How Gradient Ventures is Shaping the AI Startup Landscape with Eylul Kayin

Today on Equity, Mary Ann Azevedo sits down with Eylul Kayin, a partner at Gradient Ventures, to dive into the evolving AI startup landscape. The pair dig into what makes a successful AI startup, the importance of quality product offerings, and the fast-moving nature of AI innovation. Listen to the full episode to hear more about: Key challenges founders face, from building strong customer relationships to navigating technical hurdles. Gradient Ventures’ approach to funding and supporting AI startups, especially how to strike a balance between vertical expertise and rapid product development. Eylul's experience as a judge for TechCrunch’s Startup Battlefield 2024, and tips for entrepreneurs pitching their ideas to investors. And if you’re a founder interested in applying, the TechCrunch Startup Battlefield 200 applications are officially open — so be sure to check it out! Equity is TechCrunch’s flagship podcast, produced by Theresa Loconsolo, and posts every Wednesday and Friday. Subscribe to us on Apple Podcasts, Overcast, Spotify and all the casts. You also can follow Equity on X and Threads, at @EquityPod. For the full episode transcript, for those who prefer reading over listening, check out our full archive of episodes here. Credits: Equity is produced by Theresa Loconsolo with editing by Kell. We’d also like to thank TechCrunch’s audience development team. Thank you so much for listening, and we'll talk to you next time. Learn more about your ad choices. Visit megaphone.fm/adchoices

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Anthony Ha?

  This episode of Equity is brought to you by Schneider Electric. Schneider Electric, your energy technology partner.

• 0:17Speaker 01

  Hello and welcome back to Equity Tech Crunch's flagship podcast about the business of startups. I'm Mary Ann Acevedo and this is the episode where we bring on industry experts to help us explore a trend in the tech world and dive deep. I'm super excited to share today, we're joined by Ailul Khan, a partner at Gradient Ventures. Ailul, welcome to the show.

• 0:37Speaker 02

  Thank you so much for having me. What a pleasure and honor.

• 0:39Speaker 01

  Yeah, no, we're very excited. Now, for those listeners who aren't familiar, Gradient Ventures is a venture fund started by Google, it was about eight years ago, 2017, and it offers technical mentorship for early-stage startups focused on AI. So, you know, I guess you could say they were doing it before it was cool. Talking about visionary. So Gradient Ventures invests in what they describe as AI-driven startups across a variety of sectors, including healthcare, finance, transportation, and agriculture. The firm has managed over $1 billion in assets and invested in over 50, sorry, 150 companies since its inception. Is that right? Is it 150, Ailul?

• 1:20Speaker 02

  250.

• 1:21Speaker 01

  Ah, 250, okay. We must have had some old.

• 1:24Speaker 02

  We're a small but mighty team and a huge portfolio.

• 1:26Speaker 01

  That's a lot, yeah. So the firm typically makes initial investments ranging from $1 to $10 million focusing on early-stage seed and Series A. And I think this is an important thing to know, the firm operates independently from Google.

• 1:41Speaker 02

  That's right. We've been a part of the Google ecosystem since 2017. And while we don't have a direct strategic mandate, we do take advantage of the ecosystem resources, collaborate with various different alphabet function across GCP, DeepMind, so forth. But yeah, we are an independently run fund.

• 1:59Speaker 01

  But the startups are offered, to your point, access to Google's cloud computing infrastructure, data analytics tools, machine learning platforms, that kind of thing.

• 2:07Speaker 02

  Absolutely. As well as the mentorship that comes with being a part of the organization.

• 2:11Speaker 01

  Oh, right. Of course. Yeah, that makes sense. But you're new to Gradient. You joined last year, is that correct?

• 2:17Speaker 02

  That's right.

• 2:17Speaker 01

  Okay. And before that, you were an investor with NEA and SoftBank?

• 2:23Speaker 02

  That's right.

• 2:23Speaker 01

  Mm hmm. And so companies, startups that you've invested in include BRACs, which I've written a ton about, of course, Chime, Digits, ERGO, Flexport, NeoTract. Now, I assume all those were before you joined Gradient, is that?

• 2:38Speaker 02

  That's right.

• 2:38Speaker 01

  What are some investments you've made since joining the firm?

• 2:41Speaker 02

  So maybe I'll take a step back to talk about, you know, where I spend my time and what's the thesis that flows into that.

• 2:48Speaker 01

  Mm hmm.

• 2:48Speaker 02

  We like to back technical founders with a go-to-market edge. We've been, obviously, focused on the AI ecosystem for a while. Some of our early winners are like Lambda, Writer, Cray, but I personally like to work with founders that essentially absorb advancements in underlying infrastructure and turn them into enterprise-grade solutions that ultimately deliver real value. Honestly, I think I find it a bit silly to say we're investing in AI in 2025 because we've reached that point in the cycle where any new software company that's being built is really using or selling a product that has incorporated some AI functionality. But we want to find folks that are generally focused on selling to the enterprise and meaningfully adding value with short time to implementation.

• 3:32Speaker 02

  So examples of companies that I've recently backed, one of them is called Cascade. This is what I call like a level one employee automation that helps provide very personalized tailored questions to employees of large corporations, let it be publicly traded businesses or private equity backed. They started off with benefits extended across HR and they see themselves being pulled into other directions as well around IT procurement, even maybe legal. And the interesting value there is while taking advantage of ultimately a specialized AI solution, they have created an intimate environment for people to actually ask very personalized questions about. Issues in lives. So you can imagine you're someone who's considering taking maternity leave

• 4:14Speaker 02

  and you don't want to be elevating this immediately with your manager like I'd love to learn more about my benefits. So there's that interesting dynamic there, but the other funny part is not funny, but um I call it failing forward. A lot of the co-pilots that have a similar nature to cascade in the market, like the Sierra Zekagans of the world.

• 4:31Speaker 01

  Hmm.

• 4:32Speaker 02

  Everything kind of works, I don't know, fifty to seventy-five percent of the time, to be honest, and it's the nature of the technology we operate with, right? AI is different than software in that we have a non-deterministic system that works differently. What I've seen Cascade do really well is, you know, say the agent is unable to answer the question of the employee, then they have a ticketing system that ties in a human into the fallback system. So you get the question answered pretty quickly, but also you end up providing a end-to-end service that the enterprises really want. So that's one.

• 5:03Speaker 01

  I don't know. That's really interesting, though. When did you invest in that company?

• 5:07Speaker 02

  This was in end of summer last year.

• 5:09Speaker 01

  Okay, yeah, sorry to interrupt. You were about to tell me about another.

• 5:12Speaker 02

  So another one that we've invested in, and it's actually going to be launching pretty soon, I guess. So we're doing a an exclusive accidentally here is a company called First Work. This is a team that I genuinely really enjoy working with. The CEO has done strategy at Deliveroo before and the CTO and also, by the way, ran Remitly's APAC business to zero to eighty million. And the CTO comes from an amazing background from being a director of engineering, both at Deal and Rippling, having built out a number of the, you know, solutions before. They are building what I consider to be the part-time seasonal worker-facing version of an aggregated platform like Dealer Rippling. The difference is

• 5:52Speaker 02

  this ecosystem has previously been served by point solutions that are really focused on onboarding. There's a number of well-funded examples of, you know, Fountain, Travelas, Associates of the World. But what's really missing is having the expertise to build together these workflows that are really scalable, to be able to cater to the needs of these enterprises, but also think through the entire journey of a frontline worker from not just onboarding, which is a lot of background checks and stuff, but also thinking about managing the employees as well as thinking about creative ways of payroll, which fits into a new way of thinking around fintech as well.

• 6:25Speaker 01

  Well, we have to chat about that a little bit more later, but this kind of leads me to another question, though. I can imagine that you all are pitched like crazy from startups who are seeking to raise money. And I've said this many times before on the podcast, and I'll say it again. I feel like our jobs are a little bit similar in the sense that we do have to field a ton of pitches and kind of try to discern what startups are actually doing, something that's truly unique and innovative, and which ones are just kind of maybe using AI as a way to get our attention because they know it's such a hot topic these days. So I imagine you run into that quite a lot as well. So I'm curious, how do you address that?

• 7:06Speaker 01

  Like, how does Gradient evaluate the potential of supposed AI-driven companies in today's landscape? What criteria do you look at to say, okay, yes, this is truly unique. This is something different. How can you tell that from just, say, an email, for example, or a pitch deck?

