How do you fundraise as an immigrant founder with visa issues?

Jason Kirby (00:02.624) Welcome back to the show everyone. Today we have Pratik Josie with Jo. I said Josie. right. I'm just going cut that All right, everyone, welcome back to the show today. Today we have Pratik Joshi with us, founder and CEO of Pluto Shift. Welcome to the show. Prateek Joshi (00:23.354) Jason, thank you for inviting me. It's great to be here. Jason Kirby (00:26.594) No, I'm excited to have you. You have a fascinating story as an exited founder, a machine learning author who's written 13 books and not just, you little books like textbooks. Uh, so, and before the day of LLM where you could have Chad GP to do it for you and you built in, you know, great company and now you're a VC. You have an incredible story. What is it? How did you get Prateek Joshi (00:50.598) Yeah, during my 13 books phase, I wish I had LLMs, could have really, really used that. So I wrote them before all of this. So yeah, quick story. I was born and raised in India and southern part of India, actually a small town in the southern part of India. And yeah, I grew up there and I came to the US to do my masters. And then right after that, which was in LA, I moved to San Francisco Bay area. for my first job, which was Nvidia. And I joined their AI team. And back then, was very early, just trying to figure out, OK, what is this thing? Can we make it work on mobile devices? Do we have enough compute? Will it look cool? Will people like it? Will applications be useful? Or will it be demo -ware? So very early days of figuring out how to make it practical. So that was my first job out of college. And then, I've been building and shipping AI products for a while now. And yeah, and also during that time, I used to write a blog. I I still do in different shapes and forms, but back then I had a small blog that I just talked about. If I discover something interesting or useful, hey, I discovered this cool new thing. I just felt like writing about it. And yeah, that I I just did that and one day a publisher got in touch and said, hey, I know your blog. We like it. Would you like to write a book? And I said, wow, that that looks interesting. That sounds cool. A book author. Amazing. I'm okay, let's, let's how hard can it be? I've written a bunch of blog posts. Let's do it. And the first book was excruciating. I realized that writing like, you know, a blog post with like 700 words. that nobody to check or approve what I did was a breeze. Writing 300 pages where it goes like review after review and like, oh, this is not cool enough or not fun enough or this, I don't know what this paragraph means. So that was the first book, got through it. And then once you got the hang of it, I kept writing. And then after 13 books, I told the publisher, have nothing else to say. I'm going to stop now and I'm out. So that's that. Prateek Joshi (03:17.828) Yeah, so that and Jason Kirby (03:18.146) Well, let's just pause right there. You got to 13 books. Like that's, that's pretty substantial and like hundreds of pages each. of a, you know, and the topic in Crackman Row was around, you know, Python AI, machine learning, you know, so very heavy, technical oriented content that, yeah. And to kind of give everyone a reference of time, like you were at Nvidia in like 2012 timeline, correct? Uh, and then you did the books for a couple of Prateek Joshi (03:45.958) Yeah, 2010, 11, 12. Yeah. Jason Kirby (03:48.426) Yeah. So you had, you know, you're at the of the forefront of AI and machine learning. Well, back then was more machine learning, less probably AI. And you write several books on the topic. How did that lead you to starting a company? And what was that transition Prateek Joshi (04:08.44) Yeah. And just to set the context, the way I look at these terms, AI is the goal and machine learning is a vehicle to get there. It's one possible vehicle. There are multiple vehicles to get there. And that was always how I looked at these terms. And data, for example, is the fuel for that vehicle. So different roles in this world. The books, when I started writing the books, I realized there's so many things you need to know to make ML practical, right? To go from theories and algorithms, just very theoretical. How do you go to the real world and make it practical? And that was one of the big interests I had is to bring AI to the physical world because in the past, we know how to apply AI to images or search engines, like virtual world. And then I was very interested in physical infrastructure. So how do you bring AI into the physical world? And that was the big insight into launching the company, Plutorship, is to do just that. there was a big, and there still is, big delta between how much AI is used in the virtual world and how much it's used in the physical world. Because it's not easy to make it work. So that was the insight. So launch the company with that insight. And then at the very early, the first thing we did was out of all the physical infrastructure, let's start with water infrastructure. Because water as a topic, it's very close to heart. I grew up in a town where water was scarce. In fact, there were many days when there was no water. So we had to like store water until we get it the next time. The taps, there's no 24 seven taps concept, at least when and where I grew up. Water is a new topic very close to my heart. So did that and then expanded to other types of physical infrastructure. And yeah, that became PluraShare. We served large