The Bioinformatics CRO Podcast

Episode 50 with Alfredo Andere

Alfredo Andere, co-founder and CEO of Latch Bio, discusses the unique challenges facing young entrepreneurs and the future of cloud computing in biology. 

On The Bioinformatics CRO Podcast, we sit down with scientists to discuss interesting topics across biomedical research and to explore what made them who they are today.

You can listen on Spotify, Apple Podcasts, Google Podcasts, Amazon, and Pandora.

Alfredo is co-founder of and CEO of Latch Bio, a cloud bioinformatics platform that enables collaboration between computational biologists and wet lab researchers.

Transcript of Episode 50: Alfredo Andere

Disclaimer: Transcripts may contain errors.

Grant Belgard: [00:00:00] Welcome to The Bioinformatics CRO Podcast. I’m Grant Belgard and joining me today is Alfredo Andere. Alfredo, can you introduce yourself, please?

Alfredo Andere: [00:00:09] Totally. Thank you so much for having me, Grant. I’m Alfredo Andere. I’m the co founder and CEO at LatchBio.

Grant Belgard: [00:00:17] Welcome. So tell me about Latch.

Alfredo Andere: [00:00:20] Totally. I mean, we’re a young startup here in San Francisco creating data infrastructure for biotech companies. And specifically, we’re helping scientists analyze their data and get insights from it without having to know how to code and without having to build any infrastructure in-house. So what that means is as you know very well from your bioinformatics experience and from all your experience in bio, the data generated from a biological experiment has been annexing every two years. That means that over the last ten years it’s 100,000 X, which means that on the ground floor for biologists, we’ve gone from finishing an experiment and visualizing it with the human eye to now, ten years later, finishing an experiment and getting back a file with 100,000 lines of ACGG or 10,000 amino acid sequences or 100,000 proteomics images or microscopy images. What do you do with that? You’re not going to look at that with the human eye. You have to run it through algorithms and workflows that you’re then going to boil down into statistics, plots, graphs that you can actually look at. The problem with that is that these plots are really hard to generate. It’s not super intuitive. You need to use Python or command line or different algorithmic interfaces that biologists are not really familiar with that. So that’s problem one. And so you need a new interface to do this. So biologists sensitive to bioinformatician, to bio computational biologist, they process the data for them and then send the results back to them.

[00:01:56] Okay, that’s just a new way of doing things. It’s not, per se problematic. The real problem that we found is that these computational people are really hard to find. These bio developers, these bioinformaticians like you Grant, that have the ability to transform this data into visualizable formats. They’re really hard to find. I’m talking like 20 biologists to one Bioinformatician or one bio developer is what we usually see. And so what ends up happening in this new dynamic is biologists finishes their experiment and they send it over for analysis, and then they wait and they wait for a day. They wait for a week. They wait for a month just to get back the results of their experiment that ten years ago they got back instantly. And so I’m looking at this from a perspective coming into this from a software engineering side. I was working at Google and Facebook doing software engineering and one data engineering and the other and just getting to see the world’s best data infrastructure, the state of the art for processing terabytes of data and most of it being used for what? For optimizing advertisements, right. For getting you to click on stuff you don’t really want. And on the other hand, you have these biologists, these scientists trying to cure cancer, trying to cure heart disease, trying to cure aging, global warming. I mean, you name it.

[00:03:20] And they have some of the worst data infrastructure that we’ve seen and it’s slowing down their iteration cycles. It’s really like, how can we solve this? And we realized that initially to solve this, the best wedge into the market was to just create no code interfaces for the biologists to be able to process their data, upload it to our platform, run it through different workflows and then visualize the results. And so that’s where we started. After 3 or 4 months of market research, we raised our Series Seed, and we started working with the IGI and we started working with [AlgoBio] and we even worked a little bit with Bit Bio, which obviously you’re super familiar with accessing these no code interfaces and giving them to biologists and collecting these biologists as users of this platform. And first hundreds, then thousands. And once we created that movement, now we’re moving on more to generalizable bio development framework, and that is a type of marketplace dynamic that we want it to become the AWS plus GitHub for biotech companies. And what that means is anytime you have a marketplace dynamic, you’re going to have a chicken and egg problem. Like why are biologists going to use our platform if there’s no workflows available to them? And why are bioinformaticians or bio developers going to upload workflows to the platform if there’s no biologist to use them? And the real answer is they won’t, neither side will.

