Seed to Exit
Welcome to Seed to Exit, the ultimate podcast all about startups, scaling, and venture capital. Your host is Riece Keck: Startup veteran and recruitment entrepreneur.
Join us as we dive into the journeys of startup founders and venture capitalists who share their insights, successes, and lessons learned from seed stage to successful exit.
Each episode, we bring you candid conversations with startup founders, executives, and investors. Whether you're looking for inspiration, actionable advice, or a deeper understanding of the startup ecosystem, Seed to Exit offers invaluable knowledge and real-world experiences to help you on your entrepreneurial journey.
Tune in to Seed to Exit and get ready to be inspired, educated, and connected with the exciting and ever-changing world of startups and venture capital.
Seed to Exit
Justin McCallon, CEO and Founder at Callidus AI | The Role of AI in the Legal Profession | Transitioning from Corporate to Startups
Justin McCallon, founder and CEO of Callidus AI, discusses transitioning from corporate America to startup life. He shares insights on building versatile teams and the role of AI in modern law.
• Transitioning from corporate roles to entrepreneurship
• Importance of visionary thinking in startups
• Cross-functional skill sets as a necessity for startup success
• Challenges of AI adoption in the legal profession
• Future predictions for AI integration in law
• Advice for corporate professionals considering startups
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LinkedIn: www.linkedin.com/in/riecekeck/
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Recruitment: www.mindhire.ai
Youtube: https://www.youtube.com/@seedtoexitpod
When I try to think about vision and try to ask them tough vision related questions about how could we make an impact on the space, what I've noticed is, especially in corporate America, people think pretty small relative to in startups. When I talk to other founders, they're thinking really big, and if people are thinking about how is the landscape going to change and how they're going to capture value from that and grow their business in creative ways, that's a really good sign. Definitely trying to get a sense of can the person wear multiple hats? Everybody in a startup has to, even my developers. Even though they're really technical, they need to quickly understand the legal implications for what they're building, and so we need people that are cross-functional, um, at least in the way that we do business, and so I'd look for people with those kind of cross-functional abilities and just high levels of curiosity and interest and drive.
Speaker 2:Thanks for listening. To Seed to Exit. I'm Rhys Keck and today I'm joined by Justin McCallan, founder and CEO of Calidus AI. Calidus is an AI company dedicated to augmenting not replacing, lawyers through advanced AI solutions. Prior to founding Calidus, justin practiced law as a commercial restructuring and M&A attorney. He then spent 12 years at AT&T and its subsidiaries, including Zander and DirecTV, including where he launched the first generative AI product for DirecTV. In our conversation, we're going to talk about the inspiration for Calidus, what it was like to transition from a large enterprise to a startup, the implications of AI in the legal profession, fundraising insights and some advice for inspiring entrepreneurs. Really excited for you to listen. Let's go ahead and dive into the episode.
Speaker 2:Welcome to Seed to Exit, the podcast where we uncover the stories, strategies and insights that power the startup ecosystem. I'm your host, rhys Keck, founder of MindHire, a talent acquisition firm specializing in helping startups build exceptional teams. Each week, I sit down with founders, investors and industry leaders to explore the journeys behind iconic companies and game-changing ideas. Whether you're building, investing or just curious about what it takes to succeed in the startup world, I want this podcast to be your go-to resource for actionable insights and inspiring conversations. Now, if you enjoy the show, please don't forget to subscribe, leave a review or share it with your network. Your support means the world and really helps bring more incredible conversations to life. Justin, thanks for coming on, excited to have you.
Speaker 1:Yeah, great to be here. Thanks for having me on.
Speaker 2:Absolutely. I love talking AI, so I'm sure there's a lot that we can get into today. Before we jump into things, just for those who are not familiar, could you give me a quick overview of what Calidus is and also what the inspiration for starting the company was?
Speaker 1:Yeah, Calidus is a legal tech platform focused on work for professionals so lawyers, procurement people and then we're focused on the core legal and procurement workflows, not kind of secondary or tertiary work.
Speaker 2:Gotcha. And then, what was the inspiration for starting it?
Speaker 1:As far as inspiration, I was a lawyer by trade, ended up doing transformation at AT&T for the legal department, and then, right after that, ran a Gen AI group that launched the first Gen AI product, and it became very obvious to me the work that I was doing in transformation, which was really impactful, would have been absolutely turbocharged if we had the same Gen AI capabilities that we did a couple of years later, if we had the same gen-AI capabilities that we did a couple of years later, and so it was just obvious to me that this was the time to go from make a transformational impact on a big industry perspective.
Speaker 2:And congrats, by the way, on making that jump. That is a big one. I was curious because, when I was checking out your background, you know, like you mentioned, you'd worked for AT&T. You'd spent most of your career prior to starting the entrepreneurship journey in a large corporation. What's the adjustment been like as you jump from all of that structure to basically none?
Speaker 1:I love it. It's one of those where within every big corporation, you have pockets of people that are pretty different from the rest of the corporation, and so for me it was always being the agent of change, trying to do things faster, do things in a more visionary way and make big transformations. And AT&T and DirecTV, where I was before great companies, great people, but it takes so long to move these big bureaucracies. My sister she was younger than me, she had started a startup and bootstrapped it. She's done really well with that. So I've been pretty helpful or pretty involved with hers for a bit. I had done something small about 10 years ago, so I've been aware of the space, paying attention and looking for an opportunity and eventually one came up. So I don't think it was one that a whole lot of people that knew me were very surprised about that. My colleagues were definitely like he's the person trying to ram, everybody ram stuff through, and he knows that it's going slow and so it's really enjoyable to be able to push fast.
Speaker 2:Yeah, absolutely. What did? What did the ex-colleagues or industry contacts mentors think when, when they found out you were making the jump?
Speaker 1:besides the lack of surprise, um, yeah, definitely, it was just a. This is a good fit. I think it was mostly positive. Um, as even my boss was like I knew that we weren't going to keep you around forever, um, this was, uh, my to go, I think, and so I still stay in contact with them, trying to sign them up as a customer actually right now, and it's a great group of people that I've had a chance to work with at AT&T and their subsidiary Direct TV.
Speaker 2:So here's a question for you. So you know, obviously I've been in recruiting for quite some time now, mostly in the startup space, and typically the bias, if you want to call it that, is that people who come from big companies are generally not going to be a fit for startups because they're used to too much structure. There's all the red tape, blah, blah blah, and you mentioned a little bit. There's different types of people within these huge organizations, obviously, but what are your thoughts on that general dynamic? Would you hire large corporations for your own startup? How are you approaching that line of thinking?
Speaker 1:I think, generally it's going to be true. Like I would say most people that I've worked with in the past, a startup is probably not the right fit for them. I think when you look at people and see a lot of change in what they've done, if they've moved around a lot, that's a good sign. It's also a good sign if they're in one of the more transformational groups whether it's a modernization or transformation or tech group and then get a sense of how are they willing to move fast and are they willing to really align to the mission and buy into the culture and have a really different kind of work ethic. I think those are really the signs. It's probably a smaller percentage of people in bigger corporations that are willing to make the move and you don't want people that they've been trained to demand like free coffee all the time and all the perks of working for Google right, the perks of working for Google right. But you can probably find a few really good options if you look enough and you're open-minded.
Speaker 2:Yeah, yeah, I think that that's a great call out on the signal of having worked within multiple business units within the business or, yeah, on the transformation side. What sort of questions and that's on paper what sort of questions would you ask a potential candidate if you were trying to vet out those more qualitative aspects?
Speaker 1:One. I try to think about vision and try to ask them tough vision-related questions about how could we make an impact in the space. What I've noticed is, especially in corporate America, people think pretty small relative to in startups. When I talk to other founders, they're thinking really big, and if people are willing or thinking about how is the landscape going to change and how they're going to capture value from that and grow their business in creative ways, that's a really good sign. Definitely trying to get a sense of can the person wear multiple hats? Everybody in a startup has to, even my developers, even though they're really technical, they need to quickly understand the legal implications for what they're building, and so we need people that are cross-functional, at least in the way that we do business, and so I'd look for people with those kind of cross-functional abilities and just high levels of curiosity and interest and drive.