• 7:22Speaker 02

  I mean, we went through a couple of years of thinking through an ever-changing AI infrastructure. And I think both builders and investors are circling back to the traditional questions we've asked during the heyday of SaaS. Like, is this ultimately a reliable, scalable, secure solution that helps me automate something in my company using the best possible infrastructure that's available to me at that moment? I think stuff like DeepSeek or the general degradation of these API calls has made app layer investing incredibly more interesting because every day we wake up and our infrastructure costs are down. But the customer relationship, the last mile, per se, in the enterprise of selling to a very specific customer

• 8:03Speaker 02

  that has a very specific workflow need, that continues to be the reason why companies generate revenue at the end of the day and scale and create repeatable net revenue tension driving businesses. I'll put a different spin on your question. A lot of the companies that we see are absolutely building at the cutting edge. However, their customers are not at the cutting edge. They don't have actually the right skill sets to, one, I'd say, be able to translate use cases into production-ready things. They also Don't necessarily have a clear understanding of the capabilities of the platform as well to devise the use cases themselves. So what I'm seeing more so is these cutting edge folks building almost like a consulting type layer

• 8:48Speaker 02

  to be able to sell their products to their end customers. So I call it the Palantir style, like the forward deployed software engineers, a lot of our portfolio companies, and by the way, I think OpenAI and others are deploying these practices to make sure that their solutions are properly adopted because the thing that people care about is like enterprises don't want to pay for technology that looks interesting and works 20% of the time. They want to pay for something that is reliable, works, and repeatable. And I think the issue that a lot of the companies, especially I'd say in the past few years on the app layer have faced is they get stuck in these P O C like demo cycles because it's so easy to put out demo that looks compelling.

• 9:32Speaker 02

  But it is way more difficult to build a company which has cutting edge technology that does something better than others, but also is able to sell, implement, do post-sales on a like enterprise grade level. So the answer to your question is that I think we always back technical founders, but we really want to make sure that we back folks that have one, a little bit of arbitrage and a different view about the industry they operate in, like understand the operational dynamics and have the skill sets demonstrated in some shape or form in their careers, in their vision and the people that they're able to attract to sit around the cap table or in the office with them. We look at those things to make sure that we back the right teams.

• 10:16Speaker 01

  So do you mean that some of these companies are actually kind of adding almost sort of an education layer in between the company?

• 10:23Speaker 02

  Absolutely.

• 10:23Speaker 01

  And their target customers so that their target customers actually truly understand what it is they're being sold and how to implement it so that they really can get the most out of it?

• 10:35Speaker 02

  Absolutely. And this is orthodox and again, serving at a house view, this is me personally making this judgment, but I think that's the right thing to do right now. One of the things a lot of the investors will have to grapple with in the years to come is there's a lot of folks that are going from zero to three, zero to eight in a year, the cadence of which we have not seen before, but we have zero evidence of what's going to happen when that P O C needs to convert into a full-time contract, when the second year is up and you have to renegotiate the contract. We have no evidence of how those companies are going to fare. We're not in the business of funding a company that's going to stick around for six months. We want six years, sixty years.

• 11:16Speaker 02

  Like, we want to build the foundations of an organization and a system that sells something that is useful.

• 11:21Speaker 01

  So what are the key things that get you excited in this space?

• 11:25Speaker 02

  This is one that I'm personally trying to navigate as well. I think the really well-covered V C favorite strategy has been to focus on really vertical stuff, like the ideas, you know, get really, really good at a very generic vertical, build your go-to-market around it, build your brand around it. The way folks like Harvey at Bridge have obviously scaled is a good example of that. I'm less worried about exactly what the use case is, and again, this is the more unorthodox thing, but I really care about backing startups that really care about the quality of the offering that they're pushing forward and that they retain really, really, really good customer interactions. And sometimes that lends itself to vertical solutions and sometimes general across horizontal. And the other thing to mention is the fast shipping culture.

• 12:07Speaker 02

  Some of the best companies I work with, let it be on my angel portfolio, Follow Eyes One, that they actually just announced a Series B. I think they're definitely going to be doing a C pretty soon. That's a bombastic team that went from one and a half million run rate to more than forty million in a year. Like, those kinds of folks are, it's almost like it doesn't even matter what they do, that what they do is really compelling, but that team is crazy in their culture of how fast they push out their new solutions. They they tap into models before they even launched and find a way to host them. Like, those are the kinds of people that I like to work with.

• 12:41Speaker 01

  So what should early-stage founders building in AI be thinking about, in your opinion?

