a while to build up the confidence to, like, people were telling me that, well, when you're the CEO of a company, your only job is to make that company successful.

And if that company fails, by definition, you're not a good CEO, right? You could debate whether or not that's true, but realistically, your job is to be successful, right? And so that calls into question, well, what do you actually do? What are you good at? Do you have a skill set? And I'd never worked. I'd worked in marketing before, but never in growth, growth.

And so I was like, I don't know if there's anything I can do. And I didn't believe that people would trust that I had a skill set that was valuable, because I had investors telling me you don't. And clearly, they know more than I do, right? So it was a psychologically difficult time. And I thought, the only way I can show people what I can do is by publishing this book, right?

It's funny to think about that. I've never thought about that. But in retrospect, starting a company is, by definition, saying, I think what I can do is worth more than people will pay me for, right? I think that I can do something, whether it's because you can't measure it.

I think Paul Graham has an essay about this, something about measurement and leverage, and how companies can't do any of those things very well. So if you want to get to a place where you can make a lot of money, get to a place where you can measure it, get to a place where you have leverage, and so you look at pro athletes, anybody can measure the number of dollars that Michael Jordan brings in.

So it makes sense to pay him $100 million a year. Whereas even if you're the best software engineer in the world at a small company, they're not going to pay you $100 million a year. Google might. And Google has in the past spent $100 million to retain Sundar and stuff like that. But yeah, it's mispriced human capital is kind of fundamental to it. Yeah, but it's also a core to your business.

But that, like, that's, yeah. I think that's the key. That is the insight. It's saying, you know, if you look at any asset class in the United States, it's being traded on Bloomberg terminals instantly all over the world. So you can trade, you know, 100,000 pounds of pork bellies without anything moving, and it's priced instantly.

And there are a million people trying to figure out what the accurate price is for those pork bellies. But for some reason, humans don't have that, right? It's you get a job or you don't. And specifically, there have been women who applied to Lambda School. We get to the negotiation stage, and they say, you know, I have always been paid x. And we have to say, you're worth more than 2x.

So we're going to pay you what we actually think market is. And it turns out they've just always been underpaid, and they didn't know to ask for more. And I think that happens all the time. All the time. Well, you don't, because the thing is, when you start out, you're just applying for jobs, right? And you take what you can get.

And then, like you mentioned before, many of these, you know, quote, great jobs are never advertised, right? And so you anchor in this weird way that until you know people who make 400 grand a year, you're just like, well, the job says 75 grand a year. And that's awesome, too. Like, you know, if you're making 35, 75 is fucking killing it, right?

But then you're just like, oh, there's probably like some ceiling at like 100 something. And you're like, the answer is actually no. It just keeps going. But companies are incentivized to not publish that as well. No, it's, yeah, it's a, and that's the funny thing when you get to Silicon Valley and you see, like, there is a desperation around top talent.

And there are people commanding, you know, million dollar salaries, and the companies will happily pay it. Obviously, that's not an entry level salary, but, and there are people in the Midwest who are capable of being paid six figures in the Midwest that are making 20 in the Midwest. And that's crazy to me.

Like, that's the problem we're really out to solve, is why is there no mechanism to help people realize their full potential, both in economic standpoint and a non-economic standpoint? And why is there no, like, there's nowhere near an efficient marketplace for capital. No, nowhere close.

And that's crazy because if you look at GDP and spending and like where we can make the most improvement as far as efficiency goes, human capital is the most unoptimized asset class we've ever had. Yeah. And that's insane. Well, especially in the States too, where people aren't working in factories for the most part. Right, right.

So, aside from the tech jobs that you offer right now, what other opportunities do you see as like really great for arbitrage in that way? So right now we're hiring an economist to help us make sense of all that. But some of it you don't have to be an economist to see. You know, you can talk or download data from the U. S.

Department of Labor and see like how many people are applying for the jobs and how many jobs are out there. And there are some that have drastic, like three to one shortages that pay really well and there just aren't enough people. So nursing is one of them.