Speaker 2:I love that. So, to go back to the beginning of the company, you recognize that there is this need working in the transformation group. How did you go from? There's a need here to actually creating and launching the product, creating and launching the product.
Speaker 1:A lot of what we've tried to do is, I mean, initially, when you zoom out, legal seems like a pretty small vertical. It's pretty big though it's a trillion dollars globally in spend. There's a lot of ways you can address legal meets AI. We wanted to make something or do something aggressive, probably because it's my first time I didn't know better that it had been my fourth time, I probably would have gone a lot smaller.
Speaker 1:We went really aggressive and said we want to go after the core workflows. We know that this is going to be something where lawyers will feel uneasy about it at first. We're going to have to go after the early adopters, and so we try to understand. We talked to a bunch of attorneys, we spoke to a lot of ex-colleagues and all that, and we got a sense of what are the things that they spend the most time doing, got a really good understanding of, okay, here's the 10 or so big areas, and then try to map on how could AI really drive impact in those different areas? And then try to think through okay, what are the problems with some of these, what are the opportunities with some of these, and then came up with a list of a couple areas that we were going to experiment on.
Speaker 1:And for us, when we look at us versus some of the other groups, what we realized pretty quickly was we had built a group of developers that were really, really good, and we have engineers that I would say are best in the industry right now, and because of that, we wanted to use that to our advantage. We've tried to build kind of like a product superiority strategy of we're going to build such an amazing product that it's going to be easier to sell it, versus kind of your traditional hey, decent percentage sales and marketing, decent percentage development and so forth. But by having that approach we're able to build quickly, iterate and then learn from the customer and learn from actual usage and then make changes. And so it's not for everybody, there's other ways to go about that, but for us that's been pretty successful and I'm happy with the approach we're taking on that front. But for us that's been pretty successful and I'm happy with the approach we're taking on that front.
Speaker 2:You briefly mentioned earlier that lawyers get a little bit nervous using AI. I'm just curious is that because they have their own fear that they're going to be replaced? Is it the fear that the AI is going to hallucinate and spit out something incorrect? All of the above, something else?
Speaker 1:I think all of the above. So let's break it down in a couple of different ways. So one is lawyers do very sophisticated work when you really look at it. So think about something that seems simple contract redlining. So they're negotiating a deal and they've got maybe a 50-page document that they've got to go through and redline. There's a lot of things they need to take into account as they think about making changes in the negotiation to this contract. So for one, they might have a playbook where the playbook has a lot of specific language they want to reference and they've got to bring that language in the playbook. Two, they've got to understand the different relationships between the parties. What kind of party is it? What's the market? What are market terms? What's the industry they're in? How much can they push on these different pieces? How much does the client care about this deal? That's probably a third of the factors that are really important of that. Well, the lawyer sees it and they're like, okay, great, but I can't use any of this because it's just like a generic red line. So this doesn't, I wouldn't ever submit this and my boss isn't going to accept it and the client's not going to accept this. So there's a lot from their perspective of you've got to meet this really high threshold. At the same time, the hardest part about running a product is users, because users have to use the product and they get confused really easily. And the more you build in all these complex pieces, the easier it is for them to just kind of not understand how it works and you to create something in elegant. So you've got to always think about how do we create something that's elegant and usable while at the same time, useful for this end audience. So I think that's a big part of why lawyers are more reticent to adopt something like an AI tool.
Speaker 1:I think on the back end, they are probably proud people. They're proud of the work that they do and they don't want to just be told, hey, AI is going to take your job. We don't think that's going to happen anytime remotely soon at least, Maybe in the far future. You can talk about that Anytime before. Like artificial superintelligence, I think lawyers are at a point where they're going to be people that AI is going to elevate them and they're going to just do more and you're going to have more demand. So there's a paradox by an economist called Jevin, and so Jevin's paradox is, as a service becomes cheaper, people want more of it. You think about supply and demand, effectively, and it ends up the result is that these people become more in demand. As long as they're not as long as somebody else can't just step in and be a substitute.
