The Surprising Future of AI with Fathom's Founder - Richard White

Welcome to the Proofing Podcast, where it doesn't matter what you think, only what you can prove. Richard proved it. In a time where everyone's trying to be successful in AI and they're rushing around, he did it five years ago. He's a CEO and founder of Fathom. He's also a really great guy until he starts telling you the unforgiving truth of what's actually going to happen with AI in the next 24 months. It's terrifying. I know it. I hope you enjoy it. The show starts now. Hey everybody, welcome back. I am excited to have you on the show Richard. Thank you so much for joining us. Anything extra out of me. From the four of my people who don't know who you are, did you explain what you've done, what you're success at the day? Sure. I'm the founder's CEO over here at Fathom AI. We are the number one AI note taker on G2 and HubSpot. No one likes taking notes on their meetings. We have basically an AI that will join your meeting, record it, transcribe it, summarize it, write the notes, write the actions, fill in your CRM, you know, slack it to you, email it to you, you name it so that you can just focus on your conversations and not do a bunch of kind of data entry work. So I think most people are familiar with your product. I think the stuff we're going to talk about now is stuff that people aren't familiar with about the reality of AI. A lot of people think AI means artificial intelligence. It also means always incorrect. There's also a side of this that you believe about what it means for you as well and some of the harsh realities of what AI does. Can you kind of share what some of those harsh realities are? Yeah, I mean, I think one of the things, you know, I've been doing software for 20 years and AI is completely upended how we think about building software. