Jake Aaron Villarreal: I'm Jake Aaron Villarreal, born and raised in Silicon Valley. I'm here to take you behind the scenes to share what it's like to be a startup founder, the journey they're on, the problems they face, the products they build in an effort to make our lives better. I'm excited to have with us today Rob Scott, co-founder and CEO of Monjur. Rob, welcome to the show.
Rob Scott: Thank you, Jake. I'm happy to be here.
Jake Aaron Villarreal: I'm excited to have you. Where are you joining us from today, Rob?
Rob Scott: I'm in the Dallas-Fort Worth Metroplex, just uh near DFW airport in a small town called Trophy Club.
Jake Aaron Villarreal: Really cool. How far is out from Frisco?
Rob Scott: Maybe 40 minutes by car.
Jake Aaron Villarreal: Okay, cool. I'm looking to head over there sometime next year and just go check out that big Dallas Cowboy campus and, you know, hopefully they can get a couple more wins this next year. But anyway, let's see. We still got a chance maybe to get one or two more before the end of this year, but it's looking pretty grim.
Rob Scott: Yeah, no doubt.
Jake Aaron Villarreal: Well, let's talk about something that's not looking grim is, is your background. Uh, a little bit more for the listeners about Rob. Uh, he advises technology companies of all sizes regarding offering cloud and managed services. He graduated Summa Cum Laude from Austin College in Sherman, Texas with a BA in economics. He earned his law degree from Hofstra University School of Law in New York and he now leads a legal AI tech startup. Rob, you've got a lot going on. Background, very focused on the legal side. Excited to dive into that. Before we do, give us a little bit of your background. What were the early experiences that kind of shaped you to get on the path where you're at today?
Rob Scott: Yeah, I would say that, you know, early on in my career, I gravitated toward computer law related matters. Some of my clients were the early dot, you know, pioneers in web hosting, others. You know, I was in very early at the, at the foundation of the trend of IT managed services and outsourcing. I helped many clients get into the cloud when that happened. We've, you know, since created a practice in AI and robotics and privacy, security, and compliance. So, I've just kind of been always in and around computer law related matters. And since 1999, I've been the managing partner of a boutique law firm called Scott and Scott that focuses on computer...
[Rob Scott's Background and Legal Expertise]
...law matters.
Jake Aaron Villarreal: Well, that transition from being a lawyer in law to being a tech entrepreneur, not everyone can bridge that gap. Is this your first startup?
Rob Scott: It is. It's my first startup. But my practice, you know, over the years has been both in software law and managed services. So, I've counseled many clients on those topics. It certainly is different being an advisor looking at legal issues versus being the CEO of the startup. But I was familiar with many of the business model issues and, and, and some of the core concepts around software as a service and managed services. Um, so I, I felt like I had a little bit of a head start, but it's been a tremendous learning experience. I, I can assure you.
Jake Aaron Villarreal: For others that are in whatever space they happen to be in, it could be healthcare, it could be different industries, what's been helpful for you as building your first startup, specifically in AI around legal, but what's been helpful for you of kind of getting it all in place and making sure you're tackling it the right way from finding people to build products to the strategy, the roadmap to really getting it off the...
Rob Scott: Yeah, I would say focus is probably the most important thing. I think a lot of startups start with a cool idea and build a cool thing and then go find someone to sell it to. Our strategy is a bit different. You know, we ask our clients what they need and then we build that. So, ours is more of a feedback-based, client-driven approach. We don't build what we think is cool. We build what we think is going to help our clients. And for us that's really amounted to a focus on delivering always-on legal assistance to our clients through our AI product called Monjur Pilot that allows us to deliver chat-based legal assistance customized for each one of our clients, grounded in their agreements and available 24/7, but always supervised by a real lawyer.
And so if you think about Monjur as a startup, it's a legal service. And so from that perspective, my domain expertise, my background, my career is not irrelevant. It's central to the services. But now we've got a different business model and a different tech stack than what a typical legal service would have. So in many instances, it's not that far of a gap between a particular career that you might be in now and turning that into a software or managed service. Uh there...
[Transitioning from Law to Tech Entrepreneurship]
...are some fundamental things that need to be present and there certainly are reasons why one would want to try to do it, but it's not such a big change. Because in the end, particularly when it comes to AI, I think it's the people with the domain expertise that leverage the AI in a way that makes sense are going to be the winners. And you could put up a hundred smart data scientists against what we do at Monjur, and if they lack the legal domain expertise, their solution will be nowhere near as viable as ours, for example.
Jake Aaron Villarreal: Yeah. Really cool. Well, we've had other legal tech companies on the podcast and seems like there's plenty of opportunity for a lot of players. It's not a one-company-will-own-it-all type scenario. They have little niche areas of focus. When you look at your customer base and kind of the vision of where you see your application going, what's different in terms of what you see, what you're building versus any other legal tech company in AI?
Rob Scott: I think the biggest distinction between our approach and what we've seen to date is we're building an, an attorney supervision platform for clients to use AI. Right now, clients are faced with two untenable options: traditional legal services that are slow and costly with an outdated hourly business model, or free, unsupervised AI-based help. And what we're bringing is something that leverages the AI but keeps an attorney in the loop and makes sure that things like hallucination and truncation and summarization uh don't wind up hurting the clients. As many times as OpenAI and these other platforms are warning people not to be using these platforms for legal applications, we all know that people are. I'm trying to give them a solution so that they can leverage AI and do it in a way that's safe, that puts a lawyer in the loop so they can have all the benefits of the AI, but also get the protection of experienced, licensed attorneys to help them with that last mile, the part that is unknown today when they use open LLMs for that purpose.
Jake Aaron Villarreal: Yeah. Well, there are some risks if you use OpenAI or any other LLM to get legal advice. And you actually had brought up a scenario with a gentleman, I think it was in Canada who uh was in the space and had maybe done some, I don't know, searches or did something with LLMs and the hallucinations came up and now he's uh facing some unpleasant scenario. Yeah. What happened there?
Rob Scott: That particular case is one in Canada where a lawyer was referred for criminal contempt, held in criminal contempt of court for using a large language model to prepare a brief for submission to the court that hallucinated case citations and misrepresented the state of the law in support of the argument in the brief. This happens all the time when you use LLMs. They make things up that sound...
[Client-Centric Approach in Startup Development]
...plausible, that are completely fabricated, and they don't tell you when they're doing it. And so in a 30 or 50-page brief—I don't know how long that brief was, but a very dense legal document—it creates a very significant verification problem. One law professor has referred to it as the verification paradox. The more you use large language models, the more time you have to spend verifying all the nonsense that they hallucinate. And lawyers are getting in a lot of trouble, including that lawyer and many others, for using LLMs, filing papers with the court that later become to reveal that, later, that they were subject to hallucinations, and the courts take this very seriously.
And so my point to you was if lawyers are getting in huge trouble using LLMs for legal workflows, what is the risk to the non-lawyer who we both know are using these tools extensively as an alternative to seeking legal advice? And that's where Monjur Pilot is trying to bridge the gap to offer a fully powerful AI solution that's using every means possible to limit hallucinations, including RAG architecture and confidence scoring. But at the same time allowing clients to use the full power and creativity of the large language models and give them a means to effectively, affordably, and quickly get a legal review of that.
Jake Aaron Villarreal: So within an organization, is your platform specifically for the lawyers within that organization that's able to take advantage of AI, your system, to do their job better, but know it's going to be true in terms of the data and no hallucinations? Versus, you know, a consumer like myself, for example, as a business owner that doesn't have a lawyer on staff all the time, that will just go to an LLM and come up with an agreement and assume it's okay and kind of go off that. So, am I not a target for you, or is it, am I also a target, a customer?
Rob Scott: You are. You are indeed. In fact, we don't plan to sell our solution to law firms. As you mentioned, there's plenty of players, very established players that are building tools for lawyers to use, right? Ours is that second category. We put the tools in the hands of the client and then we give them attorney supervision and a safe way to use the AI for legal workflows. Doesn't require them to make this choice between expensive and outdated legal services and free, unsupervised AI.
Jake Aaron Villarreal: Yeah. Well, that's got to be a massive market because a lot of people that we talk with all the time are saying, "You know, I've cut my expenses down in these areas with AI and it's been great." And, you know, legal is one of those buckets. It's not always a bucket that you need on a daily or weekly basis, but you know, annually it certainly comes up. So, for, when you looked at the market, what's that TAM look like for you? How big, how big is an opportunity like this?
Rob Scott: Focus. Our focus today is using this...
[AI in Legal Services: Opportunities and Risks]
...technology to serve our existing customers. And today we have approaching 1,000 customers that are all small business customers. Many in IT, many in software, many delivering AI services, others in digital marketing, but these are tech service companies, recurring revenue service businesses. They come to us for our legal agreements and those legal agreements have now been turned into AI knowledge bases that power these legal assistants and allow legal workflows like redlining to be automated.
Jake Aaron Villarreal: If you can, feel free to answer this question or feel free not to answer this question, but take me inside how you actually built this system when most AI legal tools are still struggling with accuracy.
Rob Scott: Well, that was the first thing. You know, I tested every combination of large language model, operating instruction requirements, and I got almost nowhere with the issues of hallucination, truncation, loss of context, size limits, all the things that are core to sort of LLM made it to where I, for a year and a half, could not make very much progress. And then I found a different architectural model grounded in RAG architecture, which is research augmented retrieval or generation—research augmented generation, I apologize. And what we found is just by changing the architecture, we had a 30 plus percentage point gain in what I call "OS compliance," the extent to which the machine listens to the operating system instructions, and hallucination, the extent to which the system just makes things up that are false. And so we got to a point now, "Okay, we've got something we can work with and start testing and iterating." And that was a big part of it.
As we went through the testing, we realized that the agents were pretty good at knowing when they gave a well-grounded answer or not after they answered it. And so we created a proprietary confidence scoring system that reduced the hallucination effect to greater than 98% accurate because the way we train the agents, if they're not very confident in the grounding in the data, in the RAG or the knowledge bases, they don't answer. And so the combination of the RAG architecture and the proprietary confidence scoring that we developed really put us on a footing where we had a legal-grade AI that we felt that we could start sharing with clients and get their feedback and start testing.
Jake Aaron Villarreal: Wow, that's amazing. Well, you have the legal mind. Are you also an engineer? And if you're not an engineer, how did you go about... you're talking about building AI and AI agents and orchestration of agents. We see this with engineers that are coming out of Stanford and they've been building...
[Target Audience and Market Strategy]
...technology for years. But how did you get started with building technology and AI?
Rob Scott: So I was just a self-taught user. So I was working on the legal issues involving AI, like intellectual property and other nuanced legal issues before the LLM came out. And so when ChatGPT came out, I was one of the early adopters and I began religiously using and testing it, trying to use it for legal applications that arose within our business, developing legal document analyzers, um, and a number of different prototypes and, you know, finding that those challenges with accuracy.
But I am more of the product designer. I wrote the white paper for what the vision would be for how it would work, what it would do, how it would be organized, you know, the underlying data model. Um, and the beautiful thing about AI is it speaks English. You don't have to know a lot of code. And so for me, that lack of engineering and lack of developer background wasn't a huge hurdle as it might have been in the past because of the plain language capabilities of AI. But we quickly got our product team involved. We quickly hired AI developers to start building that vision. And so I don't want to pretend like I'm anything more than uh the product designer. I built some of the prototypes. I have a very thorough understanding of what types of things work for legal applications and what don't. I'm very knowledgeable about the different LLMs and how they compare in terms of their capabilities when it's, you know, talking about agentic workflows for law, but that's all learned behavior. Um, I haven't had any official engineering or training in that regard, but our law firm was always known as being very technical. You know, the, the legal work that we have always done has been very technical and we get called in on the cases that are very technical in nature. So over the course of my career, I've been exposed to many software-related and, and computer law-related issues and developed some technical capability as a result.
Jake Aaron Villarreal: Yeah, that's great. Well, I've talked to hundreds if not thousands of founders at this point, and talking to you, it seemed like you had the technical know-how even though you've got the legal know-how in both. That combination, so pretty lethal. I like your background. I like the space you're in. I think that there's a ton of opportunity for it. You bootstrapped a 3 million in ARR before raising capital. That's rare in any category. What did bootstrapping force you to get right that venture-backed competitors might be missing?
Rob Scott: I would say with bootstrapping, you have...
[Building a Reliable AI System]
...to manage your cash flow in a way that's much different than if you're funded. And frequently when you're bootstrapped, you have to make bad decisions for cash flow reasons that if you were funded, you wouldn't make. I'll give you an example. Every year when we were bootstrapped, I would do a, a, a heavily discounted three-year prepaid in December. And a lot of clients would buy it because they had extra cash. They were looking, you know, for last-minute expenses in December to, you know, uh qualify for deductions. And it was easy for them to get a huge discount, prepaid for three years, and they're covered. For me, I needed that money to pay payroll, to buy events, to keep the lights on. Even though today I would say, "Wow, why would I ever discount my subscriptions in a way that would damage my growth of annual recurring revenue or my average revenue per subscriber, my ARPU?"
And so, you just have to think about things a little differently when you're bootstrapped. Cash flow, runway, expense management, sponsorship levels, projects and initiatives that you can take on tend to be more narrowly viewed and you have a much more finite pool of money to invest. And therefore, in answer to your question, you better get your, your investments right because you've got some room to make mistakes, but not very much.
Jake Aaron Villarreal: Yeah. Well, lots of decisions to be made. Uh, you're bringing your development team in-house, you're scaling at a much bigger clip. What has building teams taught you about hiring, especially for roles that didn't even exist 3 years ago?
Rob Scott: I would say, you know, the fundamentals of building a team are about cultural fit. You know, don't hire someone to work in a company that grows at 200% that's not really good with change. Um, you know, if you want to hire someone into a company that's growing very quickly, you make sure that they are learners, that want to continue to learn and grow, and don't find shifting priorities or shifting responsibilities to be destabilizing for them. Um, and, and in addition, what I've learned is that when your business starts to crest towards 15 employees and up, your operating system—for those of you who know about EOS or the book Traction, there are many variations of these operating systems, but the system by which you secure alignment, measure KPIs and key objectives, and hold people accountable becomes central to your success in a way that when you're 10 or 12 people is much less important.
Jake Aaron Villarreal: Yeah. KPIs and metrics and rubrics of...
[The Role of a Non-Engineer in Tech Development]
...what you know, success looks like, and how to measure and manage that, I think is incredibly important when you get to the right scale where it really matters. But when you're bootstrapping early on and it's you and a co-founder, you know, it's all about just finding market fit and building a product that companies want and need. And then, then you try and find the right people to help scale it. As you continue to scale yourself, let's fast forward 18 months from now when you're sitting at 6 million in ARR, closing your Series A and expanding internationally or wherever you go. What gaps do you need to close to accelerate business, whether it's operations, systems, or people?
Rob Scott: There's some to do in all of that, right? I mean, as you grow, you know, there's only so many levers to pull in a B2B SaaS company, and you need to be pulling all those levers all the time. Those levers include, you know, how you onboard customers and, and what your go-to-market motion looks like and how capital efficient that is. So, we're constantly looking at that growth engine, that top of the funnel, analyzing every aspect of that and making sure that we're optimized across that sales engine. Close attention to conversion and staffing around not only sales and business development, but it becomes more important to have really good RevOps teams as you start to scale up.
For us, our primary go-to-market has been event-based. And so, we're heavily focused on optimizing that event strategy as well as activating a paid search and paid media strategy alongside of it. And that's an important aspect of our, our scaling strategy. But the people side of it is probably the biggest. We'll be hiring five or six people in the first quarter and five or six people in the second quarter. And we expect our headcount not to grow in a way that's necessarily linear with headcount, but one of the primary purposes of our Series A round will be to build out that senior executive leadership team. So our strategy to date has been sort of bottoms-up, get the worker bees and get the executives later. And with this Series A, we'll be focusing on rounding out the bottom of that org chart, getting the right worker bees in the right places, but also starting to build that c-suite of executives around CTO, around CRO, CFO, you know, those key roles are an important part of our scaling up and and will be one of the primary purposes of raising the Series A, as well as just scale up around marketing uh and, and go to market effort, efforts makes up the bulk of where the money will be spent.
And the balance is in just continuing to improve our internal engineering and AI capabilities so that we can share that with our clients and continue to iterate on our platforms, including, including our core agents, as well as integrations with client systems and further development of our orchestration platform and our Microsoft Word plug-in.
[Bootstrapping vs. Venture Capital]
Jake Aaron Villarreal: Yeah. Well, you're tackling a lot, but you're in market, you're in revenue. It sounds like things are going well. From the outside looking in, what's a challenge that, maybe one of the bigger challenges you're working through now that maybe others don't see, and this is really for the other founders that are building too that they might be going through similar things that maybe you figured out or maybe you're still struggling to figure out.