• 12:47Speaker 02

  Traditional ways of thinking around barrier to entry doesn't exist anymore. You know, just being first to something doesn't help. Frankly, arguing that you're, you know, have a very different technical edge, I don't think is necessarily the right way to go about it either. They should definitely have a very, very clear perspective on what they want to build and what they want to do for the next 12 months. Fully recognizing that tech cycles are changing way more rapidly than I have seen in my lifetime. And I've been doing this for a decade. So things will change, but you need to be having a plan A, plan B, plan C in terms of absorbing what is the new functionality that comes along.

• 13:29Speaker 02

  Let's say you were rag-based tooling that was building last year. Like, how are you going to integrate a lot of the new, what I call, agentic functionality, tool calling, to make your product more and more capable? It doesn't mean that you have to abandon what you're doing. You have to find a way to deepen your customer relationship by taking advantage of what's latest and greatest. But always focus on the customer, not on the technology. We talked to so many founders that have a technology, don't have a solution. Given our stage, we do pre-seed seed. And we'd love to work with them if we can be helpful in many shapes and forms. But frankly, it's having a perspective vision. And honestly, reach is also really interesting.

• 14:08Speaker 02

  Like, I mean, following the lovable bull story and the number of competitors that have come up in that category. I find it so interesting how having community relationships, but also having just like longstanding brand recognition makes such a big difference in attracting the right customer to you at the right time.

• 14:27Speaker 01

  Yeah, that makes sense, actually. And I can see that just from companies that I've seen grow to be successful. What would you say are the most important technical and non-technical challenges that founders should be prepared for when they're scaling?

• 14:42Speaker 02

  It's being disintegrated. So the basic example, again, maybe overdone, is the Jasper story of her building something that is super useful, but it's very adjacent. To what a large organization has in their product pipeline. That's something that's quite scary and concerning. Doesn't necessarily mean that you can't prosper. Obviously, you know, perplexity operates in a very, very adjacent category to OpenAI and many of the other really old fund the fears. And, you know, I think that's a great product. So those that can execute through it, I think, will. But making sure that you carve yourself a niche is great. I think it puts, by the way, the venture community in a funky place because then we're all focused on these more smaller vertical solutions that, I don't know, are, is it easy that it's going to be a hundred billion company?

• 15:25Speaker 02

  Probably not, but is this person going to completely crush it and execute through it? And it's going to be an actual business? Yeah, but I think you may end up seeing that a lot more funding goes into that category, especially with the multi-stage funds. We'll see if that's the right choice.

• 15:38Speaker 01

  Yeah, I mean, I can see that. I think that there's validity to that, that maybe a company is not necessarily going to appeal to the masses, but it can appeal to a specific demographic enough to be very successful just in and of itself. So not necessarily going to be of massive scale, but grow big enough to be very successful. So I don't know, there's different definitions of success, but I can see where there's some validity to that.

• 16:10Anthony Ha?

  What moves our world forward? Energy. History has been shaped by it, revolutions won with it, and progress dependent on it. For 190 years, Schneider Electric has been a leading force in this story, creating the technologies that harness energy and transform the competitive landscape. And today, in the dawning era of energy and industrial intelligence, Schneider is helping customers build more efficient, resilient, and sustainable operations across every sector, from data centers to homes, from buildings to industry. Schneider Electric, your energy technology partner. Discover more at se.com.

• 16:48Speaker 01

  We're also seeing a ton of money thrown at AI labs or companies before there's even a tangible product. And I think we've seen a bunch of startups that are founded by OpenAI LMS, for example, and I'm not going to name names, but you know, just like raising money really, really early stage. And that kind of freaks me out a little bit. One thing, this reminds me of like the days of 2021, you know, covering fintech at that time. And I saw a lot of money thrown at companies that just really were so early stage. And I remember even thinking, like, how, you know, how could, how can these companies be raising so much when they really haven't got anything very proven, no tangible product, no traction,

• 17:31Speaker 01

  you know, just this idea? And I'm having flashbacks. So what do you think about that? I mean, what's going on? Are VCs just kind of investing in the promise? Or what?

• 17:42Speaker 02

  Yeah, so very stingy funds. We're very small. We write early-stage checks. That's not the game we play. I have all the respect for folks that are able to see, I guess, maybe what we sometimes don't get to see. It's just not a game that we get to play. So not something that I'd be very thoughtful at answering. Let's just leave it at that.

