Venture Everywhere Podcast: Omar Haroun with Scott Hartley
Omar Haroun, co-founder and CEO of Eudia chats with Scott Hartely, co-founder and Managing Partner of Everywhere Ventures on episode 75: Augmented Intelligence with Eudia.
In episode 75 of Venture Everywhere, Scott Hartlery, co-founder of Everywhere Ventures and MP of Everywhere Ventures, talks with Omar Haroun, co-founder and CEO of Eudia — an augmented intelligence platform transforming legal departments from cost centers into strategic drivers. Omar shares how he built Eudia to provide legal teams with portfolio-level insights and adaptive AI agents that go beyond automation to drive meaningful business outcomes. Omar also discusses Eudia’s approach to rethinking the economics of legal work—addressing systemic inefficiencies, moving beyond billable hours, and expanding access to quality legal support.
In this episode, you will hear:
Viewing legal risk and decisions through a portfolio management lens
Leveraging proprietary enterprise data to customize AI agent behavior
Positioning legal departments as drivers of revenue, not just cost centers
Automating high-volume tasks like contracts and NDAs
Reducing hallucination risk with deeper knowledge system integration
Confronting outdated legal incentives to expand access to legal services
If you liked this episode, please give us a rating wherever you found us. To learn more about our work, visit Everywhere.vc and subscribe to our Founders Everywhere Substack. You can also follow us on YouTube, LinkedIn and Twitter for regular updates and news.
TRANSCRIPT
00:00:00 VO: Everywhere Podcast Network.
00:00:14 Jenny Fielding: Hi, and welcome to the Everywhere podcast. We're a global community of founders and operators who've come together to support the next generation of builders. So the premise of the podcast is just that, founders interviewing other founders about the trials and tribulations of building a company. Hope you enjoy the episode.
00:00:33 Scott: Hi, everybody. I'm Scott Hartley, co-founder of Everywhere Ventures. I'm here with one of my very good friends, Omar Haroun. Omar is the founder of Eudia, which is an augmented intelligence platform going for legal services, primarily with Fortune 100 companies.
00:00:47 Scott: Omar is not only a person that I've been friends with for fifteen years, back to the dual degree days at Columbia where you pursued business and law, but you were an epic basketball player, studied politics, philosophy, and economics at Oxford and at Berkeley before founding Text IQ.
00:01:04 Scott: And you were very early to the AI revolution in the creation of Text IQ, which you sold successfully and built a great company with one of our mutual friends. I'm incredibly excited to have you on the Venture Everywhere podcast and talk a little bit more about your new company.
00:01:19 Scott: You've already, in a very short amount of time, raised $105 million series A led primarily by General Catalyst. We were very fortunate to be able to participate early in that journey. Omar, welcome to the podcast.
00:01:31 Omar: Thank you so much, Scott. Really great to be here. It's always fun to get together with a friend too. Nice to see you.
00:01:37 Scott: Totally. I reflect fondly on the moments that we've been able to share together over the years, not just on the startup side, education side, but personally and everything. So I'm very thankful for your friendship. I'm very jealous of your surfing ability and your basketball ability and your height. But otherwise, let's talk about AI.
00:01:54 Omar: That's great. Let's dive in.
00:01:56 Scott: One of the themes that I think we've often riffed on and talked about, which is fascinating and is now coming really to the forefront of the public debate is around this nomenclature of AI, of artificial intelligence.
00:02:09 Scott: Fei-Fei Li, who ran this vision lab at Stanford, talked about how there's nothing artificial about artificial intelligence, and it's really this misnomer.And it's really about intelligence amplification or IA, or it's about augmented intelligence, AI, with some different wrappers around it.
00:02:26 Scott: I think we live in this world where a lot of people are knee-jerk reacting to the craze of AI. As somebody who's been building companies in the space now for over ten years successfully with exits and big fundraisers, talk a little bit about your vision about supplementing humans and what augmented intelligence means to you?
00:02:45 Omar: The point that Fei made is a really valid one, and she made that point before the ChatGPT moment. So some of us who have been using these technologies or exploring AI for a while probably have a more grounded view.
00:02:59 Omar: Post-ChatGPT, there was just a sudden complete explosion of excitement, adoption, all of which is great. One thing that I've observed is because that first experience many people have with AI just feels so mind blowing, they almost just start creating very false expectations around what the technology can do.