Speaker 1:In this case, I don't think that someone else, like an end consumer, is going to take on and do the legal work instead of the lawyers. I think it's going to be mostly the lawyers doing the vast majority of the work, but the AI is going to help them be a multiplier and just do more, and that'll have interesting implications that some people might be like oh no, we're going to have so many lawsuits right, and you saw some of that with Do Not Pay that they're kind of pushing some pieces there. That's a reasonable concern, I think. On the other side, though, you'll take the time to make your contracts very effective and write them in a way that's really thinking about all sorts of liabilities and things that can happen, and to where you actually start limiting liability and then, to some extent you don't want I'm going to.
Speaker 1:A lot of us now are in places where, if we get wronged in some way, like someone just materially breaches a contract or something, you have no recourse because it costs just too much to sue. So will that change over time? I don't know, it might.
Speaker 2:Yeah, that's what I was thinking of, as you were saying that it's is the the cost in order to yeah, exactly, to sue someone if you've been done wrong in some way. It's like, well, this person wronged me for three thousand dollars, but a lawyer is going to want five, so I guess I'll just let it go. So it's it's. It's really, then, almost the the barrier to getting that supply that's going down and that that, in turn, will get lawyers more work. Now I am curious. It sounds like and correct me if I'm wrong that a lot of the model or the lawyer population that Caledon is servicing is more on the corporate lawyer side, but then you also have lawyers that follow the billable model. Right, is there incentive for lawyers to become more efficient and do more work in less time if that means a reduction in their billable hours?
Speaker 1:We do. We do serve litigators as well, and as far as that question comes up a lot, I would say the legal model is going to be slow to change, but I don't think that that's necessarily terrible from an AI perspective. So as an example, when you're working for a big law firm, you might work 3,000 plus hours a year and you're probably only billing about 2,200 of those hours, so about two thirds to three fourths. And the reason why is, as you're doing, kind of simplistic work or work that just like a client doesn't want to see on like a line item you're going to write it off. And with AI the hope would be that you're doing so much, so efficiently that instead of working or billing for 2000 hours, you're billing for almost all of the time that you work. And then that means for the big firms they're going to have more revenue per attorney and that's going to be a very profitable deal for them. So that's certainly part of the goal.
Speaker 1:The other part would just be you have attorneys that are outputting at a really high rate and because of the tools they're using they're able to demand a higher hourly rate than attorneys that just refuse to use tools. And I would bet that the clients and the corporations that are really driving the legal bill rates. They're probably going to see that and it would become pretty noticeable because this stuff really is powerful. If you're just not using the latest AI and then one firm is, they're going to have such a big advantage to where everybody's going to want to use them, to where I think that it plays out OK. And we saw the same thing with with computers. Right, it's not like like lawyers are refusing to use a computer and they're just doing everything by hand. The market's eventually going to push everybody. It's just going to go a little bit slower, I think.
Speaker 2:That makes sense, and I know that you mentioned that you don't anticipate AI replacing lawyers anytime soon, unless we get to some sort of future hypothetical ASI. What about paralegals, those who are doing a little bit more of the rote work, just the basic filings that perhaps could be automated a little bit more easily? Do you see a little bit more of an automation path there, or what does that look like?
Speaker 1:an automation path there, or what does that look like? It's possible. My personal opinion is that those people oftentimes are pretty good with technology. Same with junior attorneys. They're going to be people who you empower with this technology and then they're really driving way more efficiency and they're able to deliver just a lot more and so well like as we're selling into the smaller firms.
Speaker 1:Usually the first thought is okay, I'm the owner of the place, I'm kind of the managing partner. I usually have to give a lot of this work to the associates. I'm just going to do it myself now with the AI, which will probably give me a better result than the associate would. And the reality is that the associates love this stuff. They start using it and they're just cranking and they're able to develop or do things just so much faster and it's really that now the partner is just happier with the results they're getting. I would expect that that's going to be more likely in the near term and it's probably less of a. Is it going to be one seniority person or another being replaced? I think it's more the people that will use AI effectively and take the time to learn how to are going to be the ones that demand higher rates and higher value, and the other groups are going to just really be less marketable very fast.