Every nursing school is at capacity because they have some, so there's something called the 90-10 rule, which says that only 90% of your money as a school can come from federal funds. The other 10% has to come through people paying tuition or private sources somehow. And that is actually the thing that drives the education system in the United States, that 10%, finding that 10%.

So every school is just desperately trying to find that 10% and however big that 10% is, they can blow the rest out with federal funds all day. So nursing schools, for example, there's a huge shortage of nurses. Boomers are getting old. Millennials aren't going into medicine. But nursing schools are capped because they can't find that 10%.

And so it's like that drives massive labor shortages across the entire economy. And that's crazy, right? That's just a market inefficiency. So we're not working on it right right now, but don't be surprised if you hear by the end of this year an announcement that Lambda Nursing is going live and we're launching a nursing school. So we look at it backwards from a labor market perspective.

And we're starting out with where are the shortages in labor markets and let's fill those gaps. And it turns out some of those gaps are 5 million people at a time. And that's a huge inefficiency. And if we can be a toll road that takes a very small toll to get you there, it's an enormous company. So, yeah. I think so too. So, okay.

I'm curious about then how you end up modeling that risk if the program, I imagine the nursing program might be a little bit longer than nine months. You're gonna have to give people, I imagine, like you're talking about testing out these living stipends, stuff like that. How do you start modeling that risk?

In the beginning, you make good guesses and you put it on a spreadsheet and you give yourself a margin of error. You lose some, yeah. Yeah. I mean, it looks like any other fintech industry where you start out saying, all right, we're gonna make some loans. We don't really know how it's gonna work out. We're gonna learn from that. And over time, we'll have a really predictive model.

We're getting better on the just income share agreement for education side for software engineering, right? We're not all the way there, but we to some degree can predict what the returns will be given the macroeconomic environment staying the same. Okay. So you kind of just have to like create terms that make sense and figure it out as you go.

And then when we talk about a moat, over time, you can better predict what repayment will be. You can better predict how much money you're going to make. You can write a tighter model. If you can write a tighter model, you can bring down the cost of capital. You can bring down your costs or you can increase the services that students get.

There's just a fundamental advantage to having done that before. And now we've got a couple years headstart on everybody else and we can pretty act, I mean, not with 100% accuracy, but we have a pretty good sense of how successful a student will be by the time they're starting or a couple months in. And we're hiring teams that are going to focus on just that.

How can we shorten that feedback loop so that we can determine very quickly how successful people will be? Can you kind of quantify someone's work ethic or grit? No, but they all along the way will spit off data that you can use to try to approach that. So the numbers are an output, not an input. But I mean, similarly to a startup, right?

Like you can't quantify the grit of founders, but you can look at what they're doing and the results of that, you could retroactively say, yeah, that looks gritty.

And if you get enough data points, machine learning is actually, like that's one of the places where AI makes the most sense is saying, let's take all of this data and let's figure out a model that maybe humans couldn't put together, but computers can figure it out. And pretty soon you can underwrite the likelihood that a person will be a successful software engineer.

a year before they've paid a dollar. And then that changes everything. Someone asked this question, so I want to credit them somewhere. Oh, no, I know who it was. David Kofied Wind basically asks, Imagine a market dynamic where it's mostly white dudes getting hired for software engineering jobs.

Is it possible that your model could learn in the wrong way and say, only select white dudes for Lambda School? So, it could if that's what we're actually happening. That's not what's actually happening. The reality is, if we can make someone a strong software engineer, they're getting hired anywhere. But, I mean, there are ethical concerns that we have to be aware of, right?

When I used to work in lending, you have to be very cognizant of that in lending. Because, for example, if you use zip code and you say, look, the people from this zip code tend not to repay, zip code is very directly correlated with demographics, and there are ethical concerns that you have to be wise about. What we're seeing right now is actually the reverse to some degree.