00:03:20 Omar: And to be fair, those of us in the tech industry who are marching towards AGI as our North Star, which one of the definitions that was recently used by OpenAI was machines replacing humans at most economically relevant tasks, is also a very dire future in my mind. And even if it's possible, it's not one that necessarily sounds like the world that I'd be excited to inhabit.
00:03:41 Omar: When I think about augmented intelligence, it almost goes back to the Minsky-Licklider debate when AI was even first coined around. Is the fundamental purpose of AI to replace people and make them unnecessary? Or is it about how machines can work with humans to ideally have both achieve something that wasn't possible independently?
00:04:02 Omar: You can probably tell from the way that I'm talking which side of that debate that I'm on. I'm much more in the Licklider camp. But really if we think about augmented intelligence rather than artificial intelligence, what it could mean and should mean is that we actually now have an opportunity to completely change how we work.
00:04:19 Omar: Almost two years ago exactly, this Goldman Sachs report came out that was pretty much read by every Chief Legal Officer in the Fortune 500, which argued that 44% of legal tasks can now be automated. That caused a lot of fear and panic because many people misinterpreted that report to mean that 44% of legal jobs can now be eliminated but, actually, what it said was tasks.
00:04:40 Omar: Our experience has really been now having two years of building products in this space. That the automation really is at the task level, not at the job level. What that really means is any workflow that a human engages in has some percentage of tasks that can now be automated, many that can be partially automated, and many that can't be automated or that even if they could be we'd actually rather have humans doing it for a variety of reasons.
00:05:02 Omar: It's really interesting. But augmented intelligence is all about how do we, as humans, achieve what may be infinite potential with the help of this technology and focus more on that as opposed to how do we get rid of humans or make them irrelevant.
00:05:14 Scott: Absolutely. It's so fun to see the debate for you having been building in the space since 2014 or even before that. And for me having been writing in the space since 2016 when I wrote it, 2017 when it came out.
00:05:27 Scott: And going back to the debate of Minsky and Licklider, for people that aren't familiar with this, it's worth a query on ChatGPT or a Google search to learn about these debates that were happening around MIT 50, 60, 70 years ago around human-computer interaction, this supplementing of humans through intelligence augmentation or augmented intelligence AI versus artificial intelligence AI.
0:05:50 Scott: And to your point, one of the studies that I often pointed to in the past and still really allude to with the rise of Martin Ford's Rise of the Robots, followed by an Oxford study that said roughly half of jobs were at risk of machine automation, followed by a McKinsey Global Institute study that delved into, to your point, tasks versus jobs and really looking under the hood.
00:06:11 Scott: Across a number of different jobs, what's the breakdown of tasks? Tasks fall into routine, non-routine, manual, and cognitive. Along those vectors, you have routine tasks that are manual. Those go to automation through robotics. Routine tasks that are cognitive. We used to call it machine learning. Now we call it AI.
00:06:29 Scott: But this idea that certain repetitive tasks and routine and rote tasks that are manual or cognitive can be automated away eventually, but there's still a substitution. In fact, there's still a question of cost. There's still a timeline duration and a think through on that.
00:06:44 Scott: But as you're going after this market and as you're interfacing with chief legal officers, what are some of the lowest hanging fruit boxes of tasks that you think about? Because to that report, it's not as if jobs are just disappearing.
00:06:57 Scott: It's the very specific hyper rote and routine tasks are being iterated away and are enabling these firms to become stronger. They're able to keep the same inputs and now generate 10X or 100X the output.
00:07:10 Scott: You start to think about a modern law firm or a modern legal department of a corporate entity, Fortune 100, and suddenly they can really supplement that team, keep cost lean, but really massively impact output. So how do you think about this as far as the lowest hanging fruit and go-to-market?
00:07:26 Omar: One thing that's really been fascinating about being on this journey is even though billions of dollars are being spent in arguably avoidable legal expenses now, especially with expensive outside counsel who doesn't have the right economic incentives. I think the reality part of why this industry hasn't changed is at least on the business side, it's still a very small percentage of overall spend for any company.
00:07:51 Omar: I got frustrated when we had to spend $60,000 in our series A legal fees when that feels like a thing that should at this point be largely automated and at least significantly reduced in price. But even for us, when we're now on a path to become a multibillion dollar company, it's not a huge expense in relative terms.