Speaker 2:That makes sense. Yeah, I have a buddy. He's on the recruiting side as well and he charges hourly and he charges, I think, probably double what most other people do, and it's basically his justification is that it's his tool set. You know, he might cost you twice as much, but he does five times the work in an hour. So it's basically the same principle that you're talking about here.
Speaker 1:Yeah, yeah, absolutely. And there are some firms that do bill on contingency or bill like a cost per X, like cost per demand letter, and I think that those will grow slowly, but but I think it's going to mix up all the above.
Speaker 2:How do you see AI changing the legal landscape over? Call it, the next three to five years. I think 10 is probably a little too far to predict.
Speaker 1:Yeah, yeah. I think that early on you'll see we'll hit this kind of S curve. So I think the next two years or so it's gonna be legal tech groups like mine are gonna be developing a lot. They're gonna have, over the next year or two years, really hit to the point where truly they're replacing what some of the boring work that attorneys do that is still like sophisticated but tedious to where attorneys can focus more on high value strategic work. I think that they're going to start hitting the law firms and the law firms will see that they have to start adopting. But the adoption cycles are going to be slow for the biggest law firms and when you look at it, just think about it like you've got these top firms like Skadden. They're probably not going to be have like a specialist who's the best in the world at some kind of specific form of litigation in the specific practice area, be just outright replaced by AI for what they're doing today. That person probably is still just going to be an absolute skilled expert and better than what any near-term AI can do. At the same time, that person might have underlying specific pieces of their work that AI can help them do really efficiently to where they can do the higher level thinking, and so, instead of like trying to replace that person's like two week task, it might be that you're replacing that person's 20 minute tasks in doing a lot of that work. That isn't that. It's kind of synthesizing a lot of information for them, boiling it up, and now they don't have to read every single case because it's quickly finding the information that they're looking for, or synthesizing some of the information in their discovery and now they can kind of focus on what really matters. I think you'll see a lot of that in groups that really understand here's my audience in the near term are going to be able to kind of segment the right audience and provide the right tool for that audience.
Speaker 1:The longer term, though, I would say we're probably going to see some movement in how firms operate. There's some states are a little bit different now than they had been in the past. For example, arizona does not require lawyers to own law firms. You might see some other states adopt those principles and adopt those changes. If that does happen, you might see different ownership models where PE firms own some of these law firms. They run them a bit differently, but I would expect that you have the corporations lead the way, pushing for their own efficiency and then expecting really high efficiency from their firms. And if the firms don't adapt to these tools, then the corporate groups are going to bring the work in-house, and so I think that's adapt to these tools. Then the corporate groups are going to bring the work in-house, and so I think that's going to kind of push the industry forward.
Speaker 1:And when I kind of zoom out and just think about what we're building and our roadmap and what really needs to be done, to where we're really doing a lot of the horror work that's tedious, it's not going to be a long way out, like I think some people saw GPT 3.5 and they were like, okay, this is crap, I can't use this. We're not there anymore. We've really come a long way already. The next year or so these startups that are really investing and building quickly are going to close a lot of the gap to be really really useful and I do think that the groups that adopt are going to be able to see really big efficiency gains.
Speaker 1:The other piece to layer in there is there's kind of a competitive advantage play with automation. So if you just automate like 10% of the work, you would think that, okay, I'll be 10% more effective. But it's the same play as when you think about comparative advantage. You're going to, if 10% of the work is pretty much done, automatically, the remaining work that you're doing you're going to will net out to where you get more than a 10% efficiency gain because you'll just do, you'll be doing more of that 10% time. To where it's building up and taking on um and just growing your overall pie.
Speaker 2:Yeah, and then there's also just the reduced mental task between time, switching focus et cetera. It's, it's one of those. One plus one equals three things. It sounds like yeah, yeah, that's right, just curious, what sort of misconceptions are you running into frequently from law, firm owners or various prospects or customers beyond? The AI is going to take all our jobs, thing.
Speaker 1:Yeah, I think part of it is just like under it was kind of related to it, to that. It's how. What is the role of AI? And for us, the way we break it down is we try to really understand what customer we're trying to serve, because somebody who's going through let's go back to the contract example a really high volume of simple contracts where they just are looking for the really critical issues and just trying to fix those and maybe they're in procurement, that's a very different person to serve, with a very different product, than somebody that's a very sophisticated lawyer.
