Joe Dormani of TR Ventures

Welcome to the Puck Venture Capital and Beyond, a show that examines the changing landscape of our world. We'll have candid conversations with VCs, entrepreneurs, and thought leaders grappling with our current challenges and providing solutions to key problems we face as a nation. I'm Jim Beer, president of CMBG Advisors. This podcast brings change makers to the table to discover the inner workings behind their decision making strategies and ultimately to how they got to where they are today. You know, I like thinking about valuation as a decision making framework, not like this is a price for a thing, therefore that is the absolute truth of what the thing is is worth.

Today, I'm talking with Joe Germani, founding principal investor at TR Ventures, the investment arm of Thomson Reuters. Joe and I discussed the types of investments they are currently making, as well as the ever changing world of AI development. We also discuss how you as the investor can find the right partner to invest in your company. Joe Dromani, welcome to the Puck. We are excited to have you, and we're excited to hear about Thomson Reuters and TR Ventures.

But before we jump in, why don't you take a minute and tell us a little bit about your background? Great. Thanks. Yeah. I'm I'm excited to be here.

Recently just moved back to The United States. Actually spent the last three and a half years living abroad in Switzerland. So been back for a few months now and excited to see New York and the city and how things have sort of rebounded from the pandemic. Yeah, a little bit about me professionally, I've sort of done a number of different things across my career. I've started my career working in startups, so done a variety of different operational roles.

I've worked in product. I did the whole MBA thing. I wound up doing some strategy work, some consulting. But thematically, the sort of thing I've always kind of focused on career wise was early stage companies and investing. So that's where I've spent a fair amount of time.

And and now, you know, for the last six, seven years, you know, I've been with Thomson Reuters. And and luckily, over the last year or so, we've we've started TR Ventures, and, you know, we're an early stage corporate venture capital arm of the Thomson Reuters Corporation. Well, there's a lot of VC money out there, and there are a lot of VCs. What's unique about TR Ventures? That's a great question.

We're a financially focused fund. The thing that is great about TR Ventures is that we have that strategic alignment with the Thompson Reuters Corporation. So what that means is that when we make investments, we also build a strategic thesis for how we can help accelerate the companies that we invest in. We invest in markets that we have a presence in as a corporation, so we have a fair amount of assets and expertise in those markets. So that's legal, tech, tax, software, fraud risk and compliance, news and media, which is perhaps from a brand standpoint, what TR is most well known for.

But from a PNL standpoint, you know, we have some pretty large businesses in those other markets. Aren't you also kind of moving into the AI space and seeing how AI will figure into working in the legal market, for instance? Yeah. Absolutely. It's a big, big part of how we think about investing and where we think about the opportunities to make some interesting venture bets.

Any company that has a sort of data element to it, that's gonna be the type of company that we can help accelerate. And so a big part of when we make investments is we build that connection strategic thesis for how we can accelerate them. I talked about the markets that we invest in, but thematically what's consistent across those is that the future of those markets are increasingly being driven by new technologies like machine learning, natural language processing, task and process automation. So when we think about investing, we think about those verticals, but then we think about the application of artificial intelligence, machine learning in those markets and in things that you might consider adjacencies. Before we dive deeper into kind of the type of AI you're seeing right now, based on your background, you've done a lot of work in the valuation space.

How does that influence what you're doing today? And are you seeing a change in valuation because of the market we're in right now? How's that looking to you? Yeah. A big part of kind of my my technical training is in finance and valuations.

Big part of my focus. I love the way valuation works. It's an area of massive interest for me, which is kind of why I've done a fair bit of thinking about it. What I really like about it is when I think about valuation kind of high level, and there's all different sorts, right? Private company, public company, you know, real estate.

So you value things in a bunch of different ways. Assets get valued in infinitely different ways. But what I like about it is that it gives you a sort of quantitative way to support a series of thoughts and ultimately what your thesis is. So all of the things in the analysis that you do to build up to that valuation are what I find intellectually stimulating. You know, I like thinking about valuation as a decision making framework, not kind of like this is a price for a thing, therefore that is the absolute truth of what the thing is worth.

But, you know, in terms of where the kind of market is, you know, I mean, when I look at the market, I kind of focus on technology stocks. Obviously, that is where, from a valuation perspective, a lot of what has been happening with interest rate increases and excess liquidity has impacted where valuations have gone, right? So at first, it was kind of low interest rate environment, post pandemic stimulus into the economy, high levels of liquidity, thus driving up asset values, a lot of money in the market, free or close to free debt. Therefore, a lot of capital liquidity. Right?