customers, Fortune 500 customers over the years. And yeah, that did that for about seven years. Jason Kirby (06:16.226) So let's break that down. You went on to raise over 16 million for Plutoshift. So that's not downplay. You raise a good amount of capital. You were a solo founder. What was it like raising capital? Walk us through the initial stage where you either started the company or raised the capital. What came first and what happened thereafter? Prateek Joshi (06:40.324) Yeah, once I decided, okay, this could be a company, I started doing a bunch of research on the customer side to kind of understand, is this real? Will customers even care? Do they care about doing this? And so did a bunch of that and then realized, okay, there is a small group, a small group of people who are extremely enthusiastic. And that was like the first... hint of a signal that, okay, at least a small group cares enough about it so that they want it to exist. So there was that. Once I had that, I started talking to investors. And the biggest, by margin, the biggest barrier for me was the visa situation. Because here, to start a company, you at least need a valid legal framework, right? And I just didn't know. wasn't rich enough to afford a personal lawyer to go find a path. And then to incorporate a company and do that full time, I didn't know how to do it on a work visa. So that was the first big barrier. So when I started talking to a bunch of people, I came across Unshackled Ventures, which amazing, amazing, amazing venture firm. know the two founders really well. And now I know them well, but back then I So yeah, I got in touch and that was my first like first true check because nobody else wanted to deal with the visa situation. The investors were like, I honestly, I don't know how to do it. You figure it out and then come back and maybe you'll talk about fundraising, right? And yeah, so that was my first like pre -seed funding, did that. And then they built the product, like there was a demo. built a real product, got a couple of pilot customers, validated that it was a real need. And then after that, went out to raise a seed round, a proper seed round with an institutional investor. And by that time, the visa thing was sorted. Turns out there is a very nice legal way to do it, but you need a lawyer to help you figure it out and you can't do it as an individual. Yeah, so the seed stage. Prateek Joshi (09:06.834) came, that was the first big institutional check. And then after that, that was also mostly based on early customers, the founder, pedigree, and the team, early team I had built. And then after that, the series A, which was the next big milestone. And that was pure metrics. can you show that this is the business and you can't. At series A, it becomes a little less the vision and the story a little more about you got to show up with metrics. And yeah, those are the three big stages, lots of ups and downs. And Jason Kirby (09:41.987) Yeah, let's come talk about some of those ups and downs. So when it comes to that pre -season, you're talking to investors, you're out in the Bay Area, and they're basically like, don't get this visa thing. And they're telling you no, because they don't want to do the homework. For lack of better word, it's not their focus, the friendly way to put it. But you end up getting on track of ventures. How much did you end up raising in that and from how many investors. Prateek Joshi (10:11.376) Yeah, right. In the very early stages, the pre -seed was about 300k. That's it. So we put together a small round. Obviously, it was led by Unshackled Ventures, and I got a couple of angels. But basically, like a very small pre -seed round. And the goal of the round was, can we validate? this hypothesis that we have. showed up with a hypothesis saying that, okay, this group of customers, they care about these sets of things. How can we prove it? How can we show, how can we gather proof points? So yeah, that was that. So a very small pre -seed round is what we Jason Kirby (10:57.098) No, it makes sense. at the point you get that pre -seed money, you still don't have your visa situation figured out just yet, but you're on your way and you build a team and you get a little bit of early interest for your seed round. How much did you raise in your seed round and how did you get in front of those investors? What was your process to go out and raise that seed round? Prateek Joshi (11:18.97) Yeah. And also just to add the pre -seed was when I figured out the visa situation because you cannot raise money without figuring that out. Right. So what we did was I talked to a bunch of investors. Everyone said, I don't even want to start because the visa thing looks dicey. So I talked to Unshackled Ventures and they said, this is exactly what we do. Like this is our thing. And so we figured out how to make it work, incorporate the company and then raise the pre -seed. So that's, so once we close the pre -seed, the visa thing was sorted. And then for the seed round, we raised 2 .1, 2 .1, actually, no, overall 3 .5. So it was kind of slightly, so what happened was we went out to raise about two and it quickly got expanded because we got more interest. And that was like the brief period of time when I remember the It was mostly, it's like a spike where the ups are very brief, the downs are pretty long. So yeah, so 3 .5 was the seed round and that's what we did. Jason Kirby (12:28.362) And when it came to getting those investors to the table, getting them interested, was