[00:04:52] So what we initially did is we uploaded all the workflows. So the no code interface I was telling you about expose them to biologists. Now that we have all these biologists using the platform, now we’re going back to the developers, to the computational biologists, to the bioinformaticians, and telling them, Hey, instead of uploading your workflows to GitHub where no one’s going to be able to replicate your academic code, to put it nicely or to react where you’re going to have to maintain a server for the next five years, just use our open-source SDK to upload it to the large platform. We automatically generate a no code interface that biologists can use. We also automatically generate an SDK and an API that other bio developers can use, and we take care of the cloud infrastructure, the scaling, the data traceability. And so we want to create the self-propagating positive feedback loop marketplace dynamic that becomes the central AWS plus GitHub for any biotech to just plug into from day one and start analyzing their data and getting insights ten times faster by not having to code and not having to build any data infrastructure. So that’s what we’re building at Latch right now and we’re well on the way there. We recently raised our series A, and we’re just building as fast as we can to be able to accelerate all these amazing companies that we’re working with.

Grant Belgard: [00:06:13] Cool. How does Latch fit into the broader ecosystem of companies in this space?

Alfredo Andere: [00:06:20] I see two main levels that we deal with. You have the all the biotech companies or really the biology companies, whether it’s Bioproduction or actual therapeutics or 100 other things. And then you have the software providers. Within the software providers, I really see it as fitting neatly into the DBTL cycle. The design build test learn like what part are you augmenting with your software that is serving then the biologists and the biology companies. I think within that DBTL there are many tools that have been growing a lot in the design and the build, so things like Benchling and other types of software that helps with the life scientists in their work. All these lymph systems that are coming along and different notebooks, they help a lot in the design and the building. Then as this data grows more and more, you have the testing phase you’re going to put into some sequencing or you’re going to create a large amount of data. And the testing phase is really interesting because there’s so large gap there from the testing that was previously biological. The microscope makers, the different wet lab makers that were doing test machinery to now it’s all computational and there’s a huge gap and there’s some companies that came along and are trying to fill that space. But it’s still a very new space, that space being computational.

[00:07:54] So that is where we fit in. Once you get your data back, you upload it to Latch and then you start processing it, visualizing it. We are not yet going into machine learning. We do a little bit of machine learning, which I see as the as the computational part of the learning phase, because that learning phase was previously human. It was you look at the results, you use your brain and you learn what experiment you’re going to do next. That part is also turning more and more computational. It’s also going more and more into machine learning, guiding the next experiment. I don’t think the space is ready for someone to build a prominent software tooling for that space because first we need to get the data right in the testing space. The data that is coming in, we need to get it organized, we need to get neatly processed. But whoever takes this testing phase is going to be very qualified to then build software for the learning phase because machine learning models are very similar to bioinformatics workflows. If you look at them from input output perspective, it’s a lot of similarities. I think whoever can build a strong foundation in the testing phase is going to be uniquely equipped for that learning part.

Grant Belgard: [00:09:01] So what’s your long term vision for Latch?

Alfredo Andere: [00:09:04] That’s a great question from that perspective, because I believe in 5 to 10 years, Latch will completely replace AWS and GitHub. And then a lot of the computational and data analysis will take place on top of Latch. We are going to be the central marketplace if you want to see it that way, where all the computational analysis are going to live, all the machine learning analysis are going to live. And so the second that an experiment finishes, all the data is automatically going to be analyzed. And then that data that is being analyzed and then the results are going to be given to a learning phase, a different machine learning algorithms that are going to be deciding the next experiment and then Latch is automatically going to send a signal to some type of cloud lab or a scientist that is manually doing these experiments to then start the next iteration cycle. And so we believe if we can build good software here, we can completely automate that whole part of experimentation and we can not just automate but also empower the people that are doing the more complex analysis. And so yeah, I mean replacing and GitHub would be the long term vision.

Grant Belgard: [00:10:22] It is ambitious, which is good for a startup. That’s where you want to be, right?

