YC Fireside: Surbhi Sarna + Reshma Shetty and Jason Kelly - Founders of Ginkgo Bioworks

Hi, welcome Reshma and Jason and everybody on the call. Hi, my gosh, I am so excited to chat with the two of you, pioneers in the field of synthetic biology.

So to kick us off, the audience today is going to be a mix of people with a tech background and a bio background. Can you tell us a little bit about what Ginkgo does?

Sure, yeah, I can do it. Uh, yeah, so I'll say it from the tech lens and then from the bio lens. So, uh, from the tech lens, you can think of us kind of like Amazon Web Services, right? Big centralized facilities that can be accessed as a service so that you can bring your product to market more easily.

Right? In our case, instead of a giant data center like Amazon's, it's a highly automated lab here in Boston. Right? So about, you know, in this building we're in here, about 250,000 square feet of highly automated labs that you could, if you want to start a new company and not build out a bio lab, you could essentially leverage our infrastructure to do your cell engineering.

Okay, so that's the tech side. If you're a bio person and in biopharma, there are organizations called contract research organizations (CROs) where people outsource certain types of research. Traditionally, biopharmas outsource like an animal study or, uh, you know, making a small molecule, uh, chemistry to like WuXi or to Charles River.

It's kind of like work they don't want to do, basically. Like, you know, it's kind of like standardized work that it's just like, "I'd rather someone else did this." Our argument to these biopharma companies is because of our automation and scale, we can do things that they can't do in-house.

So they should actually outsource to us to get access to a scale that isn't available in their internal labs. So that's sort of the tech and the bio. But either way, the idea is outsourced services, a platform business model like you would see in a lot of tech companies to enable other people's products.

Fantastic, thank you. And what year did the two of you get started, and what's the current state of the company?

So we got started in 2008. Um, we were virtual for the first year. Um, and then, um, managed to open our first lab in 2009. Um, and bootstrap for several years with no outside funding whatsoever until actually our first outside money in was basically, yeah, our class of YC, but we've been bootstrapping the company for five years before that which is like buying equipment on eBay, like moving into the cheapest part of Boston, like building up, getting some guys from South Boston to put in some plumbing into an office space. It was, it was not, uh, it was not the, you know, a lot of biotech startups fancy. It's not to start a pickup.

Um, I serve as well actually now as we have a lot more capital, it did. Yeah, yeah, it fakes frugality into your culture from the get-go that is even 15 years later is still there. We still don't like to spend money. Yeah, scrappiness and resourcefulness. Such important lessons for all of the aspiring founders on the call today.

And so take us back. You know, a lot of folks who are wanting to start companies, one of the first things they do is they look for a co-founder. You know, and the two of you have had such a successful co-founder relationship for such a long time now. Tell us a little bit about how the two of you met and how did you guys know you wanted to work together?

So Ginkgo actually has five founders. Yeah, you only get two of the five on this one. Um, yeah, that's one of the reasons we work so well together—the first thing is we want to point out that there's five of us.

Um, and we all met at MIT, uh, so four of us were graduate students there, and then my PhD advisor is the fifth founder. And, uh, we actually showed up slightly different years at MIT, but all kind of fell in love with was with what was just getting going as a new academic discipline, synthetic biology—kind of how we all met and started working together.

Yeah, we'll talk about what's in bio in a minute, but I would say in terms of starting a company with your thesis advisor, so like why? Well, I see obviously sees a lot of companies are in the tech industry, where it's all just, you know, straight on undergrad like, you know, whatever boot up a website, do up an app, you know.

Um, I think for like these sorts of like hard technology or deep technology or real technology, as I would call it, companies frequently you're gonna have a, um, like a scientist PhD person, you know, I'm an advisor in the mix, right? Like the technology is coming out of a lab or something like that.

And one of the things I would advise folks to think about is, uh, can you get your thesis advisor to leave the university and join your company full-time? That is a true signal. Did you do that successfully?

Indeed, yeah, yeah. I mean, that's hard to do—to pull people out of academia like that. So any tips because a lot of my bio founders are facing this right now, actively facing this?

Yeah, I mean, my main view on it would be, I think it is hard, right? So hey, I think if you're like a venture of apples and you see that happen, it's actually really great, underappreciated signal of a company that's a big deal, right?

Because those are like, you know, it's a big deal to leave an academic spot. It's like, it's a big deal. Yeah, there's a real thing. Um, but, but if they don't, which is most common, the bigger issue is like not really a founder, you know, right?

So it's like a weird dynamic that happens in like the biopharma space where you have these people like, "I'm the founder of like 27 companies because I'm like such and such, you know, my professor," like that—it's not like it's not founder as like Y Combinator, by any stretch of the imagination.

Like, like, you know, unless they're leaving, you know, if you want to really build a company when the Y Combinator model like a Google scale company with, uh, with founder-led leadership, that that you don't want to waste that equity and also like moral authority on someone that's not joining the company full-time.

So it's great to have an advisor as you get something, but it's just, it's just a friend. Yeah, it's completely different. I can't tell you how many applications we get at the YC bio program where there's a professor that has 30% of the company, and then the founders asked me to get on the call with them with this Macimo, can say, "Well, can you negotiate them down? We don't want to," you know, I'm like, you know, you might not have graduated yet, so they troll whether it is very challenging.

