ACM ByteCast - Lucy Guo - Episode 89

Episode Date: August 26, 2026

In this episode, part of a special collaboration between ACM ByteCast and the American Medical Informatics Association (AMIA)’s For Your Informatics podcast, Sabrina Hsueh hosts engineer and entrepreneur Lucy Guo, co-founder of the infrastructure and software company Scale.AI and founder of Passes, a creator monetization and social media platform. Scale.AI, the data-labeling platform that industrialized human-in-the-loop infrastructure for generative AI and robotics, was acquired by Meta in 2025, making Guo the youngest self-made female billionaire at that time. In the past, she also helped develop Snap Maps as a product designer at Snap and founded Backend Capital, a venture capital firm that primarily funded early-stage engineering startups. Lucy describes her evolution from a childhood hacker into a technology entrepreneur. She stresses a persistent “builder-first,” nimble mindset, the power of surrounding yourself with ambitious peers, solving problems you personally face, and the enduring importance of high-quality data evaluation (especially in high-stakes fields like medicine and clinical trials). She talks about the challenge of pivoting from enterprise data infrastructure to consumer tech, the rising role of female founders and investors enabled by micro-funds; how AI tools are democratizing product-building and design; and her investment focus. Lucy also shares advice for college students and other young builders looking to create a positive and lasting impact.

This episode is part of a special collaboration between ACM Bycats and Amia For Your Informatics Podcast, a joint podcast series for the Association of Computing Machinery, the world's largest educational and scientific computing society, and the American Medical Informatics Association, the world's largest medical informatics community. In this new series, we talk to women leaders, researchers, practitioners, and innovators who are at the intersection of computing research and practice to apply AI to healthcare and life science. They share their experiences in their interdisciplinary career paths,

the lessons learned for health equity, and their own visions for the future of computing. In this episode of our joint ACM and AMIA podcast, we sit down with tech entrepreneur and engineer Lucy Gould. We will ink explore the critical intersection, of data infrastructure, consumer tech, and the future of AI. Lucy is best known as a co-founder of Scale AI, the multi-billion dollar star, the data platform,

and industrialize the human-in-the-loop infrastructure powering today's genera-I revolution. From childhood, Lucy brings in a unique, beautiful-first perspective to the challenges of scaling complex problems. We dive into her fascinating story, pivoting into tech entrepreneurship, learn more from the origin story of scale AI, and discuss what our young generation can learn from her experiences and how our computing professionals can be inspired on the practical need of solving massive data bottlenecks.

Currently, the founder and CEO of PASIS and the driving force behind backend capital, Lucy will also share her insights on engineering, why she care about the creator economy, and the shifting culture of women in tech leadership. And finally, why the unsexy work of data quality remains the most important frontier in computing and healthcare. Lucy, how are you? Quite, very nice seeing you. Yeah, very nice seeing you here today. As you know, this is an episode of

of our joint ACN and AMIA broadcast, where we sit down with tech entrepreneur and engineer to talk about the critical intersection of all things considered, including data infrastructure, consumer tech, and the future of AI. So with you today, I think we can dive in a little bit more on each of this perspective. But first of all, maybe you can help our audience to get to know you a little bit more. For sure. Yeah, thank you for having me. super excited to be here. So as for the audience,

hi everyone. I'm Lucy. I'm a tech founder, entrepreneur, and angel investor. I've started two tech companies, one being scale AI and other being passes, which is infrastructure for data, and then a creator economy company that helps creators monetize their brand and then invested in over 100 companies. And I'm excited to be here today to chat about everything. Thank you. Yeah, Lucy has been very humble. She is best known as the co-founder of Skao-AI, the multibillion dollar data platform that industrialized the human-in-a-loop infrastructure today.

