S8E3: Jaclyn Rice Nelson and her Expert Engineers at Tribe AI are Bringing Businesses into the Modern World of AI and Machine Learning

The volume of companies that are actually doing really innovative things is so high, and that is putting pressure on the OpenAIs, the Googles, the Microsofts, etc. But it's also putting pressure on the large incumbents that are not AI-first companies. So the law firms, the tax firms, healthcare institutions, you see that actually every one of these players is focused on building solutions in AI.

Welcome back to season 8. Clauds, how we doing?

So well. Can't believe it's 8 seasons of The Room Podcast.

It feels like just yesterday we were getting started in the middle of COVID and had this vision for sharing the future of founding stories to let other founders be in the room where it happened and So much has changed for us since August 2020 when we first had this inception. You're now a founder and co-CEO of Priv, which is a startup unlocking and disrupting recurring revenue for e-commerce brands.

And Madison, you are crushing it in venture. You're now a partner overseeing investments at Divide VC, an early-stage venture firm in the Bay Area, and of course an investor in Priv. We're just two women navigating our careers and asking the people who inspire us to shed light on their stories. Unlocking Access starts with a conversation context, and as a reminder, we open the door to moments in technology history that traditionally happen behind closed doors. With our guests, we unpack the experiences that led to their success and look towards the future in their verticals.

And we hit an incredible milestone at the end of last season with Spotify sharing that we were a top 5% global shared podcast in the technology sector. And so we want to thank you for being a loyal listener. And helping us achieve this milestone of amplifying more equitable voices in the room where it happens. As you look towards Season 8, get excited. We're excited. We have some incredible founders from the founder of Superhuman, the founder of Incredible Health, Webflow, Ty Haney with her new business TYB, and more. So join us every Tuesday where we sit down with leaders, founders, and funders who are changing the way it's always been done. You could expect themes across, of course, generative AI, navigating your startup in a downturn, the creator economy, and more. So be sure to hit subscribe, like, and follow so you don't miss any Tuesdays in the near future. And one quick note, since season 3 in 2021, we have been delighted to work with our partners Cooley and Silicon Valley Bank. This season is no different, although the events of the past few weeks have brought Silicon Valley Bank into the forefront of our ecosystems conversations. Now known as Silicon Valley Bridge Bank, SVB. Thank you. And now a short message from our sponsors. Following message was recorded prior to 3/10/23. Support for The Room comes from Silicon Valley Bank.

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Welcome back to another episode of The Room Podcast. Today, we are excited to share our conversation as we sit down with Jacqueline Rice Nelson, the visionary CEO and founder of Tribe AI. Tribe AI is a firm that provides and connects AI and machine learning focused engineers to businesses wanting to optimize their operations and make data-driven decisions. Particularly relevant during this year's focus on AI. Now, any company, any business will be able to leverage expertise of AI talent. Jackie noticed a gap in the market where many AI and ML engineers were only hired via the occasional ad hoc consulting gig. However, she knew that there were countless companies that desperately needed the help of exactly these experts. She wanted to build a new market for leveraging AI experts. That was the birth of Tribe AI. Themes in today's episode include navigating the windy path to identifying a gap in the market as she talks about her journey to starting Tribe AI, which was born out of South Park Commons. Which is also where she met her co-founder, alternative ways to start, fund, and scale a startup. Venture capital is not the only way, and the future of AI in today's market, including a discussion on defensibility and IP. Let's open the door.

Jackie, thank you so much for joining us today in The Room.

Pumped to be here.

Well, lovely to have you, and we're really excited to dive right in to such a relevant topic with what you're building with Tribe AI. Um, but before we get started down the whole rabbit hole, we'd love to start at the beginning with our guests. And so could you tell us a little bit about where you grew up and how that's shaped your view of the world?

It's funny because where I grew up is where I am right now in New York City, but I've taken a really windy journey from there. I would say New York, the industry that kind of has dominated historically is finance. So that is what I did out of school. I went into banking. I actually was raised by a single mom who supported us economically. And so being able to be financially independent from day one was basically my graduating goal. I think actually on the day that I accepted my offer to join Citigroup, I got an interview at Google. And I remember thinking like, oh, that sounds really cool, but I, I'm not so excited about this whole banking thing. But I had a mission and, and was able to, you know, pay my rent and make sure none of my expenses went to my mom, go forward. But I did, I totally hated it. I was like the worst baker of all time, but I still had fun. I learned a lot. I think the part that resonated with me was really learning about businesses and like particularly businesses that like I didn't know existed, like outsourced emergency rooms. Wow, these can be like these huge companies. And it turns out that ties directly to what I'm doing today. But the kind of in between is I actually met my husband, uh, on our second or third date. He got into Stanford Business School. He had only applied to one school. He was moving to California. And fast forward, I moved to the Bay Area, and that is the only way I got into tech. I wanted to move for this guy, but I couldn't ever say that. I had far too much pride for that, and I needed to get a job, and I only knew of two companies in tech. Google and Facebook. I applied to both of them. I had my first interview at Google. I got the job and it was like, cool, I'm totally moving for a job. I always wanted to be in tech.

Oh my gosh, I— that story resonates on many layers. The one around banking being, I sometimes still look over my shoulder and I'm like, is someone going to revoke my finance card? Because I did product and then venture and I totally skipped banking and I feel like I won the lottery. And really fun that shortly thereafter you were able to find a better fit for you, which was in tech. For a boy, not for a boy. It obviously worked out. It was meant to be. And so I guess taking a step back, like falling into tech before then, or even as you were falling into that job at Google, did you think you were ever going to become a founder?

It's interesting. I don't know at that moment that I would've been able to say that, but only a few years later I did say it out loud. So I think frankly, I didn't like banking so much I wasn't sure if I liked working. I had only done something that destroyed my soul. And so it was like, I need to first find work that aligns with both my interests, but also my skills and what I uniquely can do better than other people. That is what I ultimately found in tech. And so walking into Google was just a breath of fresh air for me. And I was coming with this banking intensity. And so I would like routinely be the last person in the office. I was working crazy banking-level hours when no one else was. and I was just able to take on a ton of opportunity, not 'cause anyone was making me do it, but I was like, wait, this is actually fun. I'm into it. And I think the other piece for me was I looked around in banking at the people— I always look above me. So the, in this case, women leaders who were at Citigroup, and I looked around at Google and I saw the Lexi Reeses, the Claire Hughes-Johnsons, the Gretchen Howards, and I was like, oh, I want to be all of you. And so it was super motivating for me to be in that environment. and despite being, it was still a big company. This was January 2011, but I joined in the San Francisco office and there actually was no infrastructure. There were very few people. It was pretty flat. And so if you were willing to do the work, to raise your hand, to step up, you could get crazy opportunities. I think I always secretly wanted to do that after being exposed in tech. At first, I just wanted to be the Lexis Grechens. And Claires of the world and wanted to be leaders of organizations like the ones I was a part of. And then eventually I did get the startup bug and it was like, okay, I either want to run a business or start a business. And then very quickly that became, I want to start a business.

You traveled across the country, you're exposed to this whole new world of tech. You're at Google. You started in Google Helpouts and then ultimately found yourself at what was Google Capital is now CapG as the VP of Growth. Walk us through, you know, those different roles and kind of experiences getting to know the broader Google ecosystem and then ultimately landing yourself on the investing side.

My first job at Google was on the ad side, and so I did like pre-HellBouts, like 2 and a half years on the ad side of the business. I joined in a role that was so junior, it doesn't exist anymore and is like a purely outsourced role. Or automated, as it should be. But I really started bottom of the totem pole, which was fair. Like, I knew nothing about tech, and I knew nothing about tech B2B, and I knew tech B2B— I was only focused on tech B2B companies. So I was like, I don't know, what do you people do? I've never heard of Oracle before. And I knew nothing about advertising or online advertising. When I interviewed at Google, and I remember I just watched 100 YouTube videos of like Hal Varian, who was the chief economist, explaining the AdWords auction. I basically memorized it and I parroted it back in the interview. Like, I knew nothing. For me, it was fun. Everything was learning and it was interesting. And I started working with these really large companies— Oracle, Salesforce, Adobe, Symantec— the tech B2B behemoths, all San Francisco-based. And then had an opportunity to start working with the next generation of tech B2B companies. The up-and-comers Box and DocuSign, which at the time were really early-stage startups. And I loved it. The other guys, they're so slow. If you have an idea, like, they'll get back to you in months. Bazillion approvals. Like, it felt like Google. It felt like banking. And then being part of Box and DocuSign, if you were smart, if you had ideas, they needed you. So like, they would put me to work and I was willing to work for them. So I just felt like the speed, the excitement, the like alignment on making this vision a reality. Even as someone who wasn't on their team, I found that so infectious and so energizing. And that is basically what set me on this startup journey. That's how I ended up at Helpouts, which was a consumer marketplace product for connecting experts over live video, like a lot— a marketplace built on top of Zoom would be today. In our case, it was Hangouts, which was far buggier. That was my first exposure to building a business, launching a business, working closely with engineering teams, then scaling a business. When I joined, I was one of the first business people. There were about 30 engineers. We scaled the team up to around 150. We unfortunately failed to find product-market fit, as many startups do, although more startups within big companies do, and had an experience of shutting down the product. And then that brought me to Capital G, where the theory was, okay, you've done this entrepreneurial thing within Google. Now go help figure out how to scale the companies that we invest in. And then really built out that model.