But yeah, you're spending your whole, like if you're working full-time on a company and they're not, that's like just a very level of investment life energy, so, yeah, it's in their interest.

It's even in their interest, to be honest, because like again, I think YC, God bless you, you were all right really work. I mean remember we're, we're old, right? Like, like we started Ginkgo, you know, in 2008, okay? Right? And like there, there wasn't even good like founder, um, forward content on the internet. There was a blog called, uh, Venture Hacks that like, uh, what's his name? You know who now who ended up doing AngelList, like was writing. And that was like one oasis in the desert.

And the other one was like Paul's essays, and like we were like voraciously reading these things because everybody else we talked to was all like completely VC-centric advice, right? And, and so I think like the model that Y Combinator pioneered, a big part of it is understanding like the power of like founder-led companies where there's real ownership and like, and what then that lets it run.

Like how do you want— you want to get a Microsoft or Google? You can't just hire in like a professional CEO from the VC firm. Is that how you get Microsoft and Google's? Like it just doesn't. Yeah, right? Just admit it right?

So if you're a professor, you actually want that equity to be worth something—give it to your students, you know, right? And take a much smaller piece like that the award leave and join full time, right?

Like otherwise you're just holding back. Yeah, I couldn’t agree more with that. I am have been entangled in several of those very fun discussions. People are very short-term minded, right? Yeah, they're like, "Well, obviously the X percent is bigger than Y percent." You're like, "Yeah, but there's like eight follow-on effects to you making that decision, right?"

So, yeah, yeah, just so speaking of founder-led companies, how do you think that looks different for bio companies versus tech companies? We're sort of fighting this ingrained culture of very quickly replacing the founding team, right, with so-and-so, you know, professional CEOs or CEOs and that sort of thing?

Yeah, I think, um, biotech VCs historically have this kind of tradition of like finding a technology in a lab. You probably take the best students and post-docs from that lab and get them started, but then you pretty quickly bring in professional management and over them.

Um, and part of the reason they can do that is because like they're the first money in, they probably own like 30%, 40%, 50% of the company, and so they do have like, they're a ton of control. Right?

Right, and so, um, but I think if you can flip that model where like if you can bootstrap a little while, right, or, you know, get creative about your early funding and rely on non-diluted funding, that gives you a little bit more flex to like avoid that model and actually have the founders.

And then you have to kind of do the typical thing of like being on a very steep learning curve as a founder to kind of build the skills you need to run the company yourself, right? You don't get it by fiat, you get it because you earn it. But, um, but, uh, you know, uh, YC has been sort of helping to like move the needle on that.

Um, hasn't happened quite as quickly as it has attacked, but I think it is moving in that direction and yeah, I hope so. Yeah, um, two, two things of that, one general and one self-serving.

So, uh, you know, Ras and my point out like that bootstrapping thing, right? Like, so Ginkgo's, you know, the first 10 million or so dollars in a get-go was grants, right? We started the company in 2008, we were coming straight out of school. It's like we were the first YC biotech company. Now it's more common, and then, but like back when we were there, there was very few like, um, uh, straight out of grad school founders, and so we couldn't have raised Venture Capital we wanted to, right?

Right? The consequence 100 is like the reason we actually, by the time we raised money, we had already created a lot of that we've got a lot more leverage in those negotiations.

And so we were able to not have that situation where, well, in order to start this company, it's going to cost 10 million dollars. I'm not going to give you 10 million dollars for a small percentage of a brand new brand new company. It's too much money, right?

So it's really the starting costs of a biotech that are part of the problem, and I think it's no surprise that like YC came into its own right alongside like cloud computing infrastructure and internet because it dropped the cost of starting companies, right? And app stores and the whole thing, like all the costs for doing web fell, and so suddenly there wasn't a gatekeeper who had to give you 10 million dollars to start your internet company.

You could start it like, you know, on the first YC videos were like, what, what they give probably like 35 thousand or something like it was like, yeah. And so like that was part of why like you've even had a shot because otherwise the gatekeepers were like, "Well, no, you know, right? Like, I'm just not gonna allow it," and you needed the money to start an internet company.

So not a self-serving half, if you are starting a Zen bio company, I recommend you use Ginkgo's infrastructure, okay? It will make it much less expensive to launch the company.

Like, we're really trying to, I think this is one of the reasons you don't see founder-related biotech as much—it's just the upfront costs are too expensive. So everyone who has managed to pull that off has done it through some crazy scraping and blah, blah. The eBay and the, you know, like it's brutal, right?

It's just expensive to start a lot.

Yeah, and the last couple of batches it's felt very different for me funding companies with 500,000 each versus 125,000, you know. Of course it makes a difference if you're a tech company, but especially if you're in our space, that incremental increase means a lot, right?

Yeah, so going back to your fundraising journey a little bit, I love this founding story of Ginkgo of a bootstrapping finding YC, and then doing two sizable rounds in close succession to one another, right?

So first after bootstrapping for a while, how did you decide to join YC? What was the thought process there? And then what was it like fundraising after that point?

Sam Altman had wrote a blog post that was like, "I think YC should..." it's good, yeah, I'm gonna have buy some fun things that aren't software companies, okay?

And I probably just broke Sam, I was like, I didn't know him from Adam. I was like, "Oh, you know, thank you," like just like, I'm like Ginkgo is like two, you know, like we've been around for five years whenever we're based in Boston—we got like 20 people to laugh out here.

It wouldn't make sense for YC, but like thank you so much for just like being willing to, to like apply, like, like someone else to fund bio that isn't like trying to develop a therapeutic, right?

Like, you know, like just dance, it was like water in a desert, you know? Uh, and he was like, "Oh, you could do I— you know, like you could do, you could do it. Come out, come out, meet me," you know, right?

So like we went out and met Sam, and then after that I was like, yeah, we'll do it. Yeah, so that was it. That's how we got another one. It's like because that last one out and, yeah, that's awesome.

That's such a great thing for early founders to hear because I think sometimes when you put things like that out in the universe, like just a thank you, that's what it takes to unlock the power of serendipity, right? You just never know in the early days what conversation is going to lead to what outcome. It's pretty amazing.

Yeah, I agree with that. The other thing I would say is like, um, especially when it's like things you just like believe it. Like I think a lot of what worked over the years for us has been like, you know, the like back where at MIT it was like the beginnings of this field of synthetic biology which you can think of a little bit like DNA is digital code.

And why don't we bring in some of like the theories of like, you know, computer science and engineering more directly into biology rather than starting with the biology, right? Like start with the code and then see what can apply to the biology rather than understand how a cell works and work backwards, right?

And so, so we, you know, we just believe, you know, like Tom and Drew, like Andrew Randy was my boss, like they really like inspired us to care about this and then like that a lot of Ginkgo success has been just like making authentic bats on that like, yeah, and people we hired like in terms of like, like decisions, but business model the company—like investors we brought in—like it was really like if you really authentically believe in it, like just don't be afraid like, like it, you know, I think it helps you take risks, yeah?

Because you're like, "Oh, I'm gonna do this because I believe it's the right thing to do and you know, it's the path forward." And so your risk tolerance is sort of different because you're just like, "Well, this is what I believe, and so I'm gonna go after that."

And you know, whereas if you were trying to like build a financial model to justify the decision, you like might never know. Yeah, because I mean there's so many hurdles as an entrepreneur that unless you genuinely, authentically believe in what you're doing, you're gonna stop at some point, right?

Like believing what you're doing. Yeah, absolutely. Along the way, we're like, we're like, "Oh, well, we couldn't live with ourselves if we didn't, like this is what I'm meant to be doing." A lot of risk, right?

Like we had, remember like the other thing that was brutal making the jump to taking better money, it was like, I mean, we are just like scraped for a long time, right?

So there was a lot of sweat equity in this thing and then it was kind of like we take all this money and now you're making facts, we're like if it's wrong, you're like you're so hard over your skis, it's like, "Oh my gosh," you know, the whole thing, like man, I'm just like, "Man, you know, the last six years were like like, you know, like a lot."

You know, if you're applying for grants, you know, if you're gonna get the money, you're like trying to keep employees, they don't really want to stay, you know, like it's tough, right? Like that.

So, so we really felt like we had like a lot on the line, you know? And I agree with words, like without like really feeling like you're doing it for some other reason, you never would have made it— you would have been too risk-averse.

Yeah, so what did it feel like to make that transition from going from being bootstrapped to then raising oversubscribed rounds, and you know, two rounds in one year, right?

Or very close together? Yeah, I just did the fundraising arrangement of the money spending. So what was it like? Uh, like the change about that culture? No, what was went through was like, yeah, we had bootstrapped for so long, right?

So the employees would join us, like they just kind of engine on some level, right? Like, like on some level just bought into like, "Aliat let's give this thing a whirl, too."

Um, and then like, we raised all this money, and all of a sudden there's this opportunity to kind of build and invest in things that like we just didn't have the cash to do so previously, right?

And so it was like, we were like talked about like, "Oh, like we were 20 people. Okay, we're gonna be 40 people by the end of the year." And like they were people were like, "No freaking way. Like we don't even know how to scale."

Like we, like we've been hiring like one person a year, you know, one person, one person, one person a year. I love it, yeah. Like we’d been just growing so organically and slowly that people like didn't think we could switch into like a faster pace of doing things, right?

They were just like, "It's possible?" Like, yeah, right? And so like we're afraid of the cultural change? Yeah, or yeah, oh yeah, totally, right?

Like, what is this gonna do to us? Like what, how are we gonna be a different company and whatnot? And like, but what was cool is for all the people who were there at that time, they saw this, like, "I thought this thing was impossible," but then we went and did it.

And so that like completely opened their minds to like the possibilities of like tackling the impossible, right? Because like, again, at some point you have to like kind of believe like, "Hey, I can build this muscle; I can like leap off this cliff and build the plane on the way down," right?

Um, and we will start flying. And so that like going from like, you know, having a scientist or an engineer declare something impossible, and then the U.S. organization pull it off, and then you're like, "Oh, wow! I like I was wrong about that."

And so then all of a sudden those are, you know, some of the folks who are still here today who are like willing to make the biggest leaps because they went through this incredible transformation of like thinking we couldn't do something, and then we did it, right?

Yeah, and I think there's an extra hard when it comes to like, um, like for, again, I'll say for like deep deck or real tech, you know. And what I mean by this is like I love that, yeah, like really—okay, you know, like you're like a real company, you build actual things to Silicon Valley.

What like I would argue that like—and this is starting to change, I think some of the stuff—but like, you know, I would say I'm stupid, but there was a window where like the bulk of what Silicon Valley was doing was taking market risk, right?

Like real grown adults ride scooters, right? Work at risk, okay? Can you build a scooter network run by yourself? Of course! Spend the money, hire the engineers, get the scooters. There's no technical—it's not Intel, okay?

Right! Like, you know, ride them: they will lose them, they will throw them into the ocean—all marketers, right? Whereas, oh, or you're going to develop an Alzheimer's drug, zero market risk, all technical risk, right? Okay? Right?

Right? Like you might try your best, you're not making it, and you just might fail because it is scientific and technical risk—that is real tech, okay? Like real technology. It has risk, okay, right?

Like you're calling yourself tech because you use software, but it's no, there's no risk embedded in it, okay? You're just you're actually just a marketer back to product developer. And that became a culture of Silicon Valley.

And so, you know, I would argue that all these companies that are building real tech, they have to—they have to have good scientists and engineers. You know what makes a good scientist and engineer? Raging skeptics, raging. Okay?

Right? And so you have this, which is not the case of a product, right? Great property. They're like another visionaries, the dreamers, right?

But that is not, not what makes a good drug developer, okay? Right? Like you talk developers, big time skeptic and so that actually runs in.

So how do you balance this challenge in terms of like building the culture at Ginkgo? Like having that and having that dreamer side and having that business side? And now you guys are publicly traded, so there's the street side of it, you know?

Yeah, no, I think really hard because you're basically trying to establish an unstable equilibrium where you want to maintain that skepticism because that's how you do rigorous, like top shelf science and engineering, but you also want to have ambition and to have that dream.

Because that's how you achieve more than you technically think is possible, right? And so trying to maintain that unsuitable unstable equilibrium between those two very stable states is, yeah!

And what it requires is energy, like you need to constantly be protecting that and like—I gave one good example earlier—really high caliber skeptical scientists and engineers who have been through the experience of doing something that they personally thought was technically unlikely and then having it be successful flips a switch.

So that's what amazing—that's one of the tricks. Another one is mission. So do they get less and less skeptical as they keep beating their own skepticism? What does that evolution look like?

They just get more excited to work on hard things. They get better taste. They get better taste. So, so so because the trick is like you don't want to lose your skepticism. That's how you end up with junk science and junk, you know, like all that, that all the storage you don't want to hear, right?

Like so, so the—I hear them, right? Okay, like you want better taste, right? Okay, so that's what they're building, right?

I would argue, yeah, okay. So you only—and you only do it by being in places that are actually taking tasteful risk so you see Darkness, feel what it looks like, okay? But you can easily be in a place that takes no risk, and you could easily in a place that takes tasteless risk, okay?

Right, right into those companies. So like that those are your—you that's your—those are your two easy ones. And the harder one is building of having good taste when it comes to that kind of technical risk, okay?

So it sounds like you guys had an amazing culture going, sort of early on co-founders that really believed in each other and an influx of cash, but something else you had was customers, right?

And a lot of the early stage companies on the phone right now, that's something that they're struggling with. That's their day-to-day. How did you find your earliest customers? How do they— how did you convince them to take a risk on you?

That is a good question. Uh, yeah. Yeah, okay.

Um, I think one thing was not, um, not being picky, you know, right? Like so, so like we, you know, we went out and, um and I like, I think this is true across like, again I'll generalize us into like real tech, right?

Like, you know, the boom aerospace, right? Like they were a batch or two after us, yeah, they did some deal with like Richard Branson, like some deal, right? Like, you know, like something, right?

Something it's kind of like show something, right? Like get somebody to bite because investors who are are going to have a hard time, which is I think just this is a function of real technology, there will not be an investor who understands your technology better than you.

So they're going to look for some other evidence and I think customers is the best one, but there's other things you can pull off too. And for us, like we went to industries that were less biotech industries—we went into fragrances, right?

You know, and it was because we could get customers, and fragrances like we're fundamentally asking a company to outsource their research to us, right?

Fragrance industry, they weren't good at biotech, they were good at chemistry, but they weren't good at biotech, and so we could get customers there. Now we knew the budgets were way bigger in biopharma, and that's where like the majority of our new, you know, more of our new deals are coming from now.

We never would have been able to get a biopharma customer in 2014, we’re doing YC, zero chance. Like we weren't good enough yet, right? But we could bootstrap, you know, we can start to spin the flywheel in some of these other industries starting with fragrances and animal feed and then now, you know, now we walk into the best biopharma labs in the country and like they see leverage from what we have relevant to what they have.

But that, you know, that took 10 years, you know? So we started not being by not looking for the hardest customers to get, okay?

So, so first look for the right customers and don't be picky. Even the fragments. Easy, yes, the easiest, right?