And she's now having our new company, co-passes, and we can dive in a little bit more on that one. Lucy has a very unique and built her first perspective. I think today will be very inspiring for our audience here. But even before we dive into all this, we want to go back a little bit to the early starts, right? How did you, in your entrepreneurial journey, you started very early, right? I learned from another interview that you code in the second grade and you started. Yeah, yeah, small things. I was pretty early. I was making bots on the internet to like

auto buy specific rare items on neopets, etc. Because I discovered as like underground forum where people were, you know, selling neopoint, selling neopets, selling poll accounts. And it was great way to make money. So I started very early on doing that and then moved on and created a bunch of different websites through like, you know, WordPress. I was able to actually make a lot of money through different WordPress websites, whether it was like an arcade games website or like a movie streaming platform, TV show streaming platform, and then created a Twitter bot, et cetera. So I was just always hustling trying to figure out how to make money on the internet growing up. But I would say my like real entrepreneur journey started when I started going to hackathons and I realized there's more to the world

than just bots and internet marketing platforms, I discovered startups, right? Where you could get like millions of people to use your product and actually create impact on how their life works. Like now we're seeing, you know, startups like Uber where getting a taxi or getting around is entirely different. Or startups like Airbnb where they've like flipped a hotel model system. I got very inspired by the startups I did see in my early college years and then ended up deciding to drop out.

Yeah, you have become a role model for many of following you. I don't know if you know that. But yeah, this hacker mentality that's early from your early starts, right? So how did you see that evolve over time now? You are leading larger organization. Does that mentality still fits? And how does that help you? I would say the mentality is still there. I know that a lot of people argue that moving fast and breaking things isn't necessarily the right model to do. And I do agree that like that is true as you agree. grow larger, like when you break things, it has more impact when you have more users and more customers, right? That being said, I think it's really important to remain nimble. So that means not having that much red tape in a company. And that means thinking outside of a framework. I generally think that when you have too strict of a framework, it doesn't open your mind to like different ideas. Because startups happen when you make the impossible possible. And people that come with too much of a rigid mindset aren't able to do that and then aren't able to innovate

and build these generational companies. Right, right, right. And is there any particular inflection points that makes you realize that this can be useful or any other inflection point you want to call out in this journey? Yeah, I mean, I think my major ablection point was probably when I joined a TIL fellowship because I started being surrounded by all these people

that believe that they could build the next billion dollar company. And if you think about it, believing that for a second is extremely arrogant because very few companies actually make it to unicorn status. So I think that by being a founder, you have to have this relentless belief that you can do it and you're the one that's going to do it. But because it was so normalized in this group of Tiel Fellows and everyone that we were meeting, because everyone we were meeting, you know, was a unicorn founder.

The impossible seemed so possible. And that helped give, I would say, everyone the confidence to go out and build. And when I look back, every single Tiel Fellow has done really well. and I think it's because of the people that we were surrounded by. So I would say my major inflection point was when I joined a Tio Fellowship because I really do believe that you are the average of the people you hang around with. And when you join a TL Fellowship, you join this group of 20 people that are all extremely arrogant if you think about it.

To believe that you can build a unicorn company means that you have to be like a 0.01%, but it became very normalized within our community, especially because we were meeting so many other founders as well. And I really do think you're the average of like the five people you hang around with. So being around such a diverse group of people that all had that same mentality and all fully believed it was what drove me to have that relentless confidence to go build a company. So I would say that was inflection point number one. And then I would say inflection point number two is really learning that you should build

products that solve problems for yourself. Because when you have a problem, chances are, like there's billions of people in the world. Like other people have this problem. And it's a problem that's large enough that people are willing to, to pay for, then you have a startup. Yeah, that's a very helpful tip our younger generation here. We're now thinking about entrepreneurial journey.

And with that, say, we're also wondering about that entrepreneurial spark you have in the origin pivot, and you start with scale AI. So if you don't mind, we go back a little bit to scale AI parts. As we know, scale AI is the infrastructure backbone for autonomous vehicles and generity AI.