So, obviously, it's not causation by any stretch of the imagination. We can tap into markets of completely untapped talent, because we're not charging anything. Folks who are brilliant just haven't had opportunity before. And so, we actually over-index to those types of communities.

So, I think as a school we're less than half white, which is not the traditional makeup of a code school by any stretch of the imagination. But that's not because we're intentionally skewing admissions that way. It's just because that's where a lot of untapped talent is. And we try to find and train that untapped talent. And companies are happy to have it. In fact, it's a huge need for companies.

We don't sell ourselves as a diversity solution, but it just so happens that our students who are great engineers are, generally speaking, more diverse than Stanford would be. Yeah, that makes sense. But great question. Yeah, no, it's really interesting. So, you guys now are remote, right? So, all the coursework happens livestream. Do you see a version where you become centralized?

I mean, my buddy, he worked at a college in Vermont that just went under, right? I imagine you can buy colleges at this point. Yeah. Do you see a world where you're like, I mean, probably with a nursing program you'll have to. You would have to buy a. .. Yeah, I mean, it changes the cost structure. So, the less we can be in person, the better.

We have some experiments that we're running where we're actually housing people in group housing together. So, they live and work in the same environment. They're still taught online, because we don't have to have the density of instructors in one place at one time. We just get students together. I mean, I've looked at, hey, can we just buy a summer camp and run Camp Lambda and have a bunch?

That would be awesome, right? Yeah, great. We just have to. .. Decentralized housing is much cheaper than centralized. So, students would have to be willing to build that into the cost. So, what I like to say is, you look at Amazon. Amazon, in the beginning, was saying, we're entirely online, we're going to be focused there.

But once that's nailed, then you start to play with other stuff. We'll probably be the same way. But the core of Lambda School for the foreseeable future is online. Whether students are in the same place or not. We actually have a monthly meetup in every major city in the US where students all get together in person. And that's working pretty well.

So, there may be more of that, especially as we have more density. But the educational experience will probably always be online. Yeah, I mean, this is what I've heard from the guys at Zapier who were just saying, you basically have to be intentional and build that remote culture there. Very intentional.

Because if you don't, you could easily see a version where, oh, you weren't in class today, then you don't hear the thing, you didn't hear the tip. And I think you have to do that as a company, as a school. It's not something that happens on accident. We started out by figuring out, okay, here are all these people who could be watching Netflix right now.

So it actually goes back to our instructional design where, I mean, if I think back to my college classes, maybe 50% of people were paying attention, if I'm being optimistic. At least, I mean, this was, call it 2010, at least 50% of the class was on Facebook at any given time. Have you seen those photos from back in the day, when Facebook just started? I'm sure.

I don't think it's Photoshopped, but I imagine there's a real one out there somewhere where it's from the back of the class and the professor's talking and it's 70% of the screens are Facebook. Oh, yeah. So for better or worse, I actually think it's a secret advantage is that we can't rely on the crutch of just looking at somebody and seeing what they're doing.

So we have to use data and software and instructional design to make sure everybody's working on the right thing at the right time. So, I mean, yeah, it's a different world that you have to build for and you have to build it for it from first principles. It's like you can't just tack that on at the end. Oh, by the way, we're online. That does not work. Well, most MOOCs are, yeah, disasters.

Correct. It's like 10% or something. Yeah, of the good ones. Yeah, the good ones. Yeah, yeah, yeah. It's crazy. So Dave Dawson asked several good questions. He says, you appear to be on the successful path now.

We'll just take that for granted. Sure, yeah. Was there a point early on in Lambda School when you wanted to stop? There was never a point I wanted to stop. I mean, if you paid me minimum wage to do this forever, I would do this forever for minimum wage. Maybe I'm just a sadist or a masochist or something. Yeah, yeah, yeah. I might have to move back to Utah.

Yeah. But there were definitely times when it was just like, this is not going to work and we're screwed. I mean, in the beginning, it was like all those other schools were right. When we started, everybody said, A, you can't teach people effectively online. B, you can't teach people effectively without skin in the game. They have to put something up.