Because it’s a chair, right? Like it's a journey. This is an important point because I think some—I don't know if I should do this deal because because the terms or there's that I'm like your failure mode is not like doing the deal and the company's stealing your IP—that's what people are usually afraid of.

I'm like is that nobody will buy what you are making? Yes, that is right. Nobody actually cares to spend money on what you do, yeah?

So I think there is something where sometimes people are a little too like paranoid or picky about their first deal, um, because they worry that they're gonna get a giveaway.

Yeah, they'll look bad. Also, that's another one, right? Like I love these, like I don't realize that they're like, "I'm so friends with these people," right?

Like, like they made like an incredible bet on us, right? But like they are the—they aren't like the famous farm companies, right? So, like if you were just thinking like, "What's the thing that looks the best?" right?

To an investor, it wouldn't have been that, but it was like a deal we could get with good people who were smart, you know? Like, but, and we added, we had something to offer, right?

And it worked, right? And so I think that's the other thing is like people don't think about the little steps you can take, okay?

They think about, "Oh I gotta build like the prototype, boom, airplane." Not true, actually the first thing you could do is just get a deal—like just something—like there's anything to talk about, right?

Like, you know, and then later you'll raise money and you'll build the prototype and then you'll do the next thing and like so you gotta lever up.

I completely agree, I see, um, founders shoot themselves in the foot all the time when they're too focused on brand names, brand name customers, brand name investors—like no, just start somewhere, right?

Yeah, so one, once you do it was embarrassingly scrappy. We, and this reflects on us to this day, we still like don’t get like, you know, we have a giant, like a chip like the size of a boulder on our shoulders, uh, you know, at all times, but like, like that, you know, it's like we don't know respect, you know, right?

Like part of the reason like, you know, like the science, the engineering here is cool, but like we did it all in a weird way, right?

We didn't go straight to the to like the highest profile names and the highest and so a lot of people still give us crap about it, they still give you crap about it?

All right, well, so what was it? What was that transition like? Yeah, yeah. I feel like I just like, yeah, maybe offline we’re really good, you know what? We live to serve, right?

Like we just want to serve all these industries, you know, anyway we get there.

Yeah, absolutely! And what did it feel like to take this company that you had bootstrapped, raised money for, found a team, public? You know, a lot of founders dream of that moment, and then afterwards can be less dreamy. But anyway, what was it like for you?

What was, um, honestly, like I wasn't sure like what to expect going into it, like, you know? Um, but, uh, it was pretty cool. Like, I think it was, it was pretty cool.

Like, um, like we brought the whole company out to like the New York Stock Exchange and we, you know, they were like, you know, friends who came out and like, let's get those first customers who were there.

Yeah, oh, that's amazing that you brought your first customers. Yeah, like advisors who'd been with us for years, yeah, a lot of kids and families, you know, um, and so like, yeah, like all kind of coming together as a community and just like celebrating like, you know, how far we come was like actually it's pretty amazing.

And definitely recommend the New York Stock Exchange if you're going to go public. Yeah, that's cool! It's good, Palm!

Yeah, it's like it's good a lot of history. It was like, I think it was a good, um, you don't step back that often often. I think it's realistic, yeah?

Because you're just going on and going on the next thing, focus on the next problem, and so to take a moment in time and like kind of celebrate collectively about like how far we'd all come together, it was like, yeah, that was good.

Yeah, it must have been an incredible moment, especially because you included everybody from sort of every facet of the early days, right?

Okay, it was a lot—it was great! Um, yeah! Yeah! And then like, you know, be public, I like it. You know, I think one of the things we've always faced at Ginkgo is like, again, because you didn't come out of traditional biotech world, like like those either didn't know about us or a lot of people didn't know about us is the short answer, and you're running a services business, like it sure helps that people know you exist, you know?

Right? And so, so your profile just goes way, way up, right? Like you just—way more people know about you. It's really hugely helpful for sales and everything else, and we've seen that.

Um, so like, I, you know, I think it's like generally like really healthy for the business, um, but yeah, it's just a lot more noise but it's healthy, fantastic, fantastic.

So before we open the floor to questions, I thought that we would spend some time just talking about the field of synthetic biology more broadly and what you think the future of synthetic biology is, kind of what you're most excited about.

Um, yeah, yeah, great question! I'll be honest, I don't get this question very often. I can say, I'll say what it is while you think about the future. Okay, okay, all right?

So the, okay, so like what is synthetic biology? This is another one where, okay, um, so like the core idea, again, speaking like attack antibiotics that DNA is digital code.

Okay, right, and you can read it with DNA sequencing like genomics, Human Genome Project, all that. And then importantly, you can write it with DNA synthesis, DNA printing, which like again to a non-like biologist, you're like, "Yeah! In your computer hit print, and then like a custom piece of DNA comes out!"

I mean like it's amazing, right? Like that is like just amazing and like it is totally lost on people that most objects around you do not run on code, okay?

Right? Like the chair you're sitting in does not run on code, right? The only two things in that room that running on code is the computer in front of you and you, okay?

Right? Like it is wild that inside of every cell how their nature is it's like invented the same mechanism to information transfer with high fidelity that we did, right?