So that's the origin. But have you seen this being applied to any other industries that's very helpful? And from there, that starts you to get this inspiration, the impivoting, to many other solutions outside of autonomous vehicles. Can you just think of any example industry? Yeah, actually, the first issue that we tried to tackle, which is really interesting, was audio transcription, which obviously 11 labs is doing right now. they're not on transcribing audio, but they're translating audio. And that was what we kind of envisioned doing, but because we were doing manual data labeling, it just happened that we were

labeling all the data ourselves at first. So we were very, very bad at doing this. Now scale is focused on robotics. Your model is only as good as a data you feed it, right? So like everyone needs reinforcement learning on their data. It is applicable to pretty much every industry, I'd say. But right now we're focused on robotics and our initial market that we just couldn't break into because we were extremely bad at labeling the data ourselves was audio transcription. And now because there is a new concept called human in order for reinforcement learning and reinforcement learning with human feedback, right? So how did you see this now evolving to the next generation?

Yeah, I mean, I would say the next generation is that like people are building agentic tools. The risk factor is a lot higher when it comes to like bad labeling, right? So agendic tools really need to understand through reinforcement, like, did I make the best decision or the best action? So, for example, like, if you had an agenda tool, like researchification for you, book the hotels, book the flights, like, was this the most optimal solution? Like, did you make the customer happy? Because when things go wrong there and actually affects a person's life, that's not great. Right, right, right. Occasionally, this kind of work will be described as unsexy work, right? Because we know that

the data labeling, oh, that is necessary, but it's so necessary. Cuban some. And if we don't do it, we can innovate further. In our own world for AI medicine, we see a lot of that coming as well, right? Just wondering if you can reflect on that a little bit and let us know how do you just think of those kind of massive, unsexy bottlenecks that everyone is currently ignoring, but should be important, you know, to take notice. I would actually argue that nobody's ignoring, like, evaluation, right? Because it's the most important thing when it comes to training a model, especially in medicine, the risk factor is extremely high. Like, for example, if you're labeling data to figure out, like, oh, like, does this person

have cancer? Or could this clinical trial actually, like, help? What's the effectiveness of the clinical trial? Or, like, what clinical trial can we suggest to a patient for their specific disease? I actually saw this company, they train their model to figure out how to suggest different medicines for diseases that the medicine's not meant for. But they're running as a nonprofit. And obviously, like, with big pharma, they don't make money when they don't create new medications. This company is trying to go in and make it cheaper and, like, offer solutions for uncured diseases. And they have, like, a six out of six success rate right now, which is, you know, small sample, but pretty impressive still. But I think data is everything. So it's important to stay very close to the data and continue

investing in your valuation infrastructure. See, yeah. That was. would be very helpful for our audience as well to think about this complex field. And now that's people a little bit further than to your current company in passes that you're emerging as a new user experience with our creator empowerment economy. Can you describe a little bit more about your current mission in that economy? What's the significance you see that keeps you excited every day? Yeah, so I would say like when you look at, friends, you want to build a sector that has a growing tam. And what is interesting for better or

worse is that like most kids nowadays want to be a creator. Back in my day, everyone want to be an astronaut. But for better or worse, it's a creator nowadays. And I think creators are interesting because they are able to monetize their brand and monetize items, et cetera, without any customer acquisition costs because they have such a loyal following base. So I decided to build infrastructure to help creators really monetize their brand in the most optimal way possible. So whether that's merchandise, whether that's subscription, whether that's live streaming, one-on-one calls, et cetera. We've created all these tool sets to really help creators, like, build their own business, which is cool to see because now we have creators making six figures a month.