So asset prices rise in that environment. And then we kind of moved into this period where inflation started to spike because of the increase in prices across the board for things like commodities and valuations. We got to a point where we had to sort of say, well, we need to put off on the brakes and, you know, raise interest rates and sort of slow down the level of demand that's in the economy. And the things that get hit in a high proportion in that scenario are things that have long dated cash flows, right? So things where there's high growth assumptions and cash flows far into the future because when you raise interest rates, you're raising the cost of debt.

And thus, the rate at which you discount the value of those cash flows from the future to today gets higher. Therefore, theoretically, the cash flows are kind of worth less. But, you know, that's kind of like a technical reason for some of what's happening where whereas I think, you know, if you sort of step back and you still look at investing in great companies and putting money into really interesting technologies, it's still gonna be, you know, a valuable exercise. So in the early stage enterprise technology companies that you're looking at right now, can you give us an overview of the range of companies that you work with? Sure.

Yeah. Yeah. I mean, we're focused on, like you said, early stage, but what we define that is series a company. So generally, you know, what that means is companies that have a couple million in ARR typically, so annual recurring revenue, revenue that is based on subscriptions. It's usually a company that has already raised a seed round, which is generally like the first institutional money that comes into a company.

You know, they've gotten a fair amount of traction, have what's called product market fit, which means that what they've built, there's a clear need for in the market and companies or customers are buying that product on a pretty solid trajectory. And so, you know, they're looking for that next stage of funding to accelerate the growth trajectory, continue to enhance that product. So we're focused on series a. We'll do some seeds and some opportunity series b investing, which is the kind of next round where, you know, growth starts to accelerate. But a is, the sweet spot for us.

And do you typically lead these rounds, or are you typically coming in as co investor? That's a great question. We typically come in as a co investor. We can lead rounds. I think eighty twenty, we will come in as part of a syndicate, but we write pretty significant checks anywhere between 3 and 5,000,000 usually initially, and we look to double down on the companies that perform well.

We're taking a long term point of view on these companies. Is there a company that you're working with right now that really stands out? I love all of the companies that I work with. We publicly announce our investments in Legible and Priori. So Legible is a crypto tax software company, and Priori Legal is a illegal market place solution that helps connect general counsel with very specialized or somewhat specialized external legal counsel.

And there's software in the middle of that that helps, facilitate the interaction between those two parties. So those are two of the companies. Then there are, you know, variety of of other companies that we're looking at or at the finish line in terms of making some investments. So with Priori Legal, tell us a little bit about why you're working with them and what was exciting for you. Yeah.

So first and foremost, Basia and Mira, the CEO and chief product officer of the company, are just phenomenal. They're great to work with and, you know, they're just knocking it out of the park on execution and growth. And I would say kind of resurrecting this legal marketplace market where there have been kind of a variety of companies over the past ten years or so that have tried to do this, but they've really taken this concept of connecting or digitizing the interactions between a corporate legal department and external legal services and, you know, building software around that, making it a great experience, having a vetted network of legal professionals for corporations to go and work with. You know, they've just kind of taken it to the next level. They have great group of investors, and we're just excited to be working with them.

How do they screen the kind of various legal people in order to figure out who they wanna work with? Within their organization, they they have a ton of legal expertise, both Fasha and Mira legal backgrounds. You know, they've gotten to this point where they have a pretty systematic process for how they go about doing that. There's a fair amount of automation in it so that they're able to onboard really high quality legal professionals. And it's actually they're getting a fair bit of traction with pretty large corporations and also pretty high caliber law firms.

Like, what kind of specialties are we talking about that they're going after? It sort of varies. Right? So, you know, if there are specific jurisdictions where you need expertise or if there are specific types of matters, specific securities laws or specific types of litigation where, you know, there may be a handful of legal experts who have written or seen cases on a specific topic, they're able to get these types of experts on the platform. Got it.

So we're hearing a lot about AI and whether or not it's a military application or machine learning or otherwise. In your universe where TR is really focused, can you walk us through some of the developments in AI and what you're actually seeing? Yeah. So I think Thomson Reuters is extremely well positioned to be in this conversation and help inform the future of how AI evolves in the professional space. Right?