Like it didn't go analog, it went digital like that's, that's wild, right? And so the, but the difference is with these cells we didn't invent them, so like we don't really understand how they work at a level of each individual piece.

But boy, we can read and write, and we can measure them. And so the whole theory of synthetic biology was you can read and write code and you have something that'll run it. That's programming, so like, okay, like can you bring in the theory of program— you know, can you bring in some of these engineering theories into what predict what really was a field started by the biologists? And the answer to that is like some things and some things not.

So kind of curious like, you know, what the rate, yeah, that's the idea—that's the idea. So, it's fundamentally a tools revolution, right? It isn't some people get confused, they think it's like applying bio outside of biopharma, you know, it's like— you know, like making renewable nylon is in bio? No! Actually, that's industrial biotechnology.

In fact, that's been going on for 40 years, right? Like the—the making enzymes for laundry detergent, that that got started at the dawn of biotechnology, Genentech started working on that actually, right?

Like, okay, not, not like, no! It is a tools revolution that makes it easier to to apply biotechnology across all markets—that's what symbio is.

Um, it's pretty amazing how far this will come, right? Like I mean like early on we would always talk about sequencing because it was the obvious one that was getting way, way better every year, and then we started talking about synthesis, um, like DNA synthesis.

So writing code that's obviously gone nurse, but now it's like every part of the cycle has gotten better or so Christopher cast mumbly made it way easier to edit genomes, right? Which was a bottleneck? But now we can, you know, for most organisms you can just go in and add genome now, right?

Which was like not a given when we started, right, amazing. And then, okay, now I can actually just go um use AIML to like design proteins, like not a given when we got started, right?

Um, the fact that our measurement technologies right between next-gen sequencing and and mass spectrometry, like I can basically know exactly what's happening with my, with my, um library design like I don't know tools become a huge way and now like like pooled approaches for for designing biological systems are now, I'm not sure, like designing and testing like a thousand designs.

I get to do like 10,000 designs, a hundred thousand designs, a million designs, right? At a time, like, yeah, that's great! It's come a long way.

And so what's cool about the tools getting so much better is that the envelope of applications that are actually like realistic to go after is like massively, and so that's like why we got into this in the first place, right?

There was no like one application that motivated us, it was like, oh man, this guy's the limit. If the tools got good enough and like the tools are actually going to get them good enough, so it's pretty cool.

Yeah, and the other thing I would say is then you start to like, because you can start generating a lot more data and understanding, because remember we don't understand, we didn't design these cells, so the more things you get to try the more you're like theory of programming improves, right?

Right? Like remember like the book like the art of computer science and stuff, like you know like there’s like theory, right? You know, it's not just about like the compilers and the debuggers that like let you put the code in and let you test how your code performs, which we have a lot of here, you know, in our physical infrastructure.

It's also like how good are you at writing a code, right? Like that is getting exciting because like you've always been anemic in the data we had to teach us how to get better at writing the code and at least here again.

Go that is now training and by the way, for any of our customers who would like to access our infrastructure as a service, also available! Huge scale learning which you can then use to train your models and all that stuff.

Like it's really, it's real neat sounds valuable, absolutely. So last question for me before we open it up to the audience is, any parting advice for founders in the field who are just getting started?

I'd say the typical advice I always give folks is like don’t underestimate your ability to learn, right? I think sometimes, um, particularly for bio companies, you might start with technical co-founders, right?

Um, but like literally all of your training up until that point has been how to go into a new area and learn. It turns out that skill set is applicable even outside of technology and science, right?

You can go in and learn about how HR stuff works. You can go in and learn about how to, you know, negotiate contracts. You can go in and learn how to do sales. You can go in and learn about how to, you know, run your accounting and finance teams, right?

Like, and so understanding that like that you have a tremendous ability to learn and grow as long as you're willing to put in the energy and the effort to climb those learning curves is I think a really important thing for all family appreciating.

Yeah, absolutely. Don't build a lab. Don't do it. It's not worth it! Yeah, the cloud!

Yeah, all right, fantastic! And yeah, erase my—I completely agree, it's a big reason why, uh, I wrote my book without a doubt, because you have to be without a doubt that what you're working on is the thing you're most passionate about.

But also, you have to believe in your own ability to learn, to overcome other people's doubt, you know, your own doubt. So I absolutely love that, and the thing about not starting a lab, okay?

So, yeah, it's part of it! Um, okay, let's open the floor to questions. I love this one to get us started—in Jason's tweet he said he'd be talking about dragons. Tell us about dragons!

I did not see this! Yeah, I kind of promoted... okay [Laughter] okay, right. So that's just a start. I'll just point out they're clearly biological, so my three-year-old and six-year-old boys would love it, that's for sure! Correct, right, exactly.

All right, now we're talking! Okay, now, what a large review here—like where does this stuff go in the long run, right? Like if we really are like the long view of synthetic biology is to kind of get on a curve like our co-founder Tom Knight, right?

Like he's in his 70s, right? Like he started MIT, the faculty in like 1972—the refrigerator-sized mini-computer era of computer. Yeah, I called it like mainframes, punch cards, maybe computer architect—is that okay, right?