Creators on our platform have made over $100 million in just like three years, in under three years, actually. It's exciting for sure. And like the mission really for us is to help creators become these entrepreneurs. And I would say we're a success. And we're able to create like a unicorn creator and create generational wealth. which is probably realistically going to be either incubating a brand with them, which we're working on incubating brands with creators, or it would be helping to figure out how to invest in Uber, like the next Uber, because Angel investing in a correct company is another way to build generational wealth,

and we've created so many accredited investors that it's possible for them to do that if they get the right deal flow. I see. And this can take the brands across platforms, right, so no influencer have to be locking. was any given platform. Exactly, because they own their fans then. Because we saw the scare when TikTok was about to shut down where creators were like, oh my God, like, if they didn't move their audience to Instagram, YouTube, et cetera,

and TikTok was where pretty much the majority of their audience was, and they weren't monetizing it, like they were screwed if TikTok did shut down. We did see a need where creators really wanted engagement data on their top fans and to really know who their top fans are and they'd be able to reach them. So we're at the bottom of the funnel, but the super fans are the ones that are willing to spend money. So we really become a consistent income source for creators. They tell us that they make more on our platform that they do with all their brand deals combined, which is great to see. Yeah. Any particular success stories you want to name here? Like you have helped for your

transfer? I see our creators are pretty private, but we have several creators that are making you six figures a year. I mean, six figures a month. We've created like more than a dozen millionaires. It's just been really exciting. Right. Yeah. And. And as you say, it's a generation of wild. Yes, exactly. And it made nine figures collectively so far. Hopefully that will be 10 figures soon. We'll see.

No, no. YouTuber hasn't been a job until the past year, right? Now everybody knows that they can build a brand on top of that. Yeah, and that's indeed a different from data AI to consumer, right? Just want to understand that your motivation or jumping to consumer tech here, a lot of it. Like, is it always in your mind or is it something that you pivot afterwards? My experience has actually always been in consumer when you look at it. Like even every product hunt launched that I did. I worked at Quora. I worked at Snap. I worked on Messenger.

And then all my side projects were in consumer. Scale really happened by accident. And I would actually say to the audience that B2B and enterprise is much easier to brute force than consumer. So when we discovered scale, we didn't know how big of a company was going to be. We just ended up mass messaging every single YC founder like, hey, we have this API for humans. What do you want us to do with it? And then we just happened to get Cruz as one of our early customers who wanted us labeled data. And that was when it clicked and we're like, oh, we label data, then we can train ML models on it and reduce the human component over time for each task that we're doing, which is good. That being said, I think that consumer presents like a different challenge because it's just so much

harder to do. I always optimize my life around learning. So after I had learned to build an enterprise company, I wanted to learn how to build a consumer company. That was kind of where the pivot happened. It's a favorite you can jump on enterprise to a consumer. Other people, they might be afraid, right? But as you say, you observe the problems and you go in. That's really great to hear and inspiring. ACM Bycast and Amya, FYI Podcasts, are of available on Apple Podcasts, Google Podcasts, Spotify, Stedre, and other services. If you're enjoying this episode, please subscribe and leave us a review on your favorite platform. From there, what did you see as yourself going forward to focus more on?

Of course, passes your occupying most of your time as a CEO, but also see that you start your own venture, right? You have other informant with YPO Edge and all these. other younger generations, alliances, and the tech communities, is there any particular end goal that you're focusing on? Yeah, I would say overall an goal is to leave positive impact in the world, right? And I think that you can either leave positive impact in the world by building products that are, you know, extremely positive impact, which is, you know, what we're aiming to do. You can also leave impact on the world by donating money and like helping out with nonprofits. So I spend a decent amount of time with that as well. Yeah, I think my end goal is like,

I want to know I left the world and like people feel like I changed it in a positive way. And how does that young president's organization, the Edge Conference that you just attended? How does that go? Anything particularly interesting there? Yeah, I mean, it was really great meeting so many entrepreneurs because it was just inspiring, right? Like I was around a bunch of young people that all wanted to change the world and build companies. And that's a great energy to be in. I would say that I even started passes because I was an investor and I was around a bunch of

these founders that were just so energized by trying to change the world that I fed onto it. And I was like, wait, I want to be you again also. So I would say like that was the main takeaway from YPO and that like I got to like give my perspective and give very actionable advice on how these companies like what it looks like in the tech world and how these companies can maybe implement some things that we as tech companies do to help them scale better. And then I got to meet a bunch of really cool people. Super, right?