So in the spaces where human experts or there's, like, a higher level of cognitive understanding required to do a piece of work, and therefore, the threshold for what can be automated or the types of tasks that can be done by AI is a little bit higher. And I think what that comes down to is our legacy as a content driven technology company. And what that means is that one of our really strong organizational competencies is that we have a very strong capability around collecting data, enriching it with metadata, and then making connections between those different types of datas. And then the mining of those things is where the kind of insight comes from. You know, the relationship between a person and entity or the kind of things that or activities that that person or entity can do.

That's the kind of foundation, I think, for these AI solutions. And what Thomson Reuters is able to do is because we have this history of building technology that is able to do that with data, we're very well positioned to create the next level of technology, which is the application that understands that data and then synthesizes it and asserts those insights. So can you give us specific examples from your investments in terms of how AI is actually changing a particular business plan or how a company operates? Yeah. I mean, the way I sort of think about that is it's sort of like taking a set of human experts and codifying that expertise and almost turning the human decision making aspect of that into something that is closer to an algorithm.

Right? So some examples for how that that might be applied is, you know, let's take a process, right? Like a standard process for a business activity. Let's say like an acquisition. Think about an acquisition, a lot of documents, a lot of process, right?

So a big part of getting an acquisition done is the ability to get contracts reviewed, understanding different commercial agreements, the different types of documents that constitute the company that might be being acquired. You know, there's a whole process for how you sort of take a company that your company would acquire through a diligence process. Right? So right now or the way that has sort of worked for the last fifty, hundred years, is that you'd have a lot of human experts and lawyers, in in most cases, read through volumes and volumes and volumes of documents and then kind of take you through that process. And, you know, it's very, very expensive process to do because all of these folks are highly specialized, highly trained, and paid very well, which rightfully so.

And so the way some of that is changing is where we can have you know, a lot of these transactions have a fair bit of similarity, but where some of that is changing is that instead of having to spend so much human time on the aspects of that process and the documents in that process that may be somewhat standardized or have similarities from transaction to transaction, maybe technology can start to automate that, start to synthesize those documents in a way that enables the human experts to spend less time on the aspects of that work that don't necessarily require their specific expertise and are more just the things you sort of have to do to be in a position to assert your expertise. And then they can spend more time in the things that require sort of human cognition, which are the synthesis and then kind of explanation to the non expert about what things you should be looking for from a risk standpoint, what things that you can tolerate from a risk standpoint that you shouldn't take that risk or liability for. And so you can spend more time in making a solid decision than you do in kind of getting from point a in process to point z in process.

Well, my background is as a corporate lawyer and did a lot of m and a work. And when you're doing a transaction from a diligence perspective, one of the things that comes up is is there a requirement that the contract to be assigned needs consent, for instance. So, certainly, if you scan those documents in, a computer could look for assignment provisions and anti assignment provisions. But it sounds like you're talking about something more sophisticated than that, than actually looking for hidden bombs somewhere in these contracts. Yeah.

I mean, I don't know that I would call them hidden bombs, but maybe understanding, like, in that case, you know, those types of provisions, like, what is the standard provision structure for a transaction of this type, right? And as opposed to having to go and find 10 transactions that look similar and find within those transactions those provisions that look similar so that you can make a decision on what provision to include, you can take what would maybe constitute ten hours of kind of research and work, and you can take that down to ten minutes because the system understands what that provision looks like because they've been trained by the human experts, TR type of human experts that we have and the technology that we have to say, here's this provision. Here's very similar provisions from the last 10 transactions that happened in the market, and here are the things within that provision that are either negotiable or not negotiable. As you're working with lawyers and working with companies that are dealing with creating products for lawyers, Again, looking at the economy we're in today, do you see an opportunity, for instance, to counsel some of these companies in terms of how to preserve their cash, how to get their burn under control?

I mean, lawyers are kind of often first on the line in terms of working with these these companies as they're struggling with liquidity. Is there a role for TR in helping lawyers and companies manage their cash and get through this nuclear winter period that we're in, so to speak? From a ventures standpoint, from our portfolio companies and the companies we would consider investing in, I'd sort of straddle the fence and there's a lot of advice out there about this. But the way I sort of think about this is there's not a ton that changes for a company that is building a solution or building a company for the next seven years, you know, when it comes to the kind of near term interest rate fluctuations. Now, obviously, you know, there's specific things around demand that will sort of dictate the level of progress and the pace at which a company can go and thus the right sort of level of investing that their own capital.