00:08:08 Omar: The same thing happens where even a company that's one of our customers is doing close to $200 million dollars in revenue, they may be spending a few hundred million dollars on legal. So in absolute terms, it's a lot. But in relative terms, it's not. The reason I point that out is to really change behavior and make an impact.
00:08:22 Omar: But when I think about the lowest hanging fruit, it's really about not just saving a few dollars in what's ultimately probably a rounding error for most companies' overall budget, but how do you actually give the company a strategic advantage in some way?
00:08:39 Omar: What's interesting about legal is even though it's perceived historically as more of a cost center, it's sitting on so much valuable data. When you think about the scenarios where legal gets involved one way or another, it's usually where there's a lot of risk and a lot of opportunity depending on how things pan out.
00:08:56 Omar: One of the surprising things is the way that our technology is being used and where our customers are most excited about how it's being used is actually helping the company gain some strategic advantage, not only on that individual legal issue, but also more broadly.
00:09:10 Omar: Now on the low hanging fruit side, what we've thought a lot about is this market's moving so fast. The technology's evolving so quickly that as a startup dealing with these giant customers who have extremely sensitive data and sometimes a 12-month long procurement process or infosec process, how do we think about really quickly breaking in and showing what we can do and building some trust?
00:09:32 Omar: So for us, we have two dimensions. One is impact, and the other is data feasibility. Ideally, we find an entry point where the impact is real and as high as possible. But even more importantly, the data feasibility is actually not gonna hold us back for 18 months.
00:09:48 Omar: That's actually meant on the low hanging fruit side. I would say thinking about use cases or initial entry points where either the data is less sensitive or we can come up with some way of just getting started because once somebody sees what it can do, there's no turning back.
00:10:02 Scott: I love that thinking about, in the go-to-market, having these two entry points and from a sequencing standpoint, both are available. So either data access and availability as being a wedge to come into a corporate relationship or scale of impact and diving into scale of impact.
00:10:17 Scott: To go back to that earlier conversation we had about this intelligence augmentation, it's this dual go to market that companies can think about. And so companies can think about, “Okay. With these new tools, I could cut my inputs and I could generate an identical output on way less cost.” So that's a cost saving, skinny approach.
00:10:36 Scott: Or there's, “I could maintain my inputs. I could access this new technology, and I could 10X or 100X or 1000X my outputs.” So this bifurcation of companies opting for cost savings, going skinny, or output generation going strong. In a competitive market as we would expect, most companies will opt for strong.
00:10:56 Scott: As you're wedge going into these companies to be able to say, “Look, here's a process. Here's a cost center within your organization. That's the legal department. If we could turn this into a revenue generator that 100X’s your output and your efficiency or on the margin, saves you a few dollars here and there.”
00:11:12 Scott: But between those two sides, it sounds like you guys are really focused on turning legal departments into revenue-generating machines and helping these companies, not obviate and do away with their legal departments, but actually to supplement and enhance and augment these legal departments to expand the pie.
00:11:29 Scott: I tend to think of the two sides of the world of transactional lawyers as maybe being more playing offense and at least within companies, litigation folks playing more defense. How do you sell in? Who are the right decision makers or how do you approach that?
00:11:42 Omar: One, we're building a platform, not a product. What I mean by that is we looked at what are the humans who are involved in legal departments doing, and that's basically some combination of summarization, drafting, risk assessments, also talking to colleagues or negotiating, et cetera.
00:12:00 Omar: Many of those tasks can now be automated. A generic agent may never summarize something to the level of accuracy or satisfaction that a human expert who's doing that work can do but over time, it can start to really learn how the human does it and get pretty close.
00:12:15 Omar: By thinking about it more as we have this platform of agents, that without proprietary data and institutional knowledge, are very limited. With those two things, it starts to get much better and really starts to learn how that company operates. And then it becomes this major unlock for the people that are doing the work.
00:12:32 Omar: It's meant that we're not limited to any one use case. Even the term use case, I don't think really applies in the same way anymore in the AI native way of developing products. We're not necessarily looking to build something that automates everything for one use case.
00:12:46 Omar: It's more across horizontally the entire legal back office function. What are all the activities that do have some augmentation potential? And that's pretty much all of them. So it starts to become almost horizontal within the vertical. And then we can go really vertical where we have a lot more reps. We've now seen this as a very repeatable problem across different companies and departments.
00:13:07 Scott: Within some of your key clients, let's say Duracell or Cargill or some of the big guys that you work with, within the spectrum of legal tasks that these guys have to perform, what's the breakdown? Is it NDAs? Is it contracts?
00:13:18 Scott: Maybe you could walk through a little bit of what do these companies typically have to deal with that lead to these 100+ million dollar legal budgets that companies are spending on law firms.
00:13:27 Omar: To your point, it helps maybe to look into the specific practice areas. So if you think about the transactional lawyers, their job is to help support growth, sales, and guard against risk. But first and foremost, they're typically reviewing contracts and helping to negotiate deals on some level.
00:13:47 Omar: On that side, I would say it's closer to what you were getting at, which is that the revenue drivers, maybe the holy grail, are one example. But even leading up to that, there's a lot of examples of where many of our customers have just been in reactive mode since legal departments came into being where everybody's just overwhelmed and drowning in the next deal, the next litigation, the next patent filing.
00:14:08 Omar: They haven't had a lot of time to just even stop and think and reflect on, for example, if we spend six months negotiating limitation of liability and we're pushing really hard to have it be under a certain cap. What's the worst that's ever happened when we've agreed to a higher cap? Many of them have never asked that question.
00:14:23 Omar: A lot of the CLOs that I work with are asking that question, and we're helping them answer that question by sharing, guess what? Nothing's ever happened. So maybe you shouldn't spend six months on that one term. Maybe it's actually okay to let that go. If the company were to close that deal in two weeks instead of six months, there's huge other benefits to that, thinking about risk on more of a portfolio perspective.
00:14:43 Scott: On that front as well, in the interactions that I have ever so frequently with attorneys that we work with, there's always this bifurcation of business points and legal points.
00:14:53 Scott: In some ways, what you're doing is turning this on its head and making business points the central function of legal departments rather than navigating precedent, navigating legal points, or even worse than that, syntax of how should it be written with the actual implementation of pen and paper.
00:15:12 Scott: So it's moving away up the stack, so to speak, from the syntax of would versus should versus could in the document versus legal points of what's been done or how it's been navigated from a legal standpoint to business points leading the conversation.
00:15:26 Scott: To your point, saying, actually, let's look historically, probabilistically at outcomes and various things from a data driven standpoint. Let's interpret that from a business point of what can drive revenue to your company and what's really worth the six month endeavor of your legal team or not. Let's let business points drive not legal points and certainly not syntax.
00:15:46 Omar: Exactly. The good news is the best in-house lawyers already operate this way, but they haven't necessarily had this superpower until now. Because if you think about the data that legal teams tend to spend a lot of time generating, reviewing, et cetera, so things like contracts on the transactional side, it's really an asset for the company as well as a liability.
00:16:05 Omar: If you look at how the world's best asset managers operate, think about Charlie Munger, Warren Buffett, they're literally taking every investment and thinking about it on a portfolio level. What's the cost of capital? How does that compare to the return?
00:16:17 Omar: But when a company has a new customer contract, up until Eudia comes into the fold, their historic way of doing it is almost as if they've never seen it before and its own thing. Whereas there's a lot of value in just really even thinking from a more portfolio perspective. Once you do that, it actually changes your behavior in terms of how you do the legal review.
00:16:35 Scott: I love that it's enabling companies to see the forest for the trees, not get stuck on the implementation of this single contract. I love that metaphor of portfolio approach versus one stock in one little corner of your portfolio. To be able to build and construct and lead and generate an outcome that's at a high level, you need to be able to see the whole picture. Maybe you could talk a little bit about the name Eudia as well.
00:16:58 Omar: Eudia is a neologism, but it's derived from eudaimonia, which is the ancient Greek for people achieving their highest good, which is actually our mission as a company.
00:17:07 Omar: The etymology is cool because, eu- means good or something positive, and -dia actually refers to transformation. What we believe we're actually embarking on is this positive transformation, not only for our customers' departments, but also when you look at the legal industry.
00:17:22 Omar: Part of what really drew me to this and why I'm making this my life's work even though we had a good financial outcome with the last company's exit is we're still living in a world where 90% of people who need a lawyer can’t afford one. Many Americans are one legal event away from bankruptcy and it's really not because it needs to be that way.
00:17:36 Omar: It's really because we just both have this entire system that's propped up by perverse economic incentives, which really today, if you're at a traditional law firm and you're a 10X lawyer, you make 10 times less money. So the whole model is just not really designed, from an ecosystem perspective, in a way that it encourages the use of technology and access to legal services.
00:17:56 Scott: In all other aspects of life, we go back to the 1960’s cartoon and George Jetson, you have moving sidewalks, moving carpets. We always have had this obsession with efficiency.
00:18:06 Scott: But to your point, within the legal industry where it's billable hours, the 10X lawyer making 1/10th the money because they bill 1/10th the time, it is completely backwards to the way that companies or individuals want this to function. So you guys are really an injection of new ideas in the space.
00:18:23 Scott: To shift gears a little bit, one way that we invest and one way that we think about the market often is there's the shiny object of, I call it the A-side of the record that everyone's focused on and then there's this underbelly or the B-side of the record that's the flip side.
00:18:36 Scott: So in this generative ability of AI, there's also this darker side of hallucinations or cybersecurity. We've invested a lot around permissioning, identity management, a veracity of identity, veracity of who's doing what, human in the loop to put an audit trail in and around AI.
00:18:55 Scott: But as you think about some of the high profile cases of legal hallucinations that caused a law firm a $50,000 fine and somebody getting their license suspended for a year, the B-side of the record, how are you guys thinking about the dangers, or what are the threats that keep you up at night?
00:19:11 Omar: I think this is a huge part of why we formed the company. Ashish, my co-founder. He had actually built Search from scratch at Apple. He led conversational AI at Amazon Alexa and then was a founding engineer at Google. But most of his bread and butter is knowledge graphs, knowledge engines, building a knowledge platform.
00:19:29 Omar: The naive RAG techniques that everybody's been touting aren’t sufficient to address that risk. From a technical standpoint, I would say we felt that we had some unique technical insights to help address the concerns around things like hallucinations, which unfortunately or fortunately, are a property of large language models.
00:19:46 Omar: We actually like hallucinations when it's a creative or some example where you want the machine to hallucinate but we don't like them when it's citing a legal case that doesn't exist.
00:19:53 Omar: Technically, we've been very excited as a team, passionate, have a lot of engineers that are actually just dedicated to that. Not so much the AI piece, but how do you actually combine AI with knowledge to really go deeper than RAG to solve some of these problems.
00:20:05 Omar: The other part of this is, ultimately, with augmented intelligence, our problem statement is how do we turn this human into a 10X or 100X human, not how do we get rid of the human. A lot of that comes down to a little bit of training and education on helping a person whose work is transforming, wrap their head around how to think about that.
00:20:24 Omar: I wouldn't say we've completely solved this problem. But the human machine interaction and how the human needs to adapt to that workflow is also really critical. What we're starting to see with artificial intelligence is a lot of false promises and then a lot of risky overreliance on what the LLM can do, which is both on the machine and the human.
00:20:47 Omar: But it's really just collectively on us not doing a good enough job of actually flagging that there are significant limitations to this technology. We have to really change how we work in a way where that verifying step is actually a big part of the process as well.
00:20:49 Scott: Something that just popped in my mind is as you were talking is going back to the board game of Go and the program AlphaGo, which played, I believe the gentleman's name was Lee Sedol. This is probably almost ten years back, where AlphaGo was able to beat a human.
00:21:14 Scott: Go is an infinitely complex game, where if you just tried to brute force it with the cognitive abilities we have with computers, you can't do it. So it actually has to get to the frontier of intelligence.
00:21:25 Scott: But I remember in the case where AlphaGo won the match, there was effectively a hallucination at the last move where the computer had gotten to a limitation of being able to brute force the game cognitively, and then deviated in this unexpected way and ultimately beat the human.
00:21:41 Scott: The outset of this AI craze was in fact a hallucination that just confused the human to the point that the machine won. Early in this incarnation of AI, hallucinations were almost lauded as breakthroughs in intelligence.
00:21:55 Scott: Whereas now, when you need fidelity to be as close to 100% as possible and you're getting 99%, and then the machine just makes up a historical precedent to win the case because it thinks that's the outcome is now a liability.
00:22:08 Scott: It's so interesting that it went from conversations about these breakthroughs to now how do we navigate these and how do we feed things back into an LMM maybe multiple times to get a number of answers and look at the variance of those answers.
00:22:21 Scott: If the variance is too high, you might say it actually has no clue what it's talking about. This seems like a hallucination. Let's not use this. Or actually five times in a row got the exact same answer, therefore, it might be a high conviction right answer.
00:22:33 Scott: But some of these new ways that people are trying to get from 99% to 99.9%, what are the things that you're reading or talking about or debating internally?
00:22:43 Omar: One thing that we're finding is as knowledge work gets rewired and as the role of the lawyer goes through this fundamental change, hallucinations can be very good.
00:22:56 Omar: One observation about lawyers, having now spent a decade working very closely with many of them, on the one hand, they demand 100% accuracy. On the other hand, they're highly subjective themselves.
00:23:07 Omar: You'll notice people who get trained at law firms, especially on the litigation side where you’re doing a lot more writing, their writing style will very closely mirror whoever the partner is that trained them.
00:23:16 Omar: You almost have these different partners, all of whom might be award winning litigators who have completely different styles and approaches to writing. It's not one's objectively right or wrong. They're mostly just subjective ways of going about it.
00:23:28 Omar: Going back to the strong versus skinny, what does strong mean, for example, in the litigation context? It might actually be instead of hiring 12 very expensive $2,000 an hour human partners with different styles to all have different takes on how to make this legal argument, I wanna have 12 different variations created by AI.
00:23:45 Omar: I'm now almost using that to then let some light bulb moments go off for me to then decide how to synthesize that and ultimately come up with something myself. But, arguably, all of those might have had hallucinations in them. It's just more inspiring or inspirational in a way.
00:23:59 Scott: It's a really interesting thing to explore because in some sense, we have this dual mandate where we want AI to have high fidelity and not hallucinate and we want it to have human creative breakthrough potential, which is in fact, probably some level of hallucination.
00:24:15 Scott: That is that creative spark on that precipice of rote and routine to make the unexpected leap on that frontier is in fact, probably the same thing as that hallucination, quote, unquote, so this double edged sword. In certain contexts, we don't want hallucination. In others, it really is the differentiating factor.
00:24:33 Scott: And I love that example of not replacing the lawyer, but giving that lawyer a dozen permutations of their own voice, and how to litigate, how to explain this nuance. Is it more aggressive? Is it more nuanced? Is it more precedent based in all these different examples. It gives them a lot of creative flavors to maybe better choose and then win the case.
00:24:54 Omar: I talked about the transactional example, but another way that I've seen this pan out with some of our customers goes beyond legal. But, frankly, I don't even really consider ourselves a legal tech company.
00:25:03 Omar: The reason we call our platform augmented intelligence is if you're selling to law firms, you're definitely a legal tech company. But in our case, the Chief Legal Officer is often responsible for procurement compliance, HR, supply chain, real estate, a ton of other things. And so we have a clear focus on the Chief Legal Officer as our clear persona that we're building the platform in the first instance.
00:25:23 Omar: But one example that we stumbled into a little bit was, initially, we were doing some work on marketing compliance. So one thing that in-house legal team spend time on is reviewing all these communications that the marketing and PR teams are putting out there, especially at a large company where if they're making certain claims that aren't substantiated and the FTC has guidelines around what they're allowed to say depending on the industry and so on and so forth, the legal team needs to review that.
00:25:46 Omar: We've helped significantly streamline and improve that process from the legal team's perspective. But what's really interesting is in doing that, we started to realize these companies spend a lot of time and effort and money from a communications perspective.
00:25:58 Omar: The 10K or certain artifacts where they have armies of humans who are involved, the best people in the world to get that very specific balance right between making certain claims that are exciting and pushing the boundaries of the industry, but also not going too far.
00:26:11 Omar: We've also seen this opportunity to really, even beyond legal, start to build this brain which actually incorporates the best people in the company and a lot of feedback whether it's training data or fine tuning around what is that nuanced voice look like.
00:26:26 Once you have that baseline, you can actually begin applying that at scale instead of relying on different law firms, different PR firms, different huge teams internally, who all might have their own inconsistencies and human hallucinations on the ways that they wanna articulate that language.
00:26:39 Scott: Almost instantiating corporate culture, corporate ethos with some parameters around FTC requires this and that to then be able to bounce the ping pong ball off of or as a Socratic debate partner from the human to the culture, human to the company.
00:26:55 Scott: It's actually fascinating when you think about the history of legal entities and instantiation of there's Omar, there's Scott, and no there’s, Eudia Inc, which is its own entity that exists and persists beyond the scope of our humanity.
00:27:10 Scott: It exists in a legal context, incorporated in Delaware, existing in the world. We're on the precipice of being able to generate AI agents’ cultures that you could bounce off of in these instantiations of other things that are quite similar to the parallels of corporate structures versus people. Just something that I've personally riffed on, thought about a lot.
00:27:28 Scott: But shifting gears just in the last minute or two of the podcast here, Omar. I want to talk a little bit about your surfing life, running down the hill to your Pacifica Beach break. If you could live anywhere in the world, let's say with a surfing theme, where would that be? Where would you go?
00:27:43 Omar: Honestly, I think I'm very lucky. I think exactly where I live right now.
00:27:46 Scott: That's a pretty good answer.
00:27:48 Omar: I know during the pandemic, everyone apparently moved to Miami and Austin and whatnot, but even if Silicon Valley is ahead by one or two months, that makes a big difference right now. From a professional perspective, it's been amazing to be here right now.
00:28:02 Omar: You can build a great company anywhere, but just seeing the change that's happening and being really in the arena while some of these new technologies are developing and from a social perspective, being around people, even if they're building a music company or something that's totally different, but being able to trade notes on how everything is changing and having a very active discussion there professionally has been awesome.
00:28:23 Omar: On the personal front, once you get used to the Bay Area climate, I think it's hard to go anywhere else. My kids freak out when the weather is 72 degrees. They think it's way too hot. So I think the nice Pacific 50, 60 type of climate is also suiting me right now.
00:28:34 Scott: As far as where you ingest information about this frontier of AI, is there something you read or a podcast that you listen to?
00:28:41 Omar: Mostly, a lot of substacks. I really do think the person-to-person conversations I'm having. Again, very fortunate, partly with General Catalyst, all of that. I was just listening to Dario from Anthropic a few days ago. Mike Maples and I talk every week pretty much still, and he's just down the road.
00:28:56 Omar: I've seen the most value probably in terms of just ROI for a 30-minute conversation talking to someone like you about some of these things because we're all reading different things and then it's more about the synthesis and drawing some parallels between the different things.
00:29:08 Omar: But I think other than that, I would definitely say traditional media has not kept up with this at all. So I almost don't even spend any time there anymore. It's all podcast, Substacks, and real life conversations.
00:29:18 Scott: In that fragmentation, that long tail of experts. Finally, where can listeners find you?
00:29:24 Omar: I'm increasingly active on LinkedIn. Obviously, a little bit on Twitter, but with our audience and our Fortune 500 world, LinkedIn is the dominant platform. In the AI world more broadly, definitely Twitter is.
00:29:34 Omar: And we just moved into a new office in Palo Alto, so we're gonna be doing a grand opening in a few weeks. But we're all already moved in here. It's honestly great to be in person too.
00:29:42 Scott: Amazing. I will let you know when I'm next in the Bay Area. I'll come by the Pacifica 50-degree climate and get down to that freezing cold water.
00:29:52 Scott: Omar, thank you so much for many years and decades of friendship, of leadership in the AI space. It's truly incredible to see what you've been able to achieve and build even in the short time with Eudia. We're just super, super proud to be a small part of it.
00:30:06 Omar: Awesome. You guys have been great and was very happy to have Everywhere be one of the first checks in. So appreciate everything that you guys are doing too.
00:30:12 Scott: Thanks, Omar.
00:30:14 Scott: Thanks for joining us and hope you enjoyed today's episode. For those of you listening, you might also be interested to learn more about Everywhere. We're a first check pre-seed fund that does exactly that, invests everywhere. We're a community of 500 founders and operators, and we've invested in over 250 companies around the globe. Find us at our website, everywhere.vc, on LinkedIn, and through our regular founder spotlights on Substack. Be sure to subscribe, and we'll catch you on the next episode.
Read more from Omar Haroun in Founders Everywhere.