• 18:00Speaker 01

  Okay, that makes sense. Well, you mentioned enterprise earlier, and I saw a blog post that you wrote recently titled, "What Does It Take to Win an Enterprise AI?" And you kind of outlined that, I think it was a three-part series, and sharing your perspectives on building, selling, scaling AI applications for the enterprise. Can you talk a little bit about that?

• 18:21Speaker 02

  Yeah, I think, again, I'm a software-crowned history nerd. I care about ancient civilizations, but I also care about history of venture and history of software, too. A lot of the reason why I think SaaS is a very interesting cycle and period is not just because it changed the way we build workflow automation for the enterprise, but also the way we think about wholesale relationships. So this three-part series, which only the first one has been published, hopefully the other two will come out soon. Now, now you've put me on alert. I definitely need to make sure I finish my writing. They're going to be covering building, but also what I've learned in terms of talking to smart folks within our portfolio or External about what it takes to sell and then what it takes to do the post sale.

• 19:01Speaker 02

  Not to give too much away, but I think tying back into the forward deploy entry question is on the post sale side. It's important for people to understand, for example, the value they're getting out of the solutions that they're buying. And I'm talking to a lot of folks that actually spent this proportion amount of time coming up with KPIs that help people understand the value they get out of these solutions. So a product that offers to help your workflow 20% of the time doesn't mean that it's going to generate 20% more revenue or 20% less cost. Traditional software is harder to pin that, but especially as agentic workflows come in, we're going to be in a completely different universe where we can outsource end to end workflows, like fully replace labor in obviously well-defined terms.

• 19:44Speaker 02

  So the way you think about selling is going to be completely different because of the ROI that you're able to articulate like very easily. So that's something I'm pretty excited about and there's a lot of folks in our portfolio doing thoughtful work around ROI analyses as well. But also there's a lot of emphasis on post-sales to make sure that the end users, as well as the company is fully aware of the way products are being implemented, utilized and the value that they're creating. So we're trying to track those as thoughtfully as possible to devise different pricing strategies. For example, that could be favorable for both the customer as well as the company themselves. So those are some of the things I'm going to be talking about in the upcoming weeks.

• 20:23Speaker 01

  Okay.

• 20:23Speaker 02

  And maybe there'll be some interviews too with some of my favorite

• 20:26Speaker 01

  Yeah.

• 20:26Speaker 02

  CSM leaders and sales leaders.

• 20:28Speaker 01

  Well, keep an eye out for that.

• 20:29Speaker 02

  I'm gunning for your job, Mary Ann. Look at that.

• 20:33Speaker 01

  Go for it. Go for it. Yeah, actually you had mentioned earlier that you described your firm as, I guess you said stingy, but really, I mean, how many companies per year would you say gradient invest in?

• 20:44Speaker 02

  Well, we don't think about the number as much, but let me take a step back. We're just seven investors. We're a very eclectic bunch. Some of us have like zero days of college education, think like Thiel fellows, super entrepreneurial people. And some of us have double PhDs. They come from very technical backgrounds. And I'm smack in the middle, barely graduated from undergrad, have a more finance background. Each of us brings something completely different to the table. Each of us follow slightly different trends and we don't necessarily have a mandate to deploy a certain amount of capital per year. We just want to be taking advantage of all of our network's resources, understanding where we are in the system to be very thoughtful about deployment. But it's fair to say that while we lead, we are a high-volume platform, which means that with a small team,

• 21:28Speaker 02

  we do get to see a lot of companies. And I think that's been an interesting way of getting a pulse of the ecosystem. I think that ends up becoming a value add that we provide to our portfolio companies as well because we get to see so much of the best practices which are evolving incredibly rapidly.

• 21:42Speaker 01

  I'm sure. Well, it's fitting actually that we're recording this today because you recently served as a judge, sorry to change topics just a little bit. Startup Battlefield at Disrupt. And today it was just announced that applications for Battlefield for this year's Disrupt are officially open. So that was this past year, right? That you were a judge?

• 22:02Speaker 02

  Yeah, it was an absolute dream come true. I've been wanting to do it since watching the first season of the show Silicon Valley. And the whole experience was exactly as I imagined it.

• 22:12Speaker 01

  Really? That's cool. That is so cool. I think everybody feels like Battlefield is, it's a very special part of Disrupt. It's really incredible watching so many startups with so much promise, sharing their stories and then, you know, having the chance to evaluate and seeing them go on to be, some of them to be very, very successful later on. So what would you say, having been a judge, what advice would you offer for those pitching, pitch advice or general advice for new entrants?

• 22:40Speaker 02

  First of all, I think it's a great opportunity to put yourself out there, get your name out. One of the biggest things any startup needs is leads and customers. So obviously Disrupt is an amazing brand and Battlefield is a cornerstone. It's literally the history of the Silicon Valley since after dot com boom, probably. And year after year, it's showcased a lot of the high-quality startups. But also, for example, I, I got to share the stage with a bunch of awesome folks, like, you know, Jonathan and Christine. And by the way, our session was sandwiched between Vinod Khosla and Foster Sisters, which I don't think happens very frequently. So it's a, it's a really awesome place to be around.

• 23:17Speaker 02

  Among our cohorts, one of the companies actually ended up staying in touch with me and we started some unofficial mentorship relationship as well. So it's an excellent way to meet investors, you know, addition to customers.

• 23:29Speaker 01

  Yeah, no, that's awesome. And before we even started, you mentioned again, you are kind of a history buff. And I can relate to that. I was a classical studies major, among other things, in undergrad. So I think we have that in common. But you mentioned that, like, you kind of looked at the history of, is it disrupt?

• 23:46Speaker 02

  Yeah.

• 23:46Speaker 01

  Or both?

• 23:47Speaker 02

  Yeah, I thought, I actually didn't know that this is, this has been around since 2007. And I looked up the 2008 show to prepare for this over the weekend. And the judges were really familiar names, like Mark Andreessen, like Manyhaf. Actually, Chad Hurley, which is the YouTube founder, Kristof Off, the CEO of MySpace. There was a lot of really, really cool people. And the winner was none other than David Sacks with Yammer. And I have actually a video receipt of him saying that he thought it was really cool that Mark Benihoff liked his product. Which is so funny, because Mark then proceeded to try to buy Yammer. And when he failed, he launched a clone of the product. You know, it's a whole story there. But I thought it was even funnier that Thibet was the runner up, which is, by the way, a company that

• 24:31Speaker 01

  Yeah.

• 24:31Speaker 02

  ended up peaking at like 10 billion, 15 billion market cap, maybe, was sold even at a higher price than what Yammer was.

• 24:38Speaker 01

  Acquired by Google, right?

• 24:39Speaker 02

  Yes, that's right. That's right.

• 24:41Speaker 01

  Yeah.

• 24:41Speaker 02

  And then Dropbox didn't even make the cut. I ended up watching Drew Houston kind of mess up his demo, maybe that's why. I don't know if I'm supposed to say this on this podcast, but he says the F word against the microphone quickly on YouTube. But anyway, so he didn't make the cut. Obviously, he did really well in Life After.

• 24:58Speaker 01

  Yeah.

• 24:59Speaker 02

  And the part that I loved the most about that session was that there's a couple who fell in love on the show Biggest Loser. They made the final five when Dropbox didn't. So the point I'm trying to make is the judges make imperfect calls, but you know, that cohort at least did a really good job of predicting the future leader. So, I mean, I recommend everyone who have any interest to go apply. You never know. You never know. You could be the next, you know, David Sacks or Drew Houston.

• 25:23Speaker 01

  Yeah, you do never know. I love that you looked that up and now you made me want to go do it as well. So unfortunately, it looks like we're out of time, but this has been so much fun. I really appreciate your coming on and just talking with us and talking all things AI. Your investment thesis and sharing that super fascinating. Little tidbit, which, like I said, I did not even realize about Battlefield and Disrupt. So I would love to give our listeners a way to connect with you, though. Where can they connect with you or find your work online?

• 25:50Speaker 02

  You can find me on Twitter, LinkedIn, Grading website. We can put links.

• 25:55Speaker 01

  How can they find you on X? What's your handle?

• 25:58Speaker 02

  Follow me at @EylulKyan.

• 26:02Speaker 01

  Perfect. Easy enough. So thanks so much again for joining us on the show. And to our listeners, you can find me on X at Bay Area Writer, even though I no longer live in the Bay Area, and Equity at EquityPod. See you next time.

• 26:17Rebecca Bellan?

  Equity is produced by Teresa Locan Solo with editing by Kel. We'd also like to thank TechCrunch's audience development team. Thank you so much for listening, and we'll talk to you next time.