Speaker 1:And what some groups probably see is hey, I saw AI that's more geared toward this procurement group and this isn't useful for me.
Speaker 1:Ok, that might be true, but there is another way that we can be useful for that skilled attorney, and it's probably more in the kind of like I mentioned earlier find ways to bubble up the the kind of smaller tasks to where they're still in the loop. They're still making the end calls about how things need to operate and making the strategic decisions strategic decisions but they're working in collaboration with an AI that's doing a lot of the kind of underlying routine tasks and netting to where they can be a lot more effective and efficient. I think that's just generally a misconception. I think they think it's like, hey, ai is just going to run through and just do my contracts for me and they're like I don't believe it and it just doesn't seem like it's capable of it. I don't see the value. So that's usually the starting point when we first speak with a law firm or with an attorney about AI, and I think once we show them, no, we're going to keep you in the loop, we're going to make everything really visual, really interactive.
Speaker 2:You're still going to be a lot faster and also we're going to bubble up some things you might've missed and raise some areas to where we can make the work quality better, Then they start becoming pretty interested. So as a follow-up question to that then and you mentioned a little bit about what the product you're building is and what type of customer it serves when you think about your go-to-market motion, how did you decide what type of firms to pursue, what size, et cetera?
Speaker 1:what type of firms to pursue, what size, et cetera. A lot of it was trial and error. We had an initial hypothesis. We changed it a hundred times and we got a sense of what customers were using, what customers we were getting the most traction with and so forth, and what we saw our plan initially was hey, you've got really big ACV with these big players. These groups need really sophisticated AI. They might want to pay for it and the small players might just have such low budgets they're just not really interested.
Speaker 1:I think a lot of groups in the industry thought that. And now what we're all seeing is the small law firms are adopting the fastest and the corporates probably second, and the big law firms are really slow on the adoption curve and I expected the change a lot in a couple of years, but for today, not as much so for us. We want to meet customers where they are. We don't want to spend a lot of time just trying to convince a big firm to buy in a really long sales cycle when we're a startup and we want to build a product that kind of meets the needs of people and is a really useful product and then scale that up and go upstream after we've done that and so this kind of fit our focus as well just be more product focused, really try to build something useful, get immediate customer feedback, understand things that are really the core about how the product works, rather than kind of tertiary things that a group might be worried about, and then kind of go from there as we add features to scale up.
Speaker 1:So we're mostly focused on the smaller firms and smaller in-house groups and we've done it a couple of ways. So one is we have almost like a D to C motion where we're looking at go to market, similar to the way that a consumer type of company would look at it, where you're doing your kind of SEO and paid search and social and all that, and then we're supplementing that with a motion that's going after small firms in a sales, more of a sales motion, and so it's pretty similar profiles but one side will sign up like individual players. Then we kind of do like a B2B SaaS motion or bottoms up SaaS motion and try to kind of land the rest of the firm. The other play is more focused just from the start. Let's try to talk to the rest of the firm. The other play is more focused just from the start, let's try to talk to the leaders of the firm and get them on board.
Speaker 2:Yeah, I was going to ask you about that. If you're doing PLG or more traditional outbound motion and you don't come really from a sales background yourself, I'm just curious, what sort of learning curve has that been like? Are you still doing the sales yourself at this point?
Speaker 1:I still do most of the sales myself. I'm uh, I work closely with what we have one other person that does sales, but part-time and and he's great he was a lawyer for five years at some of the top firms. He left to do sales for a little bit that he just really wanted to get into tech and um he's we've got half of his time and he does a great job for us. But then I'll try to raise kind of awareness, do a lot of content production and then talk to a lot of customers and then he does kind of some of the rest. It's been tough, interesting, hard and all that I would say it was.