It's interesting, just even that nugget around Helpouts where you're describing a product that actually a lot of people are talking about now, which like expert matching— timing is everything. Exactly. And so just kind of cool to hear. It's like there's not new ideas under the sun, there's execution and timing. And when you can get those two things right, you can sometimes have a really awesome product. But then you learn either way, and learn you did. About to jump into Tribe AI, which you've been building for the last few years and you're working on today as the founder. However, before we jump in, you mentioned a little bit around some senior leadership who were women at Google that really inspired you. And in addition to being the CEO and co-founder of Tribe, you also are the co-founder and GP of Coalition Operators. And just for those who don't know, that has this mission of making more women operators into investors. I love this mission. Could you just tell us a little bit more about the origin story of this initiative?

I feel so lucky to have been surrounded by the top operators in our industry, but particularly the women leaders. I did get chances to work with these people who are iconic and are truly world-class at what they do. And as you grow up in your career, the people who become the most influential for you aren't just the people above you. It's actually your peer set. It's what you guys have in each other. All of a sudden you realize, oh, my friends are killing it. Like, my friends are now the people who other people are like, holy shit, Toyin Ajayi, or Lindsay Ullman, or Ashley Mayer. And, you know, I looked around and realized that despite the fact that all of us, many of us had even worked in venture or held these insane jobs, very few of my smartest, most capable, most impressive peers were investing. And I, I was— I really liked it, turned out was quite good at it. I was an early investor in all these amazing companies. I got to build these relationships with truly incredible founders, and I was just like, I became an evangelist. It was like, hello, like, where is everyone? Why aren't you doing this? And I would say most of the conversations I had were with people who, for a variety of reasons, felt really uncomfortable. Um, some of it felt really gendered, and other parts of it felt super valid, like they had real concerns. And the sort of takeaway was, I'm very good at sales, and I was very unsuccessful at selling angel investing to my peer group. And so it felt like there was something wrong. And the reason I really cared about this problem is because it became so clear to me that all of our male peers were— they were investing, they were on the cap tables of these amazing companies, they were building relationships with the venture firms who were participating in those rounds, they were building relationships with these influential founders. And more than anything, the people who were making money from these category-defining companies are either the founders, the early employees, or the investors. And there wasn't a lot of diversity in that group. And it really became clear that this is how the sort of cycle perpetuates, which has led to a lot of inequality in tech. And so instead of talking about, wow, the numbers in terms of investment going to women founders or any variety of things, women in leadership, et cetera, is so depressing. I was like, this is something we can actually change. And so we built Coalition to first study what the barriers were for women in investing and then build a, a model, a solution that actually addressed each of those and made it easy for women to get equity in some of the top venture-backed companies. We've now brought over 100 women onto cap tables of what, top-tier venture-backed companies. And in addition, we raised our own fund, $12.5 million fund. Which we've deployed a large share of and have invested in like 100 companies ourselves.

You're so right. Like there is often just such a big conversation around why there are not more female founders, which I feel, you know, very much like in that conversation. But it's true, like we've also had conversations with other female GPs on this podcast that a lot of their female friends feel uncomfortable talking about money and investing when everyone else is doing it. And so I think that's such an incredible, like, opening door mission of understanding the roadblocks to why other successful female career women are not necessarily angel investing or investing in other ways. So incredibly cool. We'll have to dig a little bit more into Coalition later in the pod, but I'd love to use this as a segue to talk a little bit more about the other thing that you founded, which is Tribe AI. Jackie, in 2019, you set out to build Tribe AI with your co-founder Noah Gale. As an experiment at South Park Commons. One, tell us a little bit more about your time at South Park Commons, how Tribe merged from experiment into what it is today, but also tell us a little bit more about how you met and entered the journey of building a company together.

So South Park Commons is a very cool place. Also, like at the time, I didn't know I joined it. It's sort of like an interesting— I didn't know I joined it and I wasn't there at the same time as my co-founder. The first piece of it is the founder is this woman named Ruchi. She was the first female engineer at Facebook. Incredible, incredible engineer and operator. She's been a founder herself. She sold a company to Dropbox. She led operations for Dropbox, and then she stepped away and saw this same gap that there were lots of people who had stepped off the treadmill of really big jobs and were taking some time to figure out what it was they did next. And her insight was that making that decision on what to do with your life's work is a really big deal. And so she created a space called Safeguard Commons. It's not an incubator, it's not an accelerator, but most of people who are members and spending time there are starting companies. And so they claim to be this space for like zero-to-one thinking and a community of peers who are all extremely talented, young, hungry, and want to do something and are just trying to figure it out. Where you don't have to have clean answers. I had left Capital G and I went on a walk with her and she's telling me about how she raised a fund and was trying to figure out how to like bring the fund and the community together. And I had just left a fund and had thought about similar things and she was like, why don't you just come and help us out? I was like, great. And yeah, totally. And so I did. I started going in, I started joining meetings, and then one day I got this email like, you're You have to pay your dues. And I was like, wait, what? And honestly, it was like the best money I've ever spent. I just hadn't really thought about it. And so I started spending time there. One of the first things I saw was there were just all of these incredible brilliant technologists that were just hanging out. What are you doing? They were like working on research they cared about. These are ex-OpenAI engineers, a guy who wrote the first client of TensorFlow, like just like celebrity-level engineers just working on things they thought were cool and like working out in the middle of the day and eating lots of blueberries. Like, truly. And I just started, like, questioning them. I was like a journalist or like an anthropologist. It was like, how do you pay your rent? Like, how does your life work? Do you like to go to Plough for breakfast? Plough's expensive. Like, how do you— like, how does this all work? And every once in a while, the answer was like, some friend will send me a consulting job. Every once in a while, do that. And then it, like, lets me float my life. Like, their costs weren't particularly high outside of plow and some blueberries and rent in Potrero Hill, and that's kind of it. They kept it basic. I was like, great, if you wanted to do another one of those projects, what would you do? Where would you get it? They were like, uh, I have no idea. Like, I would probably just like wait for someone to email me. I was like, cool. I'm such a salesperson. I could sell you. I know everyone wants you. Every single company is literally looking for you. but you're not on the market and you're so valuable. And so the experiment was, if I could get you one of these opportunities, would you do it? And that was it. I'm a hustler and persistent, and I was like, great, here it is. And that is how Tribe was born. And we started getting together this really tight curated group of people, understood what they cared about and what they were trying to achieve. And we built consulting as a means of helping them achieve their goals. It wasn't like we set out to build a consulting firm. We believed there was a supply-demand imbalance between companies and this elite, incredible talent in AI, machine learning, and data that had done it before. And my insight from Capital AG was that no companies, even if they were these really big companies, actually knew what they were doing. And so I really saw this potential to build a category-defining company that was built around the AI engineer.

You mentioned that building Tribe AI was kind of an accident in many ways, but was there an aha moment where you realized, hey, there's this group of people that companies really desperately need to leverage? Let's build a business. Let's actually formalize this into what Tribe AI is today.