But would I ultimately go and say you need to cut your burn? I don't know that there's a blanket recipe for the perfect advice there. The way I sort of think about it is remain focused on building something that people and customers need and be able to deliver that to them in a way that has as little friction as possible and don't overspend on things that you might not have to spend money on. We do look at burn relative to the amount of new growth for the companies that we invest in. It's one of the big things that we look at.

So there is a a set of discipline required there. But I think where I kind of would land on it is I don't know that when there's more liquidity in the market, it's easier to get money. Yes. But I don't know that if you would have asked me a year ago or two years ago, I would have said spend as much money as you can and do everything you can do to drive growth and get that next incremental dollar of revenue into the business. I think I probably would have tried to give some similar kind of more even keeled level of advice.

So the kind of task remains the same and, you know, you have to kind of bring a level of discipline to the process of company creating. And, you know, like, the macro environment will be what it is. And if you can, keep your head down and just keep building what you're building. We speak to a lot of VCs, obviously, and you were talking about how you guys do a lot of series a rounds. When people get their series a money, let's say they say, well, this is gonna last us six months or this is gonna last us a year or however long the period is.

The series b rounds are not coming as readily as they did six months ago. Right? So some VCs are saying, look, unless you really, really are profitable or you have a path to liquidity, you better make sure you have two years of cash on hand. That's one philosophy some people are having. And so the question is from a technology perspective and just managing this process, if liquidity is tighter for these companies and they have to make their cash last longer.

The question are there are there tools or creative ways to counsel them? Yeah. I mean, having two years of runway is just kind of good practice, I think, when it comes to to building a company. I I don't know that that has changed, you know, a ton given the kind of new overall macro environment. And I know that people are saying that more now, but you kind of run into this whiplash thing where if you actually zoom out a little bit, a lot of folks were saying, like, as you're coming into the pandemic, like, oh, hold on.

Everything is gonna stop. Let's cut your burn. Don't spend any money. Preserve cash. And then, you know, the next few years, we know what happened in terms of liquidity in the market, the type of investments that were made.

Now when we said, like, you know, grow at all costs, spend the money, capture the market, and now we're back to, okay, hold on. Let's cut our burn. Let's hold on. Make sure you preserve cash. My sort of point is that I think an even keeled approach to how you manage your business, make sure you don't get ahead of your skis is kind of the consistent thing that you should probably do.

And, you know, going too far one way or the other, not gonna be great advice because the kind of macro can change pretty quickly these days. That's true. So in terms of where you see the market going and new things that you're looking for, how do you source deals and what kind of new things are you seeing right now? Yeah. So we are very lucky to have a pretty extensive network within TR of folks who have a very high level of expertise in the markets that we operate in.

And so through those folks, we have a pretty good lens on the type of startup activity happening in things like legal tech, fraud, risk and compliance, tax. We just have a pretty good finger on the pulse of what's happening in those markets, and therefore, we have the privilege of of seeing the interesting companies that are emerging in that space. So that's one thing that's pretty advantageous for us as a as a fund. We're also pretty thesis driven, so we kind of build points of view on different parts of the market, and we we actively seek out companies that we will invest in. And then Thompson Reuters has an amazing reputation with customers.

So, you know, I think that sort of extends to the investment community as well. And the earlier stage companies are independent companies that operate around the markets that we operate in. So we actually get a pretty good flow of inbound interest for the fund just because we have that reputation with our customers and that association is pretty valuable. So we kind of do a lot of that. We're very collaborative, like, usually investing is part of a syndicate.

So we work with a lot of seed funds, a lot of other series a investors. So we're always looking to work with other investors. So we spend a lot of time testing our thinking with other investors and figuring out where we can get a little smarter. And are you investing in things not related to the, like, legal profession, for instance? I mean, how off field will you go?

Yeah. I mean, tax is a whole other area, obviously. Fraud versus compliance, that's pretty broad. And those things extend into fintech, certainly on this tax side and on the fraud side. Right?

There's a lot of fintech that we do see, so that's another area. Insurance is another area that we look at. Anything enterprise technology, we're gonna wanna take a look at. The main thing that we're looking for when we look at companies is can we do something? Do we have access to assets and expertise that can accelerate the companies that we invest in?

And when you talk about fraud, are you talking about fraud detection or fraud prevention or both? Yeah. Both. The way we think about it, there's a end to end stack there. Right?