Rob Scott: I would say that, you know, having a SaaS 1.0 platform to start, as you think about moving into AI, is both a blessing and a curse. The blessing of it is that you have real customers and real revenue and you've got a team of people that at least understand how to operate a software business. The curse is that you've got a lot of tech debt and a lot of people that have been in a business that is now changing very dramatically, and your 2.0 business may not be very similar to your 1.0 business. And it's that tech debt and that cultural shift that cause some founders to decide they want to sell their 1.0 business and not try to make this transition.
If you decide to make the transition like many of us are, including us, what you, what you face is a messaging challenge that can be really difficult to overcome because you've gone to market with a certain message that's not AI-forward and it's worked for you, or you wouldn't be where you are today. However, you have a belief that where you're going in the future is AI-forward or AI-first. And so, how do you make that messaging transition that's true to the market position, brand, and, and value proposition that you've stated in the marketplace to date, but that also has this AI advantage? And I would say that for us that's been a big struggle, just how to message around the role of our new AI platform. What's staying the same? What's changing? How does it benefit our clients? Why should they care? These are all things that I think are challenges for us in terms of how we go about making this transition.
The other for us is that, you know, with AI, you really have, you're really managing multiple products. You know, for us, we've got the agent layer and the knowledge base layer. Those could be deployed into any, you know, platforms. But we also have our platform that, that we're building in. And so we've got, you know, AI infrastructure, we've got web app infrastructure, and we have plug-in infrastructure. And a big part of what we're moving toward is integration infrastructure to bring all these apps together for our clients into a single repository, so that our agents will be knowledgeable about what's going on in other parts of the business that affect legal, like accounts receivable and contract renewals for example.
Jake Aaron Villarreal: Yeah. Well, contract renewals were huge. I spent seven years at Oracle. It became the lifeblood of the company after you sell a product or service into an organization, multi-million dollar deal.
[Hiring and Team Dynamics in a Growing Startup]
Renewals keep the lights on and there's changes and contracts and it was always hung up in legal departments like, "We got to get this stuff through." So if there's systems that facilitate that and bring the cost down to make that work, I mean that's just, I mean I'm just thinking out loud like what I saw. But I want you to kind of fast forward 5 years from now. From your perspective, what do you think the percentage of legal work to, do you think will be handled by AI versus human attorneys? And, and what's the work that will remain uniquely human?
Rob Scott: First of all, I don't think there's going to be a long, for a long time, a distinction between the AI work and the lawyer work. I think that lawyers will use AI tools and they won't see this dichotomy that we're seeing in this transition. You know, it's like, you know, a famous astrophysicist said about the internet: soon it will be everywhere and nowhere. It's in your clothes, it's in your eyeglasses, it's in...
Jake Aaron Villarreal: Right.
Rob Scott: And I think the same will be true of AI. And so the idea of a lawyer, you know, in five years not using any AI technology is going to be very rare. So all lawyers will use AI. And what it means, will mean to be a lawyer is what it means today, which is to know when it's wrong. I mean, the true power that I have as an experienced attorney is when the AI spits something out that sounds plausible, I know whether it's right or wrong. And I think that will be the role of lawyers involving AI for a very long time.
The other part of what AI doesn't do is empathize with clients. It doesn't help them address the emotional side of legal matters and it doesn't explain things in a way that makes them easy to understand. And so I think the role of lawyers in the future will continue to be as counselors and advisors to clients based on relationship strength and trust, but also the ability to make AI tools sound more human. You know, one of the things that we're very focused on at Monjur is making our legal assistants sound like real lawyers, not like AI output. They're trained to use the same vocabulary, metaphors, explanations, and so forth of the humans that they're trained on. And I think going forward, lawyers will, many of us will be dedicated to training AI systems to be more human, to be more lawyer-like. And nobody's going to be in a position to do that other than the lawyers.
Jake Aaron Villarreal: Yeah. Well, I know that AI is helping lots of industries become more human-like and communicate effectively and with empathy. It's changing. I mean, I think there's some areas that there's some work that needs to still be done, but the voice AI is incredible. I mean, I...