Alfredo Andere: [00:10:26] It’s hard. Yeah.

Grant Belgard: [00:10:27] So I remember the first time I spoke with you guys. It was pretty early on. I think your origin story with Latch is really interesting. Can you tell us about that?

Alfredo Andere: [00:10:39] Totally. Yeah. First time we spoke, if I remember correctly, we were inquiring about the bioinformatics CRO and the great work you’re doing there and trying to learn a bit more about the space and the market and what kind of customers you were serving. And we literally just booked a meeting with you as if we were looking for a service and had talks with you and some of the other people you work with. So the company officially and we had been working together before that Kyle, Kenny and I, but the company officially started in February 2021. And when we initially started, we had to incorporate because we went to some investors in Berkeley and we were telling them like, Hey, this space is really messed up. We are seeing just from a high level overview of Kenny working on the labs and on a couple companies. We’re seeing USB sticks being passed around. We’re seeing people running scripts on their laptop that should be running on the cloud. We’re seeing pipelines written F-sharp. We’re seeing all these kinds of messed up stuff. And then the investors were like, okay, so what are you going to do about it? And we were like, We don’t know. We’re going to go find out.

[00:11:55] And so blessed Silicon Valley, they actually gave us some money. And actually one of them invited us to Taiwan. There was no Covid there at the time. And invited us to Taiwan to just to a hacker house to go there for three months. And what we told ourselves is we’re actually not going to build anything. We’ve made this mistake in the past in other projects we’ve made. And so this time we’re not going to build anything until we know people have a problem and we understand the problem. And we have people that would be willing to pay for a solution to that problem. So for the next three months, we just talked to people and did contracting and we would do everything from booking 100 bioinformatics CRO and clicking book to emailing hundreds of people every day to LinkedIn messaging. Like we would have a rule where Kyle, Kenny and I every day would have to max out our LinkedIn requests, connections, and some people might not know this is possible, but it is. And so every day we would have to max out our connections.

Grant Belgard: [00:12:53] And if you do it too many times, they can ban you without notice.

Alfredo Andere: [00:12:57] Yeah. And we would have all these hacks around that and we got blocked from multiple email servers from companies because we would blast them with emails, not selling them anything, just asking them, Can we please have 20 minutes of your time to talk? And then when we did, we would have multiple calls a day and we would just ask them, What are your pain points like? We’re not going to tell you anything, but like you tell us what are your pain points? And then we would test hypotheses on them like, hey, we’ve been hearing people complaining about this. Is this right? Is this not right? And after three months, we had so much data on what people were struggling with. And even more valuable, we narrowed down our hypothesis of where we had six customers that were willing to pay for something, for a vision of something that sounded similar. And so only at that point, after having been contracting with some people and then having all these evidence and then having these six people that were willing to pay for something, then we went to investors for a seed round and we told them, Hey, there’s this huge problem. We want to hire two of our friends to help us solve this and we’re going to go and build it. And at that point, we raised our initial seed round. We were actually super surprised that we were able to raise a seed round and it got competitive and everything. And at that point, I mean, we had dropped out of school four months ago and at that point then we raised our seed round from Lux Capital and we started building out the platform that today is Slack.

Grant Belgard: [00:14:25] It’s fantastic. So when you were newly at Berkeley, were you planning to start a company or anticipating starting a company, or did this just naturally bubble up from the problems you were seeing?

Alfredo Andere: [00:14:40] I think it’s a combination of the two. I was planning on starting a company at some point, and it’s something I’ve always had in my plans being. I think being from Mexico, a lot of the people I know are business owners, whether medium to large business owners. And so a lot of the role models around me were always just business owners, not startups, more like commodity. Commodity sellers are different types of businesses, but always business owners. So I always had that in my plans, but it didn’t have to be out of college. I was planning on graduating. I was fully planning on graduating. I mean, I had a semester left. I was actually adding a major at the time in math on top of CS and planning on seeing if I could minor in it. And then during the summer of COVID when I went back home, I started talking initially with Kyle actually, because him and I were really interested in neuroscience. And so we started talking not about starting a company, but more so about starting a project like could we build something that people would use? Could we make something useful for people? And talking through different projects, we started working on neuroscience and I think a literally a couple of weeks after that, we all went back to Berkeley and bless COVID, which is something you rarely hear.