Starts with detection, and it goes into ongoing monitoring, and it goes into prevention and then into investigation afterwards. Right? So, you know, we sort of think about it from the same way that a customer would think about it. Like, customer, I have to worry about all of the data that is passing through my systems. I have to worry about my users and their activities.

I have to worry about synthetic identities. I have to worry about protecting my customers' information. I have to worry about protecting our assets. And then I have to be able to monitor the kind of entirety of that real estate on an ongoing basis. And, you know, the threats are constantly evolving.

And then, you know, if something slips through the nets, we have to be able to figure out why that happened and hopefully help close that out so it doesn't happen again. Are you involving companies that actually do fraud investigating work after, let's say, a company's lost a $100,000,000 for sake of argument and people are trying to figure out where the money went. Do you get involved in those kind of investigations? So we sell technology to the organizations that go and investigate in those scenarios. So we do have some products in that space.

And what would that product do for instance? It would help verify an identity. It would help verify that a person is who they say they are or the activity that they perform is above board. Right? And it's not something that is done from a device or an IP address that is not standard from, you know, the set of historical activity that has been associated with a particular account.

So you can if a company's historically been doing business with a certain number of vendors, there's software that's out there that'll go in there and look for things that are inconsistent or out of the ordinary. They look for patterns that are unusual. Yep. Got it. And the firms that use that are like the FTIs and the other investing forensic accounting firms and law firms that do that kind of stuff.

Yeah. Anomalies. Yeah. Exactly. And corporations and government.

Right? We have law enforcement agencies as well. Interesting. And I assume in that area because of AI, for instance, I assume that technology is only getting better. Yes.

Correct. It's amazing the stuff that's going on. And I know, for instance, Israel's got certain companies that are doing some very interesting technology stuff that they were licensing to police stations or other investigatory bodies and stuff like that. And so when you started this, are you in terms of geography, are you agnostic? Are you investing all over the world?

Are there particular locations you're focused on? Yeah. We have a we you know, it's a global corporation. We have a global purview. That being said, the majority of what we'll do will probably be in North America.

We're also a Canadian company, so we have a really good lens on the Canadian technology scene, particularly Toronto and and Ontario, where we have a a lot of really smart AI engineers. We're also focused on the TAM, Southeast Asia, UK. Like I said, global purview, but majority of investments will probably wind up being North America. And are you like you were saying, you don't typically lead these investments, but for instance, do you typically put somebody on the board? Yeah.

So we do. We take board observer roles, but only when we're asked to. We're always happy to, but we wanna do it in scenarios where the companies want us to be part of those discussions, which is pretty much all the time. Because of that strategic angle that we bring, you know, having us involved in those conversations are usually pretty advantageous to the companies because we can do a lot of things to cut through some of the red tape that sometimes exists when working with large enterprises. Interesting.

So, you know, we we can act as a lever on both sides. Right? On the corporation side and on the company side. As you're looking for companies to invest in in those people that want to approach you, I mean, what kind of advice would you give, you know, portfolio companies that are looking for money in terms of how they should approach it? What kind of common mistakes do people make, and what advice would you have for them?

Yeah. It's a great question. I think the one thing that always sticks out is just a high level of transparency is super important. Right? So just be very forthcoming with the current position of the business.

I think it's it's very important to select the right investors from a company standpoint. You don't want an investor to not understand or not have clear visibility into the performance of a company or the product and have them make a decision that is suboptimal and, you know, get on your cap table because, you know, there's a lot of hype around the company, but maybe the reality wasn't quite where that hype was. Like, that's not a good scenario for the investor or for the company. For me, the thing that I like to because we like to get into the data. We like to bring our experts from within the company on the engineering and the products.

We like to bring them to the table. We like to have conversations. We like to get into detail. So the more transparency we can have, we can just make a good decision on whether or not we're the right folks to partner with over the next ten years or so. Getting everything in clean and tight order when it comes to fundraising and that level of transparency, I think it's just, you know, that's my main piece of advice.

Have you seen in going into a more tough economy, are there any particular stumbling blocks that you think companies need to be more careful about right now? There are probably things that are specific to certain markets where the current economic environment is more impactful. But I think the longer term trends around digitization, technology spend, maybe you see pauses or, you know, reductions in budgets and things slowing down, but I just feel like those things are short term. So to me, it's about being consistent, not overextending yourself, and just continuing to focus on building something for customers that they need that is essential to the way that they operate. And I think the the kind of longevity of the company works itself out if you kind of take care of the customer and build something high quality first and foremost.