it just people in your network? Was it warm endros? Did you kind of compile a list? How did you kind of get introduced to those investors that ultimately wrote you a check? Prateek Joshi (12:43.898) Yeah, when I came in, when I came into the ecosystem, my network was precisely zero. I knew nobody. And when people said, my God, I did friends and family around. I'm like, who are these friends and what is this family who have this money to give you? Right? What is that magical thing? So I had no family investors, no friends who write checks. And all of it was just cold outbound. That's what I did. Like I looked up people on LinkedIn on their websites, I went to events to know like who is appropriate for this stage. And then as I did more and more, then a couple of, you'll always find good people who are willing to help. that's one of the best parts about this Silicon Valley ecosystem is that for absolutely no reason, people will help you. And there are complete strangers. And now I always remember that when somebody reaches out to me, I try to, in whatever way possible, just help them out because somebody helped me for absolutely no reason. And that's what happened. So I started with a lot of cold outbound and then somebody used to respond, most of them didn't. And then somebody who used to respond, I talked to them and said, hey, this is what I'm building. And they said, I might not be able to invest, but you should talk to X, and Z. And then through that, and go to the right people. And then, yeah, that's how I raised Jason Kirby (14:15.552) Yeah, it's so refreshing to hear because it's really how a lot of founders go and do it. But you don't hear these stories and like all this kind of stuff of how they end up pulling it off. just imagine it took a very long time to build the trust and build those relationships. And that's kind of what fundraising ultimately is and why people always say you always have to be fundraising because it just takes so much to build those relationships over time. Now let's jump to the Series A. You mentioned it was very metrics oriented. Share what you're comfortable with, but at what kind of stage was your company at when you guys went and raised the Series A? What metrics did you guys achieve and how much did you raise for that Series A? Prateek Joshi (14:59.098) Yeah, yeah. So we were an enterprise software company. At the heart, the mechanics of the business was we were selling software to big companies and we had to prove or gather metrics around a couple of key things. One, how many customers were able to convince? How many number of logos, basically, who are now using your software? That's one. Just pure number of customers. How much are they paying you overall? Also on average, ACV, how much is that? Like for example, you can show over the million in revenue and if 950K is coming from like one customer, that's bad. That's very risky. You fail to convince a bunch of other customers. So the question was, what's the ACV and what's the median ACV? And then on top of that, expansion is also something we had to prove. Meaning once you land this logo, great, they're paying you 50K to use the software, very first interaction. But did they come back to buy more software from you? And in our case, more software would mean that they deploy at a second facility. Did they add more people to the product? Did they come back and ask for more features? So basically, did they consume more of your software given enough time? So these are a couple of different proof points that we had to gather. And at at CDZ, we were roughly at about north of 10 big logos, actual customers. These are not pilots or these are not like, my God, I called up my friend's friend and they're doing a LOI. No, these are like official formal customers with signed contracts, no backing out. And we had to show that there were all like late five figures or early six figures. And also with at least, I don't know, one third of the customers who started at 50K and now are at double or triple that amount within the last four months. These were all the things we had to gather to show up at CESA. And again, it's different if you're selling to SMBs, it might not be enough, but if you're enterprise, meaning if you're selling to Fortune 500s who are willing to shell out millions to buy software, this is a good, this is good. At least this is what we did to show that 10 different customers, you can call them. I gave them phone numbers to investors, like call these people, they'll verify everything. So that's what we showed up Jason Kirby (17:25.768) Yeah, I'm so glad you mentioned that because that is actually a part of the process for a lot of series investors is customer reference checks. want to make sure a good VC will do that. Some VCs will be like, I believe in you. You're great. then, yeah, not always. It doesn't always work out. But it also shows that investors care and they're willing to do the homework and get involved and get their hands dirty and check on the work. So it's great that your investors chose to do that along with your raise. Prateek Joshi (17:38.936) Alright. Alright. Alright. Jason Kirby (17:55.808) When it came to raising capital at each stage, pre -seed, seed, series A, how did it kind of vary in terms of difficulty for each stage? And ultimately, which one became the easiest one to raise for? Prateek Joshi (18:13.082) that's a very interesting question. Because one would think that the more you do it, the easier it becomes. But in my case, the pre -seed was extremely difficult, mostly because I didn't know about fundraising. I didn't know about Visa. I didn't know about company building. I didn't know anything. So was difficult for those reasons, not the fundraising mechanics. was a small part of the reason. There are much bigger reasons why it was difficult. that was difficult. Series A was also very difficult because it was incredibly, it was brutal to get these companies to pay money in a reasonable amount of time because they think in terms of quarters and years and startups live and die in like days. So to convince these big companies to look at the product, use it, consume it, sign, and then wire the money, that was very difficult. In retrospect, I think at least for me, the seed stage just happened. It was easier at least than either pre -seed or series A. So yeah, that's how I look at it. So in terms of difficulty, the hardest was pre -seed, second hardest was series A, and seed was the easiest. Jason Kirby (19:33.5) I that. You think it'd be progressively easier, but it's good to kind of see the reality of your situation. And so as you kind of progress, you're raising money, you're hitting milestones, you're attracting capital, you ultimately decide to sell the business. I guess walk us through that decision -making process and why that was the best Prateek Joshi (19:57.518) Yeah, so in our case, it was more of an asset acquisition. Basically, what we did was the company is still running under new management. I'm friends with the new CEO. And the process was basically just we were at a point where we thought, OK, we've been doing this for seven years. And we all want to do slightly different things for our next phase. And then we decided, okay, there's something on the table, right? The company, the name will live on, the product will live on, and maybe the new management will take it in a different direction. So it was mostly that. It's just that, we gave it our best. And then obviously would be great if it's like a $10 billion, a $100 billion company, right? It's great. But we're at a point where the teammates, the leadership, obviously me, the investors, we just wanted to say, hey, you know what, this is, we gave it a try and now there's something on the table. Maybe the company will live and maybe it'll become something different. So we just, that's what it was basically. yeah, so now the company is running under new Jason Kirby (21:07.97) No, I appreciate you sharing that and kind of the outcome of going out, building a company, raising money, getting some top tier logos and ultimately to an exit to kind of allow it to continue to grow and flourish into something while you get the opportunity to, I don't know, write another 13 books? Is that the game plan? Prateek Joshi (21:28.838) Oh, that, yeah, that we, I think 13 is where I'll stop. People say it's my lucky number, even though 13 is considered, historically it's considered unlucky. I want to stop at 13 and I will stick with Jason Kirby (21:34.986) Okay. Jason Kirby (21:45.475) That's fair. I commend you for getting to 13 in the first place, let alone pursuing more, or at least the first book. But now you find yourself on the other side of the table. You've raised three rounds. You're a solo founder and all this, and we of glossed over that. at least in my opinion, could be exceptionally more difficult as a solo founder to attract capital. But you pulled it off. And now you're a VC. So you're on the... of the capital allocation side at Moxie Ventures. Tell us kind of that story. Why did you pursue becoming on the investor side? What does your day to day look like now on the other side of the Prateek Joshi (22:27.93) Yeah, as I did more and more of company building and I live here in the Bay Area. So the network is amazing. And as I did more and more, I got comfortable with investors, the process. I just had a bunch of this, this tribal knowledge that you acquire just by practice. And it cannot, there aren't enough books you can read to actually know what it's like until you do it. So what I did was in the second half of my founder journey, or maybe the final third, more and more like early founders that used to reach out. They're like, hey, I saw your story on Forbes, Fortune, whatever it is. they're like, oh, I do have 15 minutes. Or can you just tell me, I'm here. Where can I go from here? Who can I talk? So I thought back to people who helped me. And then I thought, this is great. Some people, maybe my knowledge could be useful to somebody else. So I started helping people. And then, I started finding founders who are like incredible. I'm like, my God, this is insane. You're really, really good. And then I started connecting them to my favorite investors for the stage appropriate investors. And I did that. That's it. The good founder connected to good investor and my role was done. And then back then I wished, my God, if I had the ability to write a check, because they used to close the rounds with some amazing names. like, I could wish I could write a check because this looks amazing. And then I did that for 12, 18, the final third. And then I realized this is amazing. First of all, it's great because I get to meet great founders. They're doing great things. And now I wish I could write a real check because that's when you actually put your skin in the game. So that was the seed that led me to becoming a VC is once I wrapped up the company, Plutoshift, I talked to a few people and realized this would be amazing. I really enjoyed doing it part time. And now I want to do it full time. So it was more like I tested it like a trial phase. I really enjoyed it. And then now I'm doing it full Jason Kirby (24:38.058) And I see that happen quite often with founders that ultimately step down from their company or exit their company, kind of seeing the other side and joining. I think that story lines with quite a few that I've spoken to before. And kind of when you look at deals now, like if it's one thing to kind of connect the founder to a VC when you're more just an advisor or just being helpful. But what's it like when you're now representing a fund? and making decisions around capital allocation. How has your decision making changed and ultimately what are you looking for in founder? Well, your seed stage, you're like, what are you looking at for in terms of the founder? Prateek Joshi (25:22.382) Yeah, yeah, it's very different now that you do it full time and you're actually managing capital raised from LP. So it's very different from, I know a cool founder, let me make the intro. So now I spend a lot of time just understanding one, where are all the good sources of founders? And where do good founders hang out? I, do I, is there enough coverage in my worldview to actually know where all the good founders hang out and do they, is there a reason for them to talk to me? So sources of founders is something I spend a lot of time on. Another thing I spend a lot of time on is these market subsectors or these themes and subsectors where, okay, what has become interesting? And there's something that my friends, my peers, my investor friends, are yet to realize or they do realize it, but they don't want to do the homework. Either is fine, as long as it's something that is interesting. I keep an eye on all these subsectors. And also I do a lot of research on customer sentiment, for example, meaning like, think robotic arms are cool. Let's say that, because I built robots in the past as a hobby. And now it's a very interesting time for robotics with LLMs. So I think it's interesting, but it's just a hunch. So what do I do to validate that? I talk to people, I talk to people who buy a robotic arm, like big, big logistics companies who operate a bunch of robots. had to buy from vendors, they had to integrate. So I spent a lot of time on this market research. And then also another area is the diligence engine, meaning given all the data, I have all this data, how do I process that to make a decision? Can I just separate out my emotion from cold hard facts? And can I make that process repeatable? Can I make it robust? So basically the diligence engine is that. And also a big part of being now VCs is selling, selling the idea that Moxie is the best for you. Selling the idea that you should come to me, right? And also helping Prateek Joshi (27:47.366) portfolio founders being like a sounding board because going from C to A is where I spent most of my founder time. So I kind of, have a very instinctive understanding of that part of the journey, more so than pre -C or series A because I've lived that life the longest. So Moxie is a seed stage fund, which aligns very nicely with all this tribal knowledge I've gathered over the years. And Yeah, that's what I ended up doing. So sourcing, diligence, winning, helping portfolio founders, doing sector and subsector research to know what's happening and what will become cool in 12 months, 18 months. Yeah, that's about Jason Kirby (28:31.126) Yeah, the what will be cool and not what already is cool. Cause if it's already cool now, you kind of missed the boat. I feel, I had a, a post that picked up a little bit of momentum the other day where I was talking about VCs want to be. Ironically, they, they, say what you say, but ultimately they want to chase the train that's already left the station. when they're, you know, that's already got all the momentum. It's got all the traction. Prateek Joshi (28:37.296) Exactly. Jason Kirby (28:58.472) And there's tons of trains waiting at the station, but had no one on them. It's like, all these companies are like, Hey, I'm here to take you somewhere. I'm here to take you on this amazing ride. then now they're running after and they're Patagonia vest chasing the, the train that's already left the station. with Moxie and kind of the deals that you're looking at, you're looking at C deals. Like you kind of talk about your diligence process, but ultimately like, you know, for a plug for Moxie on Prateek Joshi (29:02.553) Right? Jason Kirby (29:27.938) I guess with a lot of founders here. What type of deals are you looking at? Stage Sector, Check Size, that kind of Prateek Joshi (29:36.73) Yeah, Moxie, we had a seed stage fund and we invest in seed rounds. For example, when the company's raising two, three, four million, we come in and we'll write the largest check in those rounds. And in terms of sectors, we are generalists, but we do have our preferences like vertical AI, robotics, climate, healthcare, AI plus bio. So some of these areas where we are more active than others. again, at the end of the day, we invest in companies building solutions to hard problems and solutions because we come from software. have a network is mostly in software, but we have invested in robotics. So there's no hard rules, but basically we want to, rather we have invested in companies solving hard problems because of our backgrounds, are completely okay taking on the risk of technology and engineering. We want them to be doing hard things because many people stay away from things like deep tech, for example. And we're actively leaning into it because it's not as difficult for us to understand because that's what we've done for a couple of decades. So I think it's one of those things where you identify things that are easy to you. but difficult to others so that you can just do it for longer and gain the benefit. So, yeah. Jason Kirby (31:08.844) No, I think that's a wise strategy to approach and often, you the fact that you're capable of doing the homework, I think is one of most important things in terms of doing deep tech and trying to discover these. And is it mostly software or do you guys do hardware at all? Prateek Joshi (31:28.1) We mostly do software and when we do hardware, we do it when hardware is not like the core source of revenue. Meaning you can use hardware to deploy, but you're commercializing software or data infrastructure. That's fine. But if you're generating revenue by selling units one by one, that's something we don't do. But if you're deploying autonomous robots on the farms, you're almost giving it away at price and you're really monetizing the data that comes out of it or you're monetizing the software package that you sell to customers on top of that. Now that is something we get excited by. So yeah, we don't have like a hard rule against hardware. We have a little bit of bias against the unit by unit selling of Jason Kirby (32:17.718) Yeah, no, I think that's fair. And a lot of VCs are the way just because it's less predictable and, you know, hardware is usually not a generally exciting business model. There's usually, you want some kind of recurring aspect to it. so I have to acknowledge that you're a, an ML expert. You're, you know, technically very qualified in the new age of AI and everything going on. When founders come to you and they ask you. kind of for advice or seeking knowledge. What's kind of the questions you often get? What are those answers that you provide, being that you're a thought leader and an expert in the space? Prateek Joshi (32:58.862) Yeah, Many things actually start with many conversations, start with like making their AI offering more complex. And my first, my very first advice is just go in the opposite direction. If you can do this without using AI, you should do it like a hundred percent. And most founders are usually like by that because they're like, my God, you're taking the thing away from me. Like, what am I going to do now? Like, what am I going to tell people? That's your problem if I identify the problem. if AI is like nitro boost to an engine that's already working, it is not the engine. So if you are hoping that you will be able to do stuff because you call it AI powered, then there's a much, much bigger problem that you have to solve. that's my first, usually that's the first place I start is, whatever it is you're doing, if I take out AI from it, will it still be a company? Will it still be a product? And that's a good kind of starting point for first principles thinking around the product. So that's the product part. In terms of raising, AI founders come to me all the time, friends, colleagues who have an AI powered something, an application, infrastructure, some product, and they want to raise capital. And many, many, many first time early stage founders, they don't really understand the process of raising capital. And that's okay. I was the same way. I just had no idea. I feel like I felt like I was, I was part of a sport in which I had just no ideas of the rules. I kept getting yellow cards and red cards. I just didn't know what the hell was happening. Why am I getting penalized? The I recommend is just to understand, have you spent time with the people you are selling to? You are selling equity to investors. Have you spent time with them? Do you even know how equity gets bought? And many founders don't bother doing that. They're like, it's just a small part of life. I just want to get done with it. my point, I tell them, take a second. Prateek Joshi (35:20.922) there a lot of intellectual horsepower, right? So let's take a second to just understand the people on the other side of this transaction and understand how equity gets bought and sold, right? And once they understand that supply and demand play a huge role, right? And the reason I'm telling you this is many founders that do like sequential fundraising, I'm gonna talk to first investor, if it doesn't work out, I'll go to the next one and then one after that. And unfortunately, the price of the company of equity is very much driven by supply and demand, which means as a founder, you always have to generate demand for your shares. And that can only happen when more than one investor is interested. That's the only way to enforce peace and stability in your fundraising process. So there are actually many, many nuggets that come up, but I'll stop there because those are usually two big things. One is the product path, the AI product, pixie dust product path. and the fundraising process are the two big things that come Jason Kirby (36:25.12) Yeah, I think that's, those are valid advice points and just like, I appreciate what you said about kind of AI should be the nitro boost to an already working engine. I feel that just everyone has to sprinkle AI on everything because well, AI is what's getting the funding. It's like, that's not necessarily true. Like, you know, there's different layers and you kind of, brought up some good analogies in the beginning of our call in terms