[00:16:00] I was supposed to be in Palo Alto at Google. Kenny was supposed to be in Boston at Asimov, and then Kyle was supposed to be back in L.A for the company he was working at. But because of COVID, we were all working remotely from Berkeley. And so as soon as we got back, we went to a party with Kenny and we started telling him about some of the ideas. We had ideas at that point and we were like, Kenny, you should consider working with us. And he decided to join. We started working on projects initially on a cognitive science, a neuroscience project to try and predict people’s emotions from an EEG headset and try and predict their focus and their emotions and just hacking on different machine learning and neuroscience stuff and then looking where to apply it. And so we looked at focus applications, we looked at marketing applications, and we started building some projects there. But really, that is the worst way to ever make a startup, like starting with a technology, well maybe in biotech. But generally when you’re making a startup, starting with a technology and then trying to fit it to a problem is what I didn’t know at the time, a terrible way to do a startup.

Grant Belgard: [00:17:18] Well, I think that’s probably one of the reasons biotech is so hard, right? Is it often is based on technologies. And some have great commercial potential and others don’t. But it’s just such an IP minefield.

Alfredo Andere: [00:17:36] Yeah. 100%. And I think so too, because in normal software and tech land, that is the worst way to do a startup. And the real way you should do it is you find a problem you’re completely passionate about and you want to be solving for the next ten years and you try out a thousand different solutions. If you start out with a solution, you’re going to be left in a very unflexible way. But we did that. We didn’t know. We were just working on a project and and working on different ideas. And at some point while working on the project, we actually started giving it to people. Nobody wanted it and we couldn’t understand why, like, this was such a good idea. Like we could predict people’s emotions with an EEG headset. But we started getting noticed. And at that point we actually had a YC interview. We applied to YC. We were like, Oh, let’s try this. We’re still in school summer and then went into the school semester and a week before YC came into my map and in our map and we started reading about the mistakes not to make. I mean, we started reading a lot about startups, but one of them, the mistakes not to make when making a startup. And for me it was more like a checklist. It was like, Oh yeah, we did this. Oh yeah, we also did this, Oh yeah, also this thing. And at some point, I think it was me, but generally agreed to by the team. We were like, Guys, we need to pivot. Like if we actually want to make anything out of this, this is not the right way to start.

[00:18:59] And so that’s around September, November. But the special thing there and going back to your question of when we started working together, the more special thing there wasn’t the idea, the more special thing was having worked with Kyle and Kenny and all of us working with each other. We knew there was something special there. We knew that the way we got along and the way we shot ideas and the way we discussed and the way we got to the truth and the way we built and the hard work we put in, we knew there was something very special there. And so we knew that we wanted to work together further and build something as big as we could. We decided to go for it and we were like, Hey, let’s trash this idea. Start from zero. The only fundamental being we’re going to work together to solve a huge problem. What do we solve? So let’s spend some time really figuring out what to solve. And so for the next month, we just read through stuff textbooks, articles, papers trying to figure out what to solve. I remember I told you that the company was founded in February. Around January, we had to make the decision by January of whether we were going to continue with school or work on this full time, and we were getting excited about biology. We knew there was so many problems to solve here. We knew we wanted to work together, so we decided to fully drop out one semester left of school, we were like, This is the team that is going to build something really big and we’re going to figure out what that is. And so we just dropped out of school.

Grant Belgard: [00:20:35] How did your parents take that?

Alfredo Andere: [00:20:37] I would say my parents were not very happy. They were actually the most unhappy out of our three parents. I know Kyle’s parents were just like his mom was just super encouraging. Like, Yeah, yeah, this is what you were meant to do. Kenny’s parents were a little put off, but he told them it was a break at first. My parents were completely pissed off, like my mom up until recently, she was still telling me, like asking me when I would go back to school. I still joke that if we IPO one day my mom will be super happy because then I’ll be able to go back to school to finish Berkeley.

Grant Belgard: [00:21:15] Go finish your last semester. Sorry. Y’all like, technically on an extended leave.