C, people aren't going to get jobs if they don't have a network. You can't accept the categories of people that you're accepting and have them be successful software engineers. Which, looking back, is a ridiculous thing to say. Yeah. But everybody believed that. The entire code bootcamp industry believed that online was not very effective. Because they were all like, we have an in-person class.

Yeah, let's throw it online. It didn't work? Well, clearly, that's fundamentally broken. Yeah. Everybody who had ever tried a free upfront thing didn't use any sort of filtering other than a paper resume. And people would show up on day one and they wouldn't show up on day two and they would say, oh, this clearly isn't working.

So, yeah, there were a whole lot of times when we said, maybe they were right. That was the real reaction. We were wrong this whole time. And we're out here saying, hey, you guys are all old school. You're all doing it the wrong way. We're going to do it over here. Well, maybe there's a reason that hundreds of years of education have worked this way.

But really, I think what happens is we don't have another option. We have to figure it out or we die. And that's a very powerful motivator. Yeah. Not getting a real job. Yeah. Have you ever completed an online course before? I have not.

Right. Okay. And, in fact, we were talking about the book. The book was available as an online download. Yeah. And one of the things that made me want to build in this model, and I sold the book for $100. Right. It was not cheap.

No. 50% of the people that bought the book ever downloaded it even. So, between looking at that and looking at MOOCs, it was like, has anybody ever figured out how to make education actually successful? Yeah. Or are we all just opening the top of the funnel so wide that some people are going to fall out the bottom?

And that's become my thesis, is that there is some percentage of society who are autodidacts, and they just have a ridiculous advantage over everybody else. And so, part of Lambda School is, how can we help the other 98% learn how to be autodidactic, how to see a problem, approach it, figure out a solution? So, we approached instructional design with no assumptions.

And I think every school ever has looked at everything and said, okay, well, here are the successful students. So, our job is just to weed everybody else out. Yeah. Why are the other students unsuccessful? Is that because they suck, or is that because you suck? Yeah. And we found that it's really just because you suck most of the time. And it's really easy for schools to just look the other way.

Huh. I have been wondering, I'm doing a Duolingo right now. Uh-huh. And I've been curious about, I mean, it's cool, but it's very open. Like, you can just choose where you want to go. They, like, motivate you a little bit by keeping a streak up. But I'm actually a little surprised that people, if people finish it, because I'm doing it every day.

I think if you guess what their completion numbers were, you'd be right. Yeah. I think about, you know, when I went to college and I had a class and I showed up and it was a Shakespeare class, I think about the work that I put in in that class and then the work that I put in outside of that class.

There's no way in hell I put in as much work studying Shakespeare on my own as I would in the four walls of a university. But I don't think that's because there was a physical campus with a professor wearing a tweed jacket necessarily. That's just because there, there was social pressure, there was instructional design, there were external mechanisms that forced you to put in the work. Yeah.

So, we had to, like, that's what we built into Lambda School. But you also have to make it fun. Totally. You have to motivate in that way. Totally. It's why I learned to program, it's why I learned to video edit, it's why I learned everything on the side. Because you had a clear goal, like, hey, I want to build this thing. And it's enjoyable to build the thing you want to build.

So, you look at, as an example, computer science programs, right? They have ridiculous dropout. Yeah. And they're proud of that. But in my opinion, it's because they start, like, writing Java and start writing C, and you have to go semesters before you get to a point where you can write any code that you can see or touch or actually play with.

And so, like, yes, you're getting the fundamentals, but Lambda School works the other way. So, you have a site that you can play with the first day. And it's not, you know, you don't understand the fundamentals of programming. It's crappy HTML and crappy CSS. Yeah. But you can see it, you can touch it, you can play with it.