of like data being the fuel ML being the vehicle and AI being like the destination. I love that quote. We'll probably try to snip that. But I think when it comes to companies out there in the market, looking at trying to be that differentiator, the problem is, it's no longer a differentiator. So many companies are saying they're adding AI and at the barriers of entry, you're getting cheaper, faster, easier. What else can you differentiate on? When you have those conversations with companies, when they're trying to figure that out, what's typically your advice for founders that are trying to find or have a true differentiation point? What does that typically look like from your perspective? Prateek Joshi (37:38.438) Yeah, in the early days, it's very hard to be truly differentiated because whatever it is you're thinking or working on or the idea you have, just rest assured, been tried 10 ,000 times in the past. Just know your history and you'll see that it's not novel. So, so if that's the case, then how can a startup be any different? How can they talk to a customer? who's inundated with these things. So in those cases, my advice usually is like when you can't differentiate, I would say like go vertical, meaning whatever you are competing against, usually a bunch of unknown companies, you don't have to worry about those. You're usually competing with like big couple of big names. And even within that is one truly big name that everyone thinks, this is like Salesforce, or this is like, I don't know, Snowflake, how are you different? So in that case, I tell founders, instead of running away from it and listing like a table of features and like with the check marks and all the worst like business class 101, the other quarter and how you're different, I'll just say we're exactly like Snowflake, but we're Snowflake for this extremely small group of customers who prefer us, like 10x more preference to us than them because Snowflake is too general. They address a wide variety of customers, but we have... narrowed down and made our workflows and software and everything so specific to this group that they absolutely love us. And that is your beachhead. That's your entry point. That's how you get started. You need those early super fans for you to build a much, much bigger empire. that's some shape and form that ends up being the case. So that's my advice to most founders. And also, I have a, over the years, I've done a bunch of these little nuggets, which I'm happy to share about four or five of them. Maybe we'll go through them quickly. One is follow your skill, not passion, because I'm passionate about eating donuts, but it's not useful. So I need to know what my skill is, and I need to follow that. And next is the power of compounding, meaning people just give Jason Kirby (39:50.967) Yeah. Prateek Joshi (40:00.464) too easily, too quickly. You got to stay in it long enough for the power of compounding to kick in. So that's the other one. learn how to tell a good story. Obviously, you mentioned at the beginning, tech stories, people love stories. Even as adults, we love stories. So learn how to be good at it. learn to do cold outbound. The best skill I've picked up pre and post being a founder is outbound because as an engineer, Outbound was like this thing, no way, I'm cold emailing because it's awful, sounds awful, you'll get yelled at, no way. But now it's like this incredible weapon that you can wield. So it's amazing. one more, like last thing, speed wins, always. Speed wins in any situation, no matter where you are, if you can't do anything, just be fast, usually speed wins. So these are some of the things that over time have served as like good points to keep in Jason Kirby (41:04.461) Those are some phenomenal points and I agree with pretty much, I do agree with all five of them when it comes to building a company. And I think speed is something that a lot of founders tend to look past when they're not going as fast as they hope they are. And they try to be like, well, don't look at that. at this. But I think you kind of nail it pretty well. And Pratik, it's been great having you on the show. The advice you've shared has been phenomenal. Obviously you've, you an author, you have your own podcast, you're currently a VC. What's the best way for people to learn more about you or potentially reach out to Prateek Joshi (41:43.184) Yeah, you can learn more about me by visiting pratikj .com. You'll find all the information about me, my writings, my podcast, my books, my everything. And if you want to reach out to me, feel free. I'm at pratik at moxie .vc. If you're a founder raising a seed around or a founder just wants some help or support or just wants a sounding board, I'm happy to chat. And when you reach out, just mention that you found me through this podcast Jason Kirby (42:13.643) Cold email will work in this case. Prateek Joshi (42:15.938) It will work. I read every single one of them. Just know Jason Kirby (42:21.13) All right. So make it interesting enough for you to respond to the very least. But Prateek, it's been amazing having you. It's rare that we get an ML expert on the show. I appreciate the advice, especially business experience and technical experience. You're of like the unicorn in the world. So appreciate you joining us, sharing your stories, sharing your insights, and look forward to getting this out to our audience as soon as we can. Prateek Joshi (42:47.59) Perfect, it was amazing. Thanks Jason. Jason Kirby (42:50.29) Awesome. All right.