Speaker 1:One of my biggest learnings is I came here to build and do something transformational and try to kind of establish and use a vision of what the law looks like and how it can shift and change and how a great product can change that. And what you realize when you do a startup is you're selling 24-7 and that's your job. 100% of the time involves a sales mindset and so you have to sell to your team. You've got to get them excited. You've got to sell your mission. You've got to sell to your investors and any future investors. You've got to sell to your customers that are existing and the future ones. So you're spending all of your time doing that and for me it's been helpful. I've worked with someone who's like a coach and like a mentor and he's been able to kind of dissect some of the sales processes that we've had and say, ok, see what you're doing there, don't do that anymore, let's change and do this, this and this a little bit differently, and that's worked really well for us.
Speaker 2:Love that. How are you going to decide when it's time to bring on the first time sales hire, because that's obviously such a critical one?
Speaker 1:We wanted to get to where we're confident. We've hit product market fit first and do founder led sales up until that point. Because the feedback loop is really helpful, that I talk to customers, I hear their perspective, I hear their pain points. I understand why they think our product's not good enough, and then we have a really tight feedback loop with the developers. We get stuff out usually the same day or within the week and then that really impresses the customers and it really just helps us to build something really useful. Once we hit that product market fit perspective, which I think we're right on the verge of, I think that's when you've proven kind of that sales motion. I think that's when it makes sense to bring somebody else on full time. That's in a leadership type of role, yep.
Speaker 2:Yep, I think you're generally on the right path there, and then let's just talk about the general growth of the company.
Speaker 1:I know you mentioned that before we got on that you have about 10 people. How did you find hire those people? What was your primary motivation to raise was how have you gotten from that co-founders to the traction you've gotten so far? Interesting approach. I don't know if this is the best one, the worst one or somewhere in between, but for our journey it's worth considering, at least for people.
Speaker 1:What we started with was I found two really passionate about AI guys in the Netherlands and the Middle East who just really wanted to build something on a Discord channel in AI right after ChatGPT was released and they were affordable and also just really wanted to be a builder, and so I hired them to build out basically a proof of concept and use that proof of concept plus a bit of vision to raise an angel round from kind of extended friends and family of vision to raise an angel round from kind of extended friends and family. And we had a decent number of people that were interested because we've done I've been doing like a real estate investment group and a lot of those group. The people in the group were lawyers or other people that had had funds that they were interested in investing in AI and this was a pretty good vehicle because there wasn't a whole lot early on of ways you could invest in kind of the ai boom, um, just because you can invest, like in us or google but google is such like a weird type of play right so, um, so that that helped us and then that gave us enough money to where we could fund real development and um, and really grow enough to where we could get a vc on board and show, show some customer traction and um, we well, and I brought on our CTO right after that. He was somebody who saw like a Discord job posting and after I'd been really frustrated by like everybody that I spoke with, he saw this like three page posting that I had that was in a lot of detail about exactly who we want. He responded to every single like paragraph or every single sentence in it just explaining. Here's exactly why this perfectly resonates with me and the two of us just have a very similar view on just culture and speed and the importance of iteration and just being really aggressive and all that. And so he's had just a fantastic technical background where we were just very much in lockstep and it is someone who I feel like I can perfectly empower and he can just deliver. So that worked out pretty well for us.
Speaker 1:From there, we try to be smart about the hires, that when you're a startup, you end up seeing like, ok, we really need someone to start building this out quick. A customer really wants it and we're doing. We're really maxed out on capacity, let's bring somebody in. But you have to be deliberate. I think everybody has heard this before, but those first few hires are so important and they're very likely to set the culture of the company. So we really try to bring on people that really could cut it and we're really going to fit the right kind of fit the cultural mindset we had and really understand how to build in the AI world. And so we had pretty tough kind of case type questions, had them think through different problems, solve some of them live or some of them just verbally, and with that I think we ended up getting some really good picks and we've still got most all the team today for anybody that we've hired. That's fantastic.
Speaker 2:So you're at 10. Now. What do your plans look like, not just from a headcount perspective, but just generally, for the growth of the business over the next six months, a year or two years?