And I think there are a lot of people, if not the majority of people, that learn that way. And they're the people who aren't going to become researchers, and that's okay. And just because you start at that point doesn't mean you can't drill down until you're doing the fundamentals. Like, you do need to know how to write C to be a good engineer. You do need to know how memory management works.

But maybe let's not start with memory management as, like, an entry-level point to software engineering. Yeah. Now, I did a year of CS in even high school. And it was just like, what are we doing this for? Right. What is the point of this? Right.

And there are a few people that are interested by that enough that they can carry on, but that's not enough people to build the world of software that we need. No. So, yeah. Yeah. So Dave asked another question that I want to cover, and that is, what keeps you up at night now? So we agreed as a team to no longer share the number of students that we have enrolled.

But it is not a small number, and it is growing at an insane pace. Yeah. We'll soon be measuring Lamb School's scale by percentage of the overall number of students learning to program every year, to give you some context. And being able to support that kind of scale effectively is what keeps me up at night. Mostly, specifically, hiring.

Mostly hiring executives right now who can build out 100, 150-person teams beneath them. Those people are difficult to find, and it's a very important decision. And we need like five of them yesterday. And then on the individual contributor side, we're probably. .. We'd need to hire like 100 people very quickly. And that is hard. But that would be remote, right?

Those jobs would. .. Most of it would be remote, correct. So, if you're looking for a job. Yeah. Oh, please. I think we're hiring for like 50 positions right now. Lambdaschool.

com slash careers. Please, please, please. All right. So, I want to talk about two other topics. So, one. .. I actually really like this one. Deo Calliowo asks, I've made remarks I do not agree with.

That's a quote from your Twitter bio. Yeah, you're prolific on Twitter, if people don't follow you. What is that one remark you wish you didn't have to disagree with? One remark that I. .. So, I think what he's trying to get you to say is what is something that you may have had to say or go back on in a perhaps like politically correct or like environmentally correct way?

There are a lot of layers to that question. Yeah. That's a tricky one. So. .. Or maybe even a core belief where you're just like, oh, maybe I'm just wrong here. So, the one that I go back and forth on the most is as a company being remote versus in person and the trade-offs of that. So, we bring people together a lot and I see the advantages of that.

And a lot of our executive team will probably end up being in person. And so, it's. .. I would say that I wish that remote work were at this incredible place where there's no trade-off. And I think that's something that everybody wants to believe and some people do believe.

But until you're kind of in the CEO or executive role trying to bring a company together, you don't see some of the trade-offs. Yeah. I mean, I would love to be able to move anywhere and not pay what I pay for rent and by extension not pay everybody else, but I have to pay them so that they can pay rent. Yeah. But I still think. .. And a lot of our students come in wanting to be remote.

A, I don't think remote work is built into enough companies yet where I would be comfortable telling somebody that I love that they should start their career as a remote junior software engineer. B, I think we're still figuring out what the right dynamic is of in-person versus remote, like as a tech industry, what the trade-offs are and what the ideal way to do that is.

My first company was entirely remote and that's really hard. When you're trying to come together and create something but nobody's in the same spot, they're just trade-offs. That said, all of our instructors are remote, all of our career coaches are remote and all of our students are remote and because we've built around that or we've built into that, it doesn't matter.

But I think the two things that are most. .. like my most controversial beliefs maybe or most. ..