Alfredo Andere: [00:21:21] Well, that’s the beauty of Berkeley. I think they give you something like ten years to come back and finish your degree. So, I mean, you never know. I might just take some summer courses for fun because I love school. I love classes and there’s so many classes I would love to take. So it really was dropping out because the team was there and we just were all doing it. So you were not going to get left behind. So yeah, I’m glad we did. But yeah, my parents weren’t too happy.

Grant Belgard: [00:21:48] So one other thing that sticks out about Latch to me is your brilliant social media presence. Some of our listeners may have seen your coordinated pictures. You’re wearing black tops and sunglasses on a white background and things like this. Can you tell us a little bit about your marketing?

Alfredo Andere: [00:22:11] I would say there’s two branches to the marketing, the aesthetic and the different part, which is the pictures, which is a couple quirky things we do here and there. And then there’s the aesthetic parts. And I’ll start with the more quirky parts and I’ll say that actually came off. It comes off naturally from Kyle, Kenny and myself. We like to push the edge of what is allowed, where the line is at and what you can do. But those pictures actually come from a funny story. Back in the day when we were in our Berkeley office, the Berkeley office was probably not much bigger than one of our conference rooms in our current office, literally could barely fit three people. And in there, we had never raised a single dollar of venture capital. We were just three guys with a dream. And we looked at TechCrunch and you see every picture of a new financing. And I was actually making fun because it’s either in a couch or with a nature, a tree background, every single picture. And I’m seeing like, these are the people that are changing the world. These are the people who claim to be doing the most innovative, different work, the ones that are thinking outside of the box. And every picture you see is the same thing with three founders or two founders or a couple founders just on a couch or on a tree. Like, why does no one do anything different?

Grant Belgard: [00:23:40] I bet they use the same small group of photographers and probably a lot of the same backdrops.

Alfredo Andere: [00:23:47] Yeah, I would not be surprised. And so we’re looking at this and we’re like, we’re never going to be like this, we’re – if, and it was a clear if, right. If we ever raise any venture capital and if we ever go on the news and make a news announcement, we’re going to do something very different. And so we started brainstorming like, what would we do? It was either Kenny or Kyle pulled up the Lonely Island pictures. They’re really well known for taking just wild pictures. And they have one where they’re right behind each other. In that one, they’re in black turtlenecks and glasses in one of them, and in the other one they’re in blue turtlenecks and they’re like, We’re going to do something like this. And it was just like a a running joke, right? That if we ever did get funding and did big enough to get an announcement, we would do something like that. And then we got our seed round, which was actually a pretty hefty amount of money and from Lux Capital. So it was newsworthy. And the decision came and it was like, are we going to go back to the norm and do what every founder does, like we made fun of? Or are we going to stick to what we said and take those pictures and publish them? We obviously did the second and we took the pictures and we had a great time in the photo shoot. We actually took the whole founding team at the time, six people. And yeah, I think those pictures are going to go down in definitely the history of Latch and hopefully history in general.

[00:25:15] That’s the pictures and then the aesthetic of the website and the aesthetic of our Twitter page and all our whole platform, I would say that’s in big part too. I think the whole team has a lot of an eye for aesthetics and for making sure things look good from a user perspective. But really two people, Max Mullen, our founding engineer, and then even more Nathan Manske, our founding designer, he was a blessing because he was Max Mullen and Aiden. They were good friends from ours in Berkeley. But Nathan, I interviewed 100 designers and I wouldn’t like any of them. And then Nathan came along. I interviewed him. I loved his designs. He came to SF from Minnesota to interview for three days. We loved his work and we hired him. And he has been one of the biggest blessings to Latch. His ability to design and his ability to just take in your input like, Hey, I want something like this and that and then make it into the science that look beautiful and then code them up himself if need be, either in the front end of the platform or for some landing page. He actually coded our whole landing page himself. He has been a blessing to this company and we love him.

Grant Belgard: [00:26:36] You’ve brought up a couple of employees, and I’d like to talk a bit about that now. Because obviously starting a company like this in college, you’re not coming into it years of management experience. And also, how have you found the experience of, not just starting a company and having the vision and all this, but building out a team? And how many people do you have now?