I skipped over the, my co-founder part of the story, which is happens in the middle of what I just described, which is I actually, after leaving CapitalG, briefly joined a Series A fintech company. The theory for me was, I've only seen a failed startup within Google, like, where I have to put like a startup in quotes and people give me an eye roll. Like, I just need to go work at a startup. I like knew my career was going to be in an early stage, and it just felt like I needed to see it myself. And so I, I did this for a bit and was quickly like, okay, I get this. I'm now ready to like do this myself. And at that point, I was already thinking about new ideas and starting to like hone in on something that is around the idea that became Tribe. And I saw in the South Park Commons Slack channel that some guy had posted some project he was working on, and it was kind of related to the idea I'd been thinking about. And so I just cold reached out to him and said I was really interested in what he was doing and did he have time to go for a walk and catch up. He came to my startup office at the time. We went on a walk around Yerba Buena Park and I was like, oh my gosh, this is that moment. Like, this is like the perfect person. He worked at Gigster, he worked at Expah, he had built these distributed network-based talent models. He had thought about sales innovations. At the end, I was like, great, I'm about to quit and I'm gonna work on this. And he said, great, I'm about to shut down what I'm working on. And accept a job at Braintrust. It was like, what? Um, anyway, fast forward, he did and I did. I quit. I started hanging out at South Park Commons, and the first day I walked into the office, he was there. He had taken the job at Braintrust and he was working from there. And I was like, great, I'm gonna go upstairs and like work on that idea I talked to you about. And he was like, oh cool, when I don't have calls, like, could I just come up and help you out? And fast forward a few weeks, he was like, I need to work on this with you, and quit his job. And then we like an all-in on Tribe, but I knew a co-founder was gonna be critical for me, just personality-wise, to start this business. But I, I really felt like I needed to even figure out if there was a there before anything else really mattered. And so we actually just jumped in on working together before figuring out if we were the right fit. And both through that process validated that there was a there there and that we were a good fit working together.

That's fascinating. I often get other founders saying like, how do you meet a co-founder? And it's never that simple. So it's incredibly cool to hear just how, although at first timing didn't really work out, you were working somewhere else, he went to take on a new job, that it kind of organically happened because you were both passionate about the problem that you were solving. Zooming out a little bit, AI is something that is hotly talked about these days. And so given that AI started as a community of top engineers and data leaders that partner with companies to solve these real-world problems, how has the AI landscape changed over the past 4 years and changed Tribe AI with it?

Oh my gosh, it is a whole new world. And this has only happened over the last few months. So I think the insight that led to Tribe was that I had seen the most technically savvy and sophisticated companies struggling. These are capital G portfolio companies— Stripe, Airbnb, you name it— struggling with data science and machine learning. And it wasn't, you know, how do I do this really sophisticated reinforcement model? It was like, where should I apply machine learning to my business? And How do I assess a data scientist if I don't have one? We were interviewing candidates for them. The questions were really basic, they were really fundamental, and it just felt these were the problems and the questions that the top companies had. Like, what was everyone else doing? And so the real insight was, and the research that I did proved, that actually, despite— it's similar to diversity— despite a lot of talk about it, there wasn't a lot being done, or certainly not being done in ways that actually move the needle for businesses and for the industry. Now, that seems crazy today because today all anyone's talking about is AI. But even 6 months ago or a year ago, we're still out here convincing people they should care. And I think that we are in a really exciting moment because AI is mainstream, right? Our families finally understand what we do for a living, even though there is an economic pull back more broadly. AI is something that can't be ignored. You cannot pull back on your spend there. And that is a fundamental shift. It means that there will be huge gains right now. And I think the reason for that is because there's competitive pressure from truly every angle. Like the competitive landscape is so fascinating. The pace of startup innovation is unlike anything I've ever seen. Um, and it's not just that every startup deck, pitch deck you guys are seeing, it has AI in it. They do, truly everyone, but there's just the volume of companies that are actually doing really innovative things is so high. And that is putting pressure on the OpenAIs, the Googles, the Microsofts, et cetera. But it's also putting pressure on the large incumbents that are not AI-first companies. So the law firms, the tax firms, healthcare institutions, you see that actually every one of these players is focused on building solutions in AI. And it's because if they don't, one of these people, the startups or the technical incumbents, are gonna eat their lunch. And I think as a result, there is just like such dramatic acceleration in AI adoption.

Now that AI can't be ignored, walk us a little bit through who your customers are. And let's say I'm a company, how would I work with Tribe AI to make sure that I'm not falling off the wagon?

We work with everyone. We built a model that's really flexible and adaptable both to the needs of companies and to the needs of talent. And so that means that we can work with startups who are working on the most innovative large language model generative solutions. We can work with mid-market companies, private equity firms, Sleep BP-backed businesses that have data but are thinking about data warehousing or are exploring generative solutions, but like need to be convinced there's enough value for investment. And then we're working with large enterprises, public companies, Fortune, you know, 500 and 100 companies. And those problems are wide-ranging. They could be generative applications like a large auto insurer, or they could be truly like any of these large data security types of challenges where they're really building their infrastructure for scale.

You mentioned that in the past 6 months, we're now in the zeitgeist of AI, and I'm sure there's been a lot of inbound leads in the past few months to Tribe. But on this podcast, we love to dig a little bit into the moments that were not always up and to the right. Could you explain or kind of walk us through a moment in building Tribe that, you know, things didn't quite go as planned?

Let me count them. So yeah, being a founder is a comedy, an actual comedy. But it's amazing that we are where we are today because in the not too distant future we had this existential moment. And that is 2021 was probably like our best year of all time. We had a tiny team, we were totally off guard, we hit product market fit, we were growing at 20, 30, 50, 100% quarter growth. And multi-millions of dollars per quarter. It was feeling awesome. And we were doing this with a team of 3, which our profit margin was like off the charts. That was real good times. We were feeling really high on our own supply. Of course we needed to scale, so we started hiring a lot. We started saying no to smaller customers, leaning in on only these sort of like bigger, larger managed engagements. Interestingly enough, despite doing all the quote right things when you're building and scaling a company, all of a sudden our business disappeared. And so now we had all these really expensive, fancy people that were used to working at scale and like we had no business. This is like 2022. This is like yesterday. And basically a variety of factors. One is scaling a team is hard. Ramping a team is extremely difficult. Finding the right fit. Pain points there. Another is that by focusing on these large managed engagements, we actually ended up having a lot of customer concentration, which, A, was challenging from a churn perspective, uh, which is inevitable. But beyond that, actually, it meant that you could only have people from our network engaged on projects because you only had a few projects, even if they were hugely profitable and generating a lot of revenue. And so we could have looked at— we had this amazing asset of hundreds of these engineers but we're only using like a fraction of that. This doesn't make sense. And what we realized is that actually not only was that the problem, but by cutting off kind of startups and smaller projects, we actually unintentionally cut off a major growth lever for our business. So we are hugely network effects based, which means anytime the talent engages with a company, any kind of opportunity, value is accrued. That customer goes on to refer us, to like shout from the rooftops how amazing these people are. The talent does the same, and we just get like talent coming to us and customers coming to us, and every single interaction is valuable. And so by compressing those number of interactions, we also compressed the number of companies and talent that knew about Tribe. And so that was from another challenge. And then the third is that I think we really were like a canary in the coal mine, which is to say that AI and machine learning is sort of a more experimental area or has been historically. And clearly we are in a challenging economic moment, but this was before we all realized that. This was before anyone was talking about inflation and all the fun topics we get to think about today. But we were seeing people really cutting down and like trim on budgets and pull back, and we didn't know why. Now, of course, now it all makes sense because, you know, the economy only went in one direction. But I think we were one of the first places to get hit because it is so experimental. And while today it's something that you can't cut, then it felt like, of course you would cut there, right? So the fact that fast forward only a few months and we are in this like mainstream AI adoption moment, we have more demand than ever seen before. Where we once were getting dozens of applications a week, we are now getting dozens of applications a day from talent. Companies of all sizes are showing up at our doorstep. We are working with every one of the top foundational model generative companies, all the hot buzzy names. We're working with these amazing companies and we're getting, most importantly, such a high percentage of the talent in our network that wants to work on these opportunities that are so exciting and engaging for them. And that is just like fueling the growth on top of this step function change moment in the industry.

And there's a lot of good nuggets there on understanding the levers of supply and demand within your marketplace to having early signal on a macro shift and turn down, but then ratcheting it back up in a moment that almost no one could have predicted where AI is on everyone's mind. You mentioned the hundreds of cutting-edge engineers, data scientists, ML engineers who were in your ecosystem. And this lends itself to the core principle of Tribe AI around freedom being a driver for success. These employees and engineers, they work with Tribe to find partnerships and find projects and companies that they want to work with, which can be more efficient than an in-house AI team. But in a time when everyone's kind of talking about either owning their large language models or connecting via API, how do you guys think about, or how do your engineers think about, like, the intellectual property and the engagement they're having with some of these models that are getting built in real time?