like seemingly like don't seem to jive with each other is that I think the best high-growth companies are still going to be built in Silicon Valley for right now or at least they'll having an executive team in Silicon Valley but also I believe the best schools are remote and I don't think that's a contradiction though it certainly feels like one mm-hmm yeah yeah that's a good yeah just think about yeah no I was listening to Michael Seibel talk yesterday and he said he's had his mind changed about remote companies given the success of you know GitLab Zapier type companies right but the way he puts it now is that it has to be one of your like core things one of your like core innovations and if you're thinking like maybe we have the energy or the insight to innovate on a couple maybe three categories like are you willing for remote work to be one of them yeah I think that's exactly right you can only solve so many problems as a company and I mean I I've talked to the CEOs of both Zapier and GitLab in the past couple weeks and they think about that all the time yeah and the nice thing is the talent advantages that you have when you do that are enormous you know when Zapier is like yeah we've got like this guy in Ohio and this guy in Nebraska it's like man you know I'm hiring but but at the same time that the trade-offs are that if you're if you know you have an office in the financial district and you're hiring five executives there are a hundred companies that have been high growth that you know the funny thing is a lot of the people who they join a high-growth company they know how to grow it they figured it out now they're successful and they have less incentive to move than other people do yeah so like I think the pool of high-growth executive talent with 15 years of experience growing high-growth companies is still largely concentrated in San Francisco like if you need or call it Silicon Valley whatever if you if you need 50 people to do that it's really difficult to find 50 people in Ohio to do that if it's still difficult to find people anywhere but yeah if you've built that in like GitLab and Zapier have you know in other companies like InVision or whatever else they've chosen that as their path and they have to spend a whole lot of time thinking about and focusing on and optimizing for that maybe that's a trade-off where they have to spend less time hiring or less there's a less competitive hiring market I mean the instructors that we have now there's no way on earth we could have had a similar quality of instructor base in San Francisco they're just there's fundamentally is not so it's yes it's a trade-off yeah it's difficult it's a tricky one okay so the last thing I want to cover is I've heard you mentioned a couple interviews that the market is not very good at measuring product quality correct or something to that effect right yeah so I think what I usually say is specifically analysts so people who are and you know if you look at public companies or VCs or whoever else and another way to say this I think PG has said that product is or revenue is a very very trailing indicator of product right so I think and so I you know back when I had spare time I would play the stock market a lot okay and I think people just don't have a very good there's no way you can quantify product quality very well so people who are looking at things from a quantitative standpoint underestimate it every single time I mean I look at some of the classic companies like you know look at the YC companies the Airbnbs the stripe they all had competitors some of their competitors had a head start some of their competitors had more money and more market share at different times but there's a reason those companies win and become durable companies another you know Dropbox as an example well it's it's one of my favorite Steve Jobs videos I don't know if you've seen this one before but it's like a very hot burn on Microsoft and where he's just like listen they're good people the problem is they just have no taste yeah and so what I was curious about with you is like do you think you can teach taste in a school to because it's very much it's related to product it's related to listening to users it's all of that but there's something like more ethereal about it you know I think that the main thing is having thought about it a lot and then having seen it and having noticed it when you see it so for example we use slack as a school so we've got I could tell you how much we spend that would tell you how many students we have it's a non-trivial amount of money for slack and people say you know why don't you use you know competitors or you know just use IRC but like it's very very subtle the work that has been put into slack and slack has it's not perfect right but as a product you can just tell yeah and so it's a whole lot of the way I like to think about product is a whole lot of subtlety built up over time to the point where it becomes an advantage and if you build up a lot of those advantages over time it compounds to some degree and I think because it's difficult to measure and it's so subtle I mean if you for example if you'd like drive a Model S and then you go drive a similar cost Jaguar for example the Model S like the materials are worse the build is probably not as good like they're not as good at like assembling the pieces but just the experience of that car versus the other one it's not even close so Tesla's probably the canonical example of like product matters way more than analysts can measure mm-hmm cool so you just think expose students this over a long enough time frame I think you show people like the when I started to realize it is when I had a few product minded people like point out some of the subtle details and be like you really like you find yourself looking for one app or one piece of software or using something more often yeah and it takes somebody to sit down and point out like you know why you're doing that right it's because this is happening at this specific time in this specific way and you're like oh that that was very pleasant actually in retrospect and pointing that out and then beginning to look for it is when I think you start to notice the the key differences fair enough yeah I like being critical sometimes especially products all right man so if people want to sign up or learn more about lambda school where should they go yeah lambda school calm sweet and you're on Twitter at at Austin cool than me like the feminist author not like the city all right thanks for coming in probably thank you.