Alfredo Andere: [00:27:03] I think at this point, it’s 14 people. Three of them are interns. So it’s really 11 people full time, which is wild. If you had told me a year ago that we would be here. But yeah, that’s a great question. And I think it’s one of the biggest problems that you face as a company founder is just building a team and not just leading the team, but putting the team together and finding the right people. Because if you want to build an iconic company, you have to bring in people that are very, very special and that are going to lead the company themselves and lead themselves. And this is just a constant thing that we think about every day. Thankfully, I was blessed by always being interested. And I can say the same thing about Kenny and Kyle. We are have always been interested in finding really special and talented people, especially engineers, and not because I was like, Oh, I want to recruit them in the future. It’s just the type of people I find really interesting are the scientists, the engineers, the people that are that are technical and builders and creating things. And so in Berkeley, I would say we surrounded ourselves a lot with those types of people. Machine learning at Berkeley was a club we were in at Berkeley and it was very selective. And it’s the people there are incredible. And actually I think half of our company now is from that club itself.

[00:28:23] And so we’ve always been very keen about this. And so now when we did start a company, it’s like, Hey, now we have a cost, now we have a mission. And it’s not an ad optimization mission. It’s not another SaaS startup. We’re actually building software really hard engineering problems that then help biologists and scientists tackle some of the world’s biggest challenges. Let’s recruit some more of our friends and let’s recruit some of the people we know. And so it’s something that we think about a lot in the company. We actually have meetings every week where we talk about the people that we’re talking with and the people that we want to hire in the future. And no timeline is long enough for someone that you want to hire. Like you might want to hire someone in a year or two years and they’re currently busy, but you know that they’re amazing and that at some point there will be a great fit for the company and it is part of your job for every engineer, for every person, for myself especially to continue building relationships with those people and following them and setting up the company so that in the future they’ll be uniquely positioned to drive our mission forward. And so it’s something we take very seriously and that we drive forward every day.

Grant Belgard: [00:29:38] Who and what are your near-term plans for Latch in terms of expansion? It sounds like you’re in the Bay Area. Does everyone work on site? Do you have a hybrid team? How does that look and what are your plans going forward?

Alfredo Andere: [00:29:53] So we actually work fully in person, which seems to be different these days with remote COVID return, but we hope to stick to it fully in person for the foreseeable future, at least to 20 people, hopefully to 100 people. We work from San Francisco, from the Bay Area. We’re hoping to double over the next year and we’re about to get a bigger office down in Mission Bay. And yeah, actually it’s funny enough, it’s the first question I ask now in interviews. As soon as I hop into an interview, I ask them about are you willing to move to SF and work in person six days a week? And yeah, it’s six days a week. So we actually work on Saturdays, so it’s Monday to Saturday and then NSF and that disqualifies a lot of people, which is surprising because it’s one of the top things in the job postings. But that’s currently the first question I ask.

Grant Belgard: [00:30:50] I wonder if people are really reading them thoroughly.

Alfredo Andere: [00:30:53] That’s the thing. But that’s the first question I ask and it disqualify some people. But the people that are coming into the office, they’re very special.

Grant Belgard: [00:31:05] What do you think are the influences from when you were growing up and so on that led you to do this, the semester before graduating. I think most college students wouldn’t have the confidence to do that. They would be too scared, frankly.

Alfredo Andere: [00:31:23] Yeah, I think for me definitely a combination of the entrepreneurs that have talked about their story and have inspired me since I’m young and then my parents. And in the sense of the entrepreneurs, I think my first vision of Silicon Valley was actually when I was 13 or 14. I read Steve Jobs biography by Walter Isaacson, and I remember just feeling chills through my body throughout many parts of the book where I was just so surprised and impressed that something a brand I already loved. Like at that point, I was already a huge fan of Apple and then seeing how it had been built by a team and a person and just been built out from scratch in a lifetime, less than a lifetime. And I think that put a lot of things into perspective and inspiration. And from there, reading about Elon Musk and then reading about the Twitter founder, which I mean, it’s a little more problematic. I love biographies and reading about all these people doing it and going through it, It was always a huge inspiration for me and what actually inspired me to then go study at Berkeley instead of in Mexico where I’m from and try and pursue that myself. And so when the opportunity came and it felt like the right opportunity, I knew that my parents, as much as they would love for me to finish school or they really want and have always pushed me to do, is to just follow what makes me happy and follow what I love. And so with that combination, when the right opportunity came and the right team was there which in my mind is the most important thing. I just knew I had to do it and school could wait and school is going to be there. And I think it does take a little bit of being fine with risk, but also some logic around risk and what you’re really missing out of. So yeah, that’s how we had the ability to drop out. And I think I don’t regret it at this point, but initially I definitely had my days where I look back and I was like, Wow, is this the right choice?