And so he saw computers go from being something that, number one, you had to be an electrical engineer to even know how to program. Number two, you had to be like a wizard, right? Like just like a, like a complete genius to now like you can go on your, your 10-year-old can go on an iPad or go on Scratch and write code, right?

So why can't this happen in biology? Like it's gonna happen, right? Like it is going, it is going to happen in biology. Like there is no—there's not like a physical barrier in the way from this happening in biology.

It will ultimately get low cost. It will ultimately distribute your kids will ultimately get to design your garden, okay? And like that, that's a really to me like, like that's a beautiful future, right?

Like, like there’s a—like I mean artisan designers, like when they get their hands on a substrate just are incredible to watch, and like biology is the most beautiful, right?

So, so yeah, I, I definitely agree! Okay, one for Arrangement since it's Women's History Month. Any advice you have for women in bio who want to start companies?

Yeah, it's a good question. Um, I don't know that I, I do actually have specific and for women, because I think, you know, being a founder is being a founder, and what it takes to succeed is the same across the board.

Um, you know, you might, you might face some incremental challenges along the way—like let's be real about that—but I also think that it's important to not let that occupy too much of your head space, right?

I try—I try well. I consider really important to think about, how do I like give back and like and lift up like other women in the field?

Um, I also try not to spend too much time thinking about that, like, for myself because I think it just takes you to a negative place and you can't really afford that, um, as a founder.

And so kind of staying focused on the future and staying focused on maintaining that learning mindset is I think kind of kind of critical, like everybody has their moments of doubt and negativity.

But the extent you can just kind of stay focused on what you want to build, yeah, Reshma, I totally agree. I mean, one problem with unconscious bias is that the people receiving it—they are always, you know, part of their brain might always be thinking, "Is it happening right now?"

And they'll expend the energy thinking, "Is it happening right now?" But being a founder is so ridiculously hard. You don't have the mental energy, you know, and you don’t need everyone to believe in what you're doing.

You don't need everyone to believe in you. You just need a few, you know? So as much as possible, and of course it’s hard, and of course it should be acknowledged, but not letting it occupy that mind space, like you say, I think is so important.

You know there's just so much other stuff to do.

Um, okay. I like this next one because it's a little bit inducing controversial, but not in a—anyway, so it is, what do you think is the difference between the biotech ecosystem in Boston and Silicon Valley?

Uh, I guess on the Venture side maybe that’s there or maybe just the biotech in general. I mean, I think, um, when it comes to the companies, um, I think there's great companies in both places.

Uh, I think Boston has really crazy, uh, drug development, like, like in terms of like the big biopharmas moving their research hubs, it's all come here and that's a combination, I think it's like the European companies.

It's not that far, and then historically was New Jersey because that was like where the chemical industry was, and it's all consolidated to Cambridge.

I mean, there's no, I mean there's big companies out in the Bay area, but not— it's just gotten so, so heavy. So I think I think there's a real advantage if you're doing drug discovery specifically to be out here.

Um, I think that's just true at this point. Um, the—but I think there's like San Diego, there's, there’s San Francisco and Boston that all have like the talent.

Um, I think I honestly think there's a real opportunity. I think, I think the Silicon Valley area is like, like deep cultural product development.

Um, and so like I think if you look at like all the people moving biotech into new non-pharma areas, I think that I think Silicon Valley area is going to dominate that.

Um, they, they—I just think it's, and you see it, like new materials, leathers, mushrooms for this, like all that, like all the cool stuff that you see like all these new apps in bio, like a lot of it almost, like I'd say percent or more of those companies are out in the Bay Area.

Yeah, and Y Combinator hopes to be part of that Bay Area movement for sure!

Yeah, um, so two questions that I'll ask, uh, sort of back to back, what do you think about AIML and the space of synthetic bio and any thoughts on how organoid intelligence intersects with sinbio?

Yeah, so in terms of AIML and send bio, I mean, I think it has the potential to do a ton. Historically we've always been data limited, and so that's why I think the first place you've seen AIML like have a real impact in BIO is like where we have a lot of data, which is like how do you take a sequence of a protein and turn it into the structure of a lot of all day on that?

That's been built up over many years. It was all available in the public domain video, the PDB, the protein databank. And so that's kind of, I think partially why that's where AIML first made its Mark in BIO is the place where we had the most data.

And so I think essentially I see it in like AIML is gonna like have impact like wherever you can get enough data to make those models useful.

Cool, so that's a fundamental piece is like how do you get access to the data sets?

Um, because the tools are there now, but so it's the data is the limiting—it's the precious thing, you know? What's a good way to generate lots of biological data access?

And Ginkgo's Foundry as a service automation, right? So like this is right. Like the limiting reagent for these models, like everyone's got the same algorithms, right?

Like the algorithms are commodities more or less like at the edges, they're not, but for the most part they are, right? It is, it is having proprietary data, right?

And then that—as well, like it's just the cost to particularly to generate like data systematically that's like reliably comparable, uh, honestly, I believe requires automation, right?

Yeah, absolutely! And then what about this other one on thoughts on how organoid intelligence intersects? What’s—I don't know what organized intelligence is?

If you have escaped the bounds of ourselves, yeah? The idea—the organoid and intelligence together is what's, yeah?