Speaker 1:I don't want to be one of those companies that grows just to grow people, and I think if we were to grow headcount a ton on the developer side, we'd start seeing some operational inefficiencies where, like, the team size right now is pretty efficient and it kind of forces us to think about how can we solve the problem the easiest possible way, rather than like here's, like the big, if we like waterfall it out. Here's how we we solve the problem the easiest possible way, rather than like here's, like the big, if we like waterfall it out. Here's how we might solve it. And so I don't want to like see a little bit of growth and then hire three more people on the developer side. We do need some more sales support, so eventually we'll bring someone on there and then there's probably gonna be a little bit of growth. Beyond that, maybe some help with some of the routine tasks to where I can focus more on product and the customer. But as much as I can, I want to automate that.
Speaker 1:This is a personal opinion, but, being part of a big company, the kind of trend of talking about founder mode resonated pretty well with me, where, as a founder, let's give like the most ridiculous example, where it still makes sense. So, like on support, I think a lot of people will have support be something that they outsource. But, like when I look at like a customer complained about something and I got an email about it in our email, I'll see it. I'll immediately know where in the product the problem is stemming from. I talk to the developer directly, we talk, we figure out exactly what the problem is and how to solve it, and then the developer releases something right away and then I can tell the customer exactly what we're doing to fix it and then I can give them free credits or some kind of refund or something like that and the problem is solved.
Speaker 1:If we had a support person it would take. They just realistically wouldn't care enough to take the time to really understand the product. They'd probably go through like a longer channel to diagnose these issues and it just slows down the business. So eventually you have to scale right, you have to bring in people, but to the greatest extent possible I'm trying to run as automated a shop as we can and use some of these new tools to do some of these underlying functions and then just take on a little bit more of the work. That's going to be more cross-functional.
Speaker 2:Yeah, I think that's a great approach. Like you said, eventually there's going to be a point where you can't get away with it, but until you reach that point and you don't have to introduce just extra steps or lack of feedback loops, then I think that's the right way to do it. So, final question then, since you mentioned that the founder mode when you were in the big corp resonated. There's probably going to be some people who are in big corporations who listen to this and feel inspired by your own moves. So I'm just curious what advice would you give somebody who wants to make the leap from corporate to startup leadership or even starting their own thing?
Speaker 1:Yeah, a couple of things. What worked for me at least was I jumped around a lot. I did. I was a lawyer, was in supply chain, worked for a consulting firm, worked in an e-com group, did transformation, did a bunch of finance stuff and then ran an engineering team. And having that mix of backgrounds you don't need to go that extreme.
Speaker 1:That sounds kind of crazy, but jumping around a few times is really helpful in helping you just understand all the different ways a company operates and you'll start picking up, like when I'm in marketing and I understand the finance component, I understand the vendor component. It just helps me run that better and then it helps you kind of zoom out big picture when you're kind of thinking about the whole company a lot better. So I think that's one. The other thing is that these the strategy parts of the corporate when, like the corporations discussing strategy at like your big off sites or whatever, those can be pretty helpful, trying to just say like really adopt like a mindset of, okay, what are we doing? Well, what are where does this strategy not work? What are the threats? And being able to not just pare it back the strategy that your CEO told you, but to really respond to really tough questions about it and really think through the vision. I think that that's really helpful.
Speaker 1:What we did a good job of coming up with at least a high level strategy at AT&T. I don't think we executed it as well as we could have, but our strategy was always really good and being able to kind of think through the elements there was really helpful. And then the last piece is you got to pay a little bit of attention to the startup space. I learned a lot doing this and really jumping in and I had a bit of experience before. If you just go in totally cold, it's pretty hard. So podcasts like yours are a great avenue. Just getting involved in the communities, being close with a startup, maybe as an advisor or something similar, would be really helpful. But try to just gain that kind of closer, first-hand experience.
Speaker 2:I love that. Well, justin, this has been super fun. Real appreciate you coming on. Thanks for joining Great speaking with you. Bye. Thank you for tuning in to this episode of Seat to Exit. I hope you found today's conversation insightful and valuable. If you enjoyed the episode, please take a moment to subscribe, leave a review and share it with your network. Your support means the world helps us continue to grow and bring more incredible guests onto the show. Now for more content and updates, follow me on LinkedIn or Twitter, or you can check out MindHire, where we help startups build exceptional teams. Thanks again for listening and I'll see you in the next episode of Seed to Exit.