Grant Belgard: [00:33:38] What have been your biggest surprises?

Alfredo Andere: [00:33:41] I would say two. One of them is definitely the timelines, stuff takes time. And it’s not just hard work, but hard work over a long period of time. And just understanding how long stuff is going to take and how hard building good software is and how hard getting a single user is, and then how hard getting ten users is and 100 understanding that a lot of the superficiality that you see in TechCrunch is actually just very few data points over a lot of companies. You’re always seeing companies getting funded and so you’re always thinking like, Oh yeah, this goes really fast. But when you actually look at the background of these companies, they’ve been being built for five years, ten years. And it’s only now that they’re reaching the point of really rocket ship trajectory. And so stuff takes time and stuff takes a lot of hard work over that time. And understanding that we’re dealing with ten year timelines and 20 year timelines has been a huge surprise to someone that my biggest timelines had been four years for college. On the other hand, it also surprises me how from the inside, a lot of companies that look very prominent and like everything is going perfectly are actually not that great. Actually, if you can find a team of people that are really willing to work super hard for an extended period of time, let’s say ten years, actually that in itself is super special and super hard to find. It’s very rare. So those are two of many surprises I’ve had while doing this.

Grant Belgard: [00:35:30] What advice would you have for young entrepreneurs possibly starting a company during undergrad or grad school or whatever?

Alfredo Andere: [00:35:39] My first advice would be to not take anyone’s advice. Not anyone’s advice, but be very selective and filter out a lot of the advice you get. I like to say that all advice averages out to zero. And so I think you have to be very selective because when you’re a young startup founder, especially in biotech. Like if I had a dollar for every person who told me that I cannot start a biotech software company without a PhD, I wouldn’t have to make a startup. But it’s very discouraging to talk to people and to get everyone’s advice because most people will tell you can’t do it. And sure, the probabilities are low. But the other advice I would give is don’t do it just for the sake of doing it, because it’s really, really hard and it’s not a good life. I mean, unless this is your calling and you might not know if it is. You should probably not do this. It’s really hard to make a startup. It’s working seven days a week, 16 hours a day, every single day for the next ten years of your life. It’s really painful in many ways. You miss out on a lot unless you are convinced that this is your calling and this is what you want to do, you will not enjoy it. And so that would be my other piece of advice is don’t do it. And I like to give that advice because I think if you’re the person that’s the type of person who’s going to do it anyway, you’re going to do it anyway. But I would recommend not doing it.

Grant Belgard: [00:37:16] If you’re contrarian enough. Yeah, it’s rough. It’s really hard. If there’s one message you would have for our listeners about Latch, what would it be?

Alfredo Andere: [00:37:32] We are not a no code platform. We are a development framework for bio developers to be able to easily yes, create no code interfaces, but also to easily create other interfaces and also to easily deploy to the cloud and to easily be able to track data, traceability and all of these benefits that wrapping your code in our SDK gives you. And so we’ve been dealing a lot with that. We were initially a no code platform because we were dogfooding our own SDK and a lot of people are like, Oh, I can’t do my work in a no code platform. We know, we understand, and now we’re open sourcing our own SDK that we use to create those no code platforms to the rest of the world and hoping to get the developer community in bio to adopt it and accelerate their work and accelerate the work of their company. And so if I can say one message and you’ll hear me saying this a lot over the next coming months is Latch is not a no code platform. It is a bio development framework.

Grant Belgard: [00:38:41] Nice. Well, thank you so much for joining us today. It was great.

Alfredo Andere: [00:38:46] No, thank you Grant. Really appreciate you having me. I’m a huge fan of your work so thank you for inviting me to your podcast.