But for younger generation, like some in our audience, I ask you students, maybe in Glasgow, in college, they haven't really started. How do they get access to this fantastic network and starts exposing themselves? And as you say, right, you need to be surrounding with the people that you want to be. How can they get started? Well, I would say that college is one of the best places to do it because there's no time in your life. I think quite literally no other time in your life, you're around so many people in a dense area where everyone is the same intelligence level as you. So especially if you know you're going to an Ivy League school, everyone's smart.

And your network really is your net worth. And hiring and like building a company especially is all about emotional sales and emotional retention. Like if you're talking to the best engineers, they're getting seven-figure offers straight out of college. And you need to convince them to work for you instead. of whoever's paying them millions of dollars. And the only way you're going to do that is if you're friends with them, if there's like emotional attachment. So college is one of the best places

because everyone goes to college with knowing nobody, right? Like you're new. You have no friends, but you want to make friends. And you're around a bunch of really smart people. So I would say get to know everyone, like get to know all the smartest people, be friends with the smartest people because that's going to be the smartest network you actually have for, I think, the rest of your life. Yeah, that would probably be my main piece of advice to really young people. And then if you want to expand that network out to, like, other colleges, so many colleges host hackathon. So like I would go to HackMIT, Calhacks, like Mhacks, like Mhacks, etc. traveled around, really, going to these different colleges and Pennhacks. That's actually one of my favorites. And then meet students at all these other universities, too, that were incredibly smart and ambitious. Yeah. So if they want to get to meet you, they have to go to all these. hackathons. Yeah. Go to all the hackathons. Many of our audience are women, right? And this podcast series actually also sponsored by women in Amy. I was wondering if you can also touch on

that part a little bit, how does the culture of Silicon Valley shifting? Did you see more women CEO now in your circles and growing? I would actually say I do see more women CEOs. And I think the reason why is because, like, Angel is actually democratized being able to be in the to start micro funds. So now it's much easier for, you know, you to be a solo GP or start a small fund with other people. Because we're seeing more female investors, because it's easier to now start funds. Female investors obviously invest in more female founders. And then it's just a firewheel. And the female founders exit and then become female investors. I do think Silicon Valley was in this little rut where all the VCs were bros and there were no female partners. But now because so many

solo GPs exist or microfunds, it's a lot easier to get investment in the seed round by a woman. It's creating a flywheel, which is great. To what person did you say right now that we have the female founders in the circle? I mean, other female founders should all talk to Sarah Guo. She's incredible. She's our conviction, which is an AI fund that's doing really well. She was also kind of like my little mentor when I was working on things. But she is incredible.

And she's just an example of, you know, a female investor that started her own fund. But there's lots of them out there. And how is the current AI boom affecting this area? Did you see that bringing more women as we democratizing this AI world now to make it less tech-centric, right? Basically, everyone can comment AI to start a new company if you know how to command agents. Yeah, I would say that it's actually helping a lot of female founders. Like I said earlier, it's a lot easier to get like seed round funding because there's so many more GPs and funds. And a lot of women have started these funds because it's cheaper to build products now, right? Like every employee can be a 10x employee. That means you can get a lot further metric wise with the same amount of money. In fact, you can even like create a good enough MVP, I think, with like cursor and cloud code that you can get. funding from that, right? Just through prompting correctly.

So I do think that it is changing the landscape and democratizing access, which is great for female founders. And not just for female founders, right? It's for everyone who want to now coming to this world, right? And they can now use their ideas to start a new company if they know how to do things with AI in the look. Exactly. And actually earlier last week, I think in Lenny's podcast, they interview the Figma Design Office,

the Open AI design officer, and she's saying that the design process is now completely getting changed, and I think it's entropy design officer. So everything we originally believe as a design process is going to be changing. So we need to actually revisit the concepts that we try to design this thing as normal. again in this new world, right? So in your world, do you observe any such kind of transformation happening? Our design process is definitely benefiting from the use of AI. And then also on top of that, we no longer use as many front and engineering resources for things such as like landing pages, right? Because now designers are able to use AI to help engineer these landing pages that they

design. And because that's obviously like, you know, it lives separate from the actual platform. And it's okay if there's, you know, like little bugs or mistakes on a landing page. We're able to save end resources and our designers able to do more with AI. You're having actually quite vocal also about rejecting the Silicon Valley, Patagonia, vets and hooty uniform. Right. But I did that. Did you see some new kind of uniform emerging?

Or did you bring in any other kind of styles in this community? I actually don't remember rejecting it. But like, yeah, I have my own style. and I like to dress nice or I'm honestly no I'm in a hoodie every single day in the office but like I dress nice when I'm going out but I think everyone should just dress how they feel comfortable right so if you're comfortable in a hoodie you wear a hoodie if you're comfortable looking nicer look nicer like do whatever feels best like do what makes you feel confident because confidence is aura and aura is like what will help drive you in life and that's what brings you to you

and that's your aura that you bring to the world. Yeah, super. Going to your own venture, right? So you have this venture firm. Is it back in capital? Is there any particular focus you have now for that your venture firm? Is any core investment philosophy there you want to share with us? Yes, I started back in capital and HF0,

and the philosophy is invest in the best engineers. And the reason why is because engineers are able to build products without having to hire a full team. Even if the UX UI is bad, people will generally use a product as long as like, if they wanted enough, they will go through bugs and go through bad UX to use the product. That being said, you should probably have a designer as a co-founder. But anyways, because your runway lasts a lot longer as an engineer, it just makes more sense at the seed round.

Because as long as you don't give up, like, the engineer could pivot like for a decade, really. And even if it takes a decade for the company to work out, like if there, it's a, it's a able to make the money last a decade, which I have seen people do, I think that smart people eventually figure it out as long as they don't give up. I like investing at the seed stage, so that's my investment hypothesis there. Yeah. And when you are evaluating teachers, it's a practical thing you take notice? I tell you take notice at what have they done outside of just college, right? Like, what

have they done outside of doing the basic coursework? Like, if you say they went to MIT, I'm not that impressed. They say they did competitive programming, then I'm like, wow, you took that extra step, and competitive people make great founders for many reasons. So I like competitive people, even if they're an athlete, like that's still competitive to me. So I'm like, that's amazing. I love it when I see they try to do something on the side, such as, you know, like going to hackathons, creating side projects. Like they have experience building actual products because that means that they've had to think about certain things like what is the tam of this product. How much money should I be charging? Like how do I get to like, you know, 100 million a year? Because you know

actually thinks that you're judged on at hackathons too. So stuff like that is cool to see. Being able like not only know the theoretical stuff that school teaches you, but taking the initiative to learn how to learn the practical skills as well. Do you invest in investing any company that touch on health care? Just other curiosity for all the answer here. I actually invested in Boyle, which is essentially the shot that help us extend a dog's lifespan, which is obviously a huge market. I think people are going to be willing to pay a lot of money to make their dogs live longer. I think the hope is eventually, you know, like we can extend human lifespan.

But what I learned is that aging is not a disease. So you actually can't test medication on aging. There are certain loopholes such as like menopause being a disease, right? So you can test medication on menopause. But yeah, I'm always interested in stuff like that. Yeah, that can be the interaction point with you for our dance here in the future references. And is there any particular parts of the technical team you want to mention that in your entrepreneurial journey, any particular technical challenge you feel that's worthwhile

mentioning to our computing professional here? Yeah, I mean, I would say it's just so important to be able to build products, right? Because I think a lot of engineers, they focus, so much on this theoretical, like they can create models, but they can't create an app. Being able to actually take concepts and get them in production and get people using it is how you create real impact. So I would say, like, and it's not even, like, it's so much easier. Creating nap is easy, right? But, like, learning those practical skills is the technical challenge. Like, how do I build a good app that people will use? That takes my concept and changes lives.

There are many practitioners in our audience here will be taking notes now. When you look at this landscape today, any particular hype you think that's going to be pass on, any particular quiet trend that you think that you will double down while no one else take notice? So many people are building just products that are layer off of like chat GPT, like an AI wrapper. And those product companies don't have defensibility. So I typically, when I see an interesting product that might have really fast growth, really fast revenue, I try to see what makes them defensible. And that can be anything from like network effects to proprietary data loops.

I try to look for what I think will grow in the long term or can stay defensible in the long term versus something that's just blowing up in the moment. Because there's so many companies that can blow up but go to zero at any point in time. When you are observing all these pictures, right, did you know? notice any trend that you feel that hasn't been talked about enough that you are doubling down? I mean, I'm probably doubling down on AI and workflows, specifically ones that, like, you know, AI is very good at because it involves like repeatability, summarization, et cetera. So I think like things that interest me are probably like AI when it comes to like finance or AI in legal, et cetera, because these are typically industries that have a lot of pattern match.

where data is important. We ask you this question because we have both healthcare practitioner here and also computing professional here. So in this intersection, did you see any particular thing worth noting in your teacher listening or just observation of where the tech community are going? Yeah, yeah. I would say like within medicine, I think that clinical trial data management is incredibly interesting. I would say that what I had described where you can take, like, all the medical papers and try to find solutions on what medicines could be useful for certain diseases, it might not actually be prescribed to.

Like, I've seen that be possible because there's actually multiple startups working on it. And I've heard real life cases where it's healed people of their diseases. But yeah, I think that, like, this is probably what is this is where, like, because medical data is so proprietary, there's a lot of interesting things you can do where if you build a company, there's, is defensibility and just regulations, like being HIPAA compliant and everything. And if there is any actions you would like to name for practitioners here who are in this intersection of medicine and AI, how do you think that would be the one action they should take down today in order to position them better for that future? Yeah, I mean, I would say get close to the data and really think about what AI can do

with the underlying data that they have, right? Because in their specific practices, they have very specific data and being able to have both that domain literacy and data literacy is rare in the medicine field and it's valuable. So understand how AI can really use that data and 10x what your job is. For the younger generation, any parking words you have for them, as well are closing up here, I think they are all wanting to learn from you other than if you already talk about right to being the schools, any other things you want to bring us teeth to them. Yeah. So I would say, like I said earlier, you should definitely become friends with all the smartest

people around you because how you're going to build companies is through emotional sales and how you're going to keep your employees is emotional retention. I think that if you're building, don't always go for things that look sexy, like scale was not sexy, right? But it was a very valuable industry. And I think more boring things, you know, like the infrastructure foundations are very important and there's a lot of money to be spent there. Actually, just easier companies to build in general because B2B sales and enterprise sales are brute forcible. Understanding theory and deploying it is a very different skill set. So learn practical skills, not just theoretical. So far, so far. Yeah. If you haven't been listening, we are interviewing

the founder and CEO of passes and the driving force behind backend capital and as co-founder. of SCOAI here, Lucille. Thank you so much for sharing your insights on engineering, robots, architectures, the shifting culture, in the tech leadership here with us today. And we've learned so much about you that how the unsexy work of data actually can remain to be the most important frontier in computing and healthcare today. So thank you so much for sharing those with us.

Of course, thank you for having me. Thank you for listening to today's episode. ACM Bycast is a production of the Association for Computing Machineries Practitioners for. And AMIA's for your informatics is the production of women in AMIA. To learn more about ACM, visit ACM.org. And to learn more about AMIA, visit amia. For more information about this and other episodes, please visit learning, acm.org slash

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