[Future Growth and Scaling Strategies]
...for one, like many entrepreneurs and operators of companies, have a, have a business coach, and I also have an AI coach from the same company. And I will tell you that the AI coach actually in some ways is available whenever I need an answer to something and it's very empathetic and it communicates and it understands me very well. And in some ways you can almost say, "Well, maybe it replaces coaching services." I wouldn't tell my coach that and I don't, it won't for me personally, but it's a, it's a tool that coaches can use. It's going to get a lot more data at different times than maybe it won't get for me directly too. So there's some real... to me it amplifies the coach in the same way that our systems amplify the lawyers and give them more reach.
Rob Scott: And, and I would say Jake, to your point, I'm not surprised by your feedback. Our clients tell us that the 24/7 high availability of the agents is one of the primary value propositions. It's not that they're smart. It's not that they're fast. It's not that they're human-like. All that is true. But the thing that stands out the most in their mind is, "It's always available. I don't ha- if I wake up in the middle of the night with a concern on my mind, I can ask the AI a question, and it gives me an answer at 2:00 in the morning, at 5:00 in the morning, at 9:00 at night," right? In ways that traditional legal services cannot answer for that, in the same way that you're talking about with the coach. You could wait and ask all those questions to the coach, but it sure is nice to have that immediate answer.
Jake Aaron Villarreal: Absolutely. Yeah. And that right there is a value that you're willing to pay for. So, it's not just about, can you give me the data because it can, but can you give it to me when I want it, whenever I want it, and help me reduce my stress? Because in the end of the day, when it comes to legal, a lot of that is stress related. Just natural psychology behind, "Am I doing the right thing?" And if I know when I'm, I need to get the answers at the times that my lawyers might not be available, that's a huge value that I think anybody should be worth exploring and trying out.
Rob Scott: Yeah. And, and I think Jake, for us, we did 27 client videos. In each of the videos, we asked the client, "How does your relationship with Monjur impact you?" And almost all of them said, "I sleep better at night knowing that I'm protected." And that speaks to your stress, you know, your cognitive load, you know, kind of point, which is there's a certain feeling that you get when you leave your estate planning lawyer's office and you know that your estate plan is intact, right? I mean, you just get this sense of relief. And I think all legal services in some ways are designed to deliver that value. That's what lawyers do is give clients clarity around the situations they face and provide them with some relief around um, easing their mind about these challenges. AI is one way that lawyers can do it at scale and 24/7.
Jake Aaron Villarreal: Yeah. Well, what a great story. There's a lot of future ahead to build. Excited...
[Challenges in Transitioning to AI]
...to see where things go for you, Rob, in the future with Monjur. When you look forward after building this company that could be a hundred million, a billion dollar organization, maybe much bigger, when you look back on it, what do you want to see that you feel will truly matter?
Rob Scott: The way I think about it is we wake up every day to protect clients. Doesn't matter what tools we use, doesn't matter how the technology evolves, we'll always use whatever tools are at our disposal to help more clients better. And if we do a good job of helping a lot of clients really well, then the financial implications of that will be realized and deserved. But we're only going to focus on protecting more clients and protecting those clients better. And if that happens, you know, my financial future, the financial future of our employees and our clients will be brighter.
And so I don't, I try not to focus too much on the financial aspects. I like to tell people I was rich before I started Monjur, um, just as a way to kind of defuse the motivation of financial gain. And I would say to those founders that are out there that are focusing their energy around financial metrics, consider changing your focus to helping people and serving, and serving more people better. And I think if you dedicate your life to that, it will be a life well spent.
Jake Aaron Villarreal: Yeah. Well, on that note, Rob, I want to thank you for your time. Also want to thank the listeners for listening. If anybody wants to find you, Rob, or wants to find your company, Monjur, where do they go?
Rob Scott: Well, you can find us on the web at monjur.com, m o n j u r.com. We're also on all the socials, LinkedIn and the rest. And you can catch me at rob@monjur.com. Love to hear from you, get your feedback, any questions you have. Would love to chat. And Jake, thank you so much for having me on the show. I've really enjoyed it.
Jake Aaron Villarreal: Well, thanks for joining, and again, thank you to the listeners for listening. I'm your host Jake Aaron Villarreal signing off for now, but can't wait to catch up with you all on the next episode. Until then, Rob, take care. If you like what we're doing, don't forget to subscribe, leave a review on Apple Podcast or wherever you listen, and follow us on YouTube where we go behind the scenes to learn what it takes to be a startup founder.
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