I'll do this, remind me to not ask questions that I I don't know one Live on YouTube on LinkedIn, yeah? I was like, "Well, maybe they know what organoid intelligence is."

Um, now you have seen the challenges of real tech, yeah? Um, let's see what other questions.

Um, would love to hear your take on the line between science and venture-backed engineering. How much does Ginkgo allocate to the unknown versus revenue-generating from the known?

Yes, I would say since we're a platform company, um, you know, like most of our platform capacity is Kick It Up by like customer cell programs.

Um, we do reserve a certain portion of it for, you know, internal R&D of various kinds. Like a lot of us can make the platform better or to develop IP that we think will accelerate our customers' programs.

Um, but just as a platform company and since that's our business, that's kind of our focus. And what's cool is that it's like some of our customers want to do pretty amazing stuff, right?

Like, you know, the imagination and creativity and, um, and ambition of our customers is pretty see, and so we get to do some really cool stuff in partnership with.

Yeah, yeah, we have a weird—yeah, our Dynamic again, let's just keep some of that learnings. So that’s one of the big ways we do it here.

I would agree with that. Yeah, I had when you, when you think about, um, Ginkgo in five years, what do you see the company working on or what do you imagine it being with this explosion of data and everything else that we're seeing now?

Uh, I think in five years like we we ought to be starting to capture like a material chunk of the cell engineering across the current applications for biotech.

So the big, you know, the big three are basically biopharma, um, and again half of biopharma is chemistry—that's not us—but the half of biopharma that is biotechnology, uh, AG biotechnology, um, so like plant traits and biologicals, um, and then industrial biotechnology like enzymes for laundry detergents, making renewable chemicals, animal feed, things like that.

Okay, and so in those areas where people already do biotech, we want to affect like—it’s like literally what the—remember when there used to be a time where everyone had their own IT department and had their argument?

I know, but there's like IT departments and servers and like little teams that ran them all, and like that all got outsourced. Because I do remember that! I'm, I'm also old!

I also had trouble with the fact that this wasn't on Zoom, so yeah, yeah, exactly! So it’s all like you know the, like that transition from like everyone having their own small, low throughput, high-cost version of something to making use of a centralized infrastructure.

I think we can pull that off on Xbox like that. And then from there, it’s all the new stuff! Right? Then it’s then it’s dragons, right?

Like that is who knows what you can do it, then it’s dragons. And you start to drive improvement at a faster rate than you ever could have in the little server farm, right?

Like, you know, we wouldn't be having, you know, all the stuff happening in AI right now had it not been for all the data center drive and then what that drove on all the chip improvements and all that.

Then suddenly new apps show up, right? That’s what we want to, you know, that's the long game in the next five years. It’s move share from two people doing it in-house to our infrastructure.

Okay, fantastic! So you talked about arrangement, um, your customers doing a lot of cool things. So I feel like this question from the audience to take us home, what's one recent partner with Ginkgo that you're most excited about in terms of growth and why is that?

Like asking your favorite child? Or, yeah, or you know, or anything like, like what technology?

Um, I think what's been cool to see in the past couple years is just how diverse the set of applications have gotten, right?

I mean we have programs in food, we have programs in agriculture to like address sustainability and climate change. We have stuff to like try to work on metabolic diseases, we have stuff like in gene therapy.

It's like, like we had talked about this for a long time, right? But to actually like see it become a reality is like pretty—yeah, to see that the range, yeah, you could all live on the same platform.

Yeah, not expected, you know, again like, you know, we always talk about it like we got to make the tools better so we can serve all these different applications and it's like now the tools are actually getting better.

Um, and, and that's making a huge difference on the diversity of applications on the plum and so to me that's actually the thing that gets me the most excited and stoked is just like how broad a breath, um, that folks want to do out there with biology, yeah?

It's incredible what the implications are! So Reshma, Jason, thank you so much for being with me here today and talking about the incredible story of Ginkgo. I really appreciate your time.

And for those on the call, don't forget that we have another fireside chat with Adam Elliser of Penumbra who was the founder of the company and now the company has a 10 billion dollar market cap. It's rare for founders just like these two to be there kind of the whole way through.

And I had one small thing I would say, like the other thing I would like—a small piece of advice is like—and I say I'm talking about this too—but I think like the set of early employees that like can grow along with the company, like made all the difference in the world, you know?

Right? Like that, like that ends up creating all these nodes, founder-like, throughout the company and as you get bigger, oh my gosh it’s such a big deal, yeah?

You know? And so like I would expand how you how people think about like I think why she's really good about founders, and it kind of loses a little bit of the thread on the very earliest employees.

And I think that that would be like a bit of a nudge, you know? Like I think that's been as important for us. Um, yeah, we have a lot of founders that helps, but like that extended net has really paid off, such a great point to end with because you know, it really takes a lot of people to make a company successful.

And, um, those early folks end up being like family and carrying sort of the culture of the founders and of the company forward as it grows, right?

So absolutely! And, um, in my book that's coming out on Tuesday, I do that! I try to celebrate the early team as much as I can in all of their contributions, you know? So, a wonderful point!

Yeah, yeah! Thank you both so much!

Yeah, thank you!

All right, all right! Thanks all! Bye!

Thanks! Bye!

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