So if you were gonna look at the legal profession today, 2022 versus 2010 or 2015, and you were to say what the biggest change has been in terms of technology affecting it from from what TR has seen out there. What is the biggest tool or change affecting lawyers from your perspective? Yeah. I mean, the way I sort of think about the profession where it is today and where I think it might be able to go in the future, you know, I think it is this intersection of depth of insight around the expertise that a human has and the codification of that expertise and the ability to parse through large volumes of data that, like, previously just would not have been possible, but today can be quickly synthesized. That being pillar one and the synthesis with pillar two being three sixty degree understanding of the entirety of a process.

Taking something from this is a closed piece of work or work product and having the understanding of each intricate step of that process and the optionality within the different steps and tasks to get from task one to that end product. It's that combination and the codification of that, which I think takes the profession from something that has been more of a craft, something that has been more focused around the human being at the center of that and having that knowledge passed down from one person to another, to being something that is made more digital native, right? Something that doesn't necessarily rely on piece of paper being the sort of foundational object or or thing of record that all of that work and matters and transactions are predicated on. Having that process be redesigned for a world where access to information is almost unlimited and the amount of compute that's out there is almost unlimited. The amount of storage out there is almost unlimited.

And thinking about what that process looks like when you're not reliant on organic life forms to be the thing that is processing all of that information to get from point a to point z. Do you see companies working on more sophisticated ways to set up data rooms, for instance, from that perspective if they're doing due diligence and they're having people sign NDAs and then access coming into a room and looking at contracts and reviewing them? Are there tools that people are developing to facilitate that process? Yeah. I mean, I'm in and out of a lot of data rooms.

Right? When we look at the deal, we're in the data room. Right? When we're talking to founders, we're we're super excited to get access to the data room. Can't wait to dive through.

So, like, am I seeing stuff on that front that is particularly innovative? I don't know that I am seeing a ton, specifically around the data room, which is just kind of this set of documents that are related to to a dealer transaction. The way I think about it is there's a lot of stuff behind the scenes that kind of just need to be in place, like access management needs to be pretty tight. Security of the data needs to be pretty tight. But in terms of technology that that I think is kind of pushing the the leading edge there, I'm not sure that I'm seeing a ton on that front.

What about oftentimes, lawyers will pull up a contract, you know, or a complaint from their most recent deal they did, and they'll modify it. And so they'll they'll go in and they'll change the names, they'll change in the notice provisions, they'll change the governing law provisions. But let's say there's 20 sections in a 100 page document that you really need to focus on 90 spoiler plate. But for instance, on page 50, there's a reference to the old company's name and you didn't catch it. Are there AI tools that are there to facilitate lawyers in drafting these documents so that as you're going through it, it actually helps you figure out to make sure you catch all the places where you needed to change something?

Yeah. You know, there are a lot of AI drafting tools and things that help with document creation. I I guess I should say that I'm I'm not trained as a lawyer, but I think I might have a little bit of a contrarian view on this topic. Whereas I'm not sure the premise here is the right one, which is, like, how do we make the creation and sort of progression of a document creation? How do we make that more efficient?

If we sort of took that back to to first principles, it's like, what is a digital native mechanism to get all the right things in place so that two parties who willingly wanna interact with each other can do that in the way where there's the least friction possible and the least manual effort involved. And I think where I land on that is it actually looks more like software than it does a piece of paper or like a legal contract. I don't think the industry is there yet, and I think there are companies who are starting to get there. But I think, you know, we're kind of early on on that journey. And I think the way to sort of to make the counterpoint on that kind of potential future is that you have to think about your users.

Oftentimes, you have professionals, right? I won't just say lawyers, I said professionals, accountants, consultants, financial professionals like myself who have been trained to do things a certain way and then have done things, you know, that certain way for decades sometimes. Right? To come in and say, don't do it that way anymore. Do it this way.

And use the program that the kid over here made. There's just a ton of friction there, right? Because these aren't high complexity cognitive tasks, and it requires, you know, a certain type of expertise to be able to do those tasks. And you need a certain level of pattern recognition and experience ingrained in you as a professional to be able to do that. So the bar on adoption is pretty high when it comes to these things.

So that's the counterbalance. Joe, this was great. Cool. Thank you. I appreciate it.

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