IP is one of the most interesting questions in the space right now, as well as moats and how you think about like really where value is going to accrue in the ecosystem, in the stack. I think right now, if you're an engineer, the most important thing is to know how to use these models, to know how to fine-tune them. Of course, like there is the idea generative talent doesn't exist unless you were part of building transformer models from the beginning. Or did a PhD on something really similar or worked at OpenAI and maybe one or two other companies, you are learning this with everyone else. And so I think a lot about upskilling of the industry and where these differentiated skill sets are really— and where value is going to be accrued from a skill perspective. And I think that building that expertise is valuable. So aside from just the IP question, which is like there's value in just having that experience and knowing how to do it, because once these questions get figured out, you're gonna be the go-to. As far as how to think about IP, I do think there are lots of ways you can think about protecting yourself and your ideas and your company. And we are already seeing lots of companies, just George Matthew from the Insight team, who was the lead investor in one of the last rounds of Jasper, was in the office the other day. Talking about kind of ways they're thinking about really protecting IP and building defensibility, experimentation frameworks, UX, and of course, like, the dataset you are fine-tuning with being proprietary and thinking about ways to actually keep that proprietary so that data isn't just going back to companies like OpenAI and feeding into everyone's model.

That's like the other coin of IP, right? There's like the IP on the models themselves and actually understanding how they're built such that one is better than the other, quote unquote. But then there's also the privacy of the data that's training the models itself. And kind of like an analogy I can give from my world where I was at Gap was one of the reasons we were using Azure over AWS for our cloud solution, we were migrating from on-prem, was because of this concern over privacy. Even though like really, if you think about it, AWS probably isn't like reading Gap's data stored in their cloud data warehouses, but there's the concern. And so almost like applying that analogy here to data models of like, oh, I'm a next-gen search provider or, you know, productivity tool, but I don't want Google to have my data, or I don't want OpenAI to have my data, which is Microsoft in some way. Could you maybe untangle some of those notions, right or wrong, for any startup or company that's looking to implement some of these newfound APIs?

I think this is super interesting. We have many experts on terms of service in our crew, and they would tell you that the terms of service of some of these models are deeply upsetting and being really cautious about what kinds of data you are feeding in, particularly, my gosh, for anything regulated, right? Any PII information, like, don't do it. It's just a reality. You, you really do have to be thoughtful about these things. That said, like, this is a problem that will get solved because it has to. It's the only way we can continue to accrue value from these models. And if we all have to build our own foundational models, this all defeats the purpose, right? The value here is that we are able to create new infrastructure that companies can build off of and benefit from that help us all leapfrog so many levels from where we are today. And so I am a deep believer that there will be a lot of change here. In the interim, I think like my guidance is be cautious on how and what you feed into these models. And that is where I really think about where talent is differentiated, which is you are in an industry where you're working with proprietary and sensitive information. The people on your team who are building, fine-tuning, and developing solutions that tie to these models, my gosh, they better understand your privacy and security concerns. And be thinking first and foremost about how they protect your business when building solutions here. It doesn't mean that it's not possible. It means that it's just critical that you're working with people who know what they're doing and have done this before and can help you come up with the right solutions for your business. So I don't believe in custom software for custom software's sake, but the reality is that not every business is the same. Some people think they have like hugely proprietary data and they don't. And I'm like, you just feed it into the model, you're buffing. And other people like, you should never give them that data. Honestly, it doesn't even have to be a deep engineer. It has to be someone who understands the landscape, understands what's possible, and can help be a strategic advisor on thinking through some of these critical questions and then making sure you have the right talent that actually understands the considerations that are important for you and your business. Business. How this ties to Tribe is we really think about building the right match of talent. This is why this model works to the right problem type. You cannot have someone who worked in consumer and e-com working on deep healthcare data. It's just not what's going to be the optimal solution.

Well, we'll be sure to link Tribe AI here in the pod because I think there'll be a lot of founders listening in who will be eager to tap into this talent and have some of this expertise as they're really navigating and thinking through this shifting landscape. Taking a step back, I'm kind of asking this a little bit selfishly. You mentioned companies like Jasper. Of course, with your work with Coalition, you're still investing on the side. You have this amazing thousand-foot view. How are you thinking about the application layer on top of these models?

It's funny, I also talk to a lot of investors in the space, and I think early days everyone was like, I don't wanna be at the model level, I wanna be at the vertical application level. And now all of a sudden everyone's like, oh, the vertical application level, is gonna get disrupted because of course Google and OpenAI are gonna do that. And so the truth is no one knows what the heck is going to happen. And I think there are lots of people now saying actually like the value's all gonna be accrued to the players that already exist. And are there even large gains to be had? I do not take that view. I think that for sure those players will accrue tons of value. I still have held onto all my Google stock. and I'm banking on them pulling out. But at the same time, and my gosh, I would never bet against OpenAI. I do believe this is a platform shift, and I do believe that there would be incredible opportunities for huge companies to be built, and I do not believe it's a winner-take-all. So I really think that what we're seeing, it's really not AI, it's really the future of software. And so everyone's talking about how UX becomes the big differentiator. And to me, that's like such a crazy description of what we're talking about. It's a product experience. Like, of course a product experience is gonna dramatically change your adoption. It's not UX, it's literally like, that's what's innovative about ChatGPT. It's like a novel way for humans to interact with technology. That is just modern software, right? And modern software development that is underpinned by machine learning and large language models. And I think that is where the industry is going. In the same way that you might have seen in pitch decks, we're a cloud-based company, and that was like, whoa, cool. It's like an AI bounded company is just going to be a feature of the future. And what matters is what problem are you solving? Is it something that other people need and care about? How are you solving it? And are you well suited to solve that problem? Now I think where there is probably the highest risk of competition from incumbents is if you play in their area. So anything related to core BI, you know, spreadsheet type work, document stuff like Notion's playing in this space, Canva's gonna be playing in this space. Google and Microsoft are so well suited to play in this space. So it's just, there are areas that it feels like there's a lot of swarm. And then as anything, there are areas that people are, that startups are gonna go to that are unsexy, that the Googles of the world are not going to touch. There are going to be really niche applications. Someone mentioned a company that's doing simultaneous language translation and work for video. It changes the emotion and the intonation, etc. They basically are selling a SaaS product directly to movie studios, right? That's something Google's not going to do. And so like finding these applications that both are novel consumer or business experiences, but play in some of the white space is where I get the most excited.

I grew up in Seattle, so Bing was actually the default search engine of my high school because all of our laptops and computers were Microsoft donated. So it's funny to see that in the headlines again. But to your point, it's hard to predict. I know we're almost at time, so I'm going to pass the mic back to Claudia just to ask our final two questions for you, Jackie.

Jackie, thank you so much for being here and enlightening us on just this really unique point in time that we're at. But I'd wanna just look back a little bit. We ask this question to all of our guests, and that is, who's a woman that has had a profound impact on your life and your career?

I love this question because there are so many. I will give you two. I know you asked for one, but one is a woman named Caroline Vanderlip. She was actually my mom's best friend and has been a huge supporter of mine my whole life. Most notably, she was a large executive at, uh, leading enterprise companies and then left to go on a startup journey herself. She has since run 5+ startups as a CEO and co-founder. She is closer to my mom's age and she recently launched a new startup and is like hugely successful. She is fearless. There is nothing this woman can't do. I would bet on her any day. And she was not just an example for me, but I actually interned with one of her startups when I was in high school. And so that really was my first exposure to startups and just seeing someone who was able to navigate and build multiple companies in a repeatable way and do it while being an awesome person. And the second is one of my bosses at Google, one of the other amazing women who I got the pleasure to work with, a woman named Lindsay Lyle. Her husband at the time was leading the growth fund at Sequoia, and she was a director, then became VP at Google. She was leading a huge team at Helpouts, which is where I worked for her. And she taught me how to balance all this family shit. Every single trick I saw her and her husband Christopher do, I employ today with my husband. So we have like complete division of responsibilities. She was like very pro-division of labor. I don't do this. She does this. I do this. My calendar has every day, every trip, who's traveling where. That's just how I manage all the things I need to do with kids. Because he's going to be out of town and out of the country. It's like the practical tips and tricks of how you actually manage working in a really demanding job with having a family and multiple children and all of the things I now have to navigate.

Thank you so much for sharing both of how those incredible women have changed your life. Tactical advice is always great, but thank you all so, so much, Jackie, for being on the podcast, sharing a little bit more about your career journey, building Tribe, and all of the exciting things that are to come.

No, it was really fun to be with you. Congratulations to you all on maintaining your careers while also being founders of this incredible podcast and bringing insights hopefully to a much broader audience of people who will go on to do incredible things in tech and beyond. Pleasure to meet you and be part of it.

So appreciated. Thank you.

Thank you so much for joining us at The Room Podcast. If you want more from The Room every week, subscribe to our newsletter at theroompodcast.com/newsletter. We'll be back next week with a new episode Tuesday, 10 AM Eastern, 7 AM Pacific. See you in the room.

All opinions expressed by Claudia Madison and podcast guests are solely their own opinions and do not reflect the opinion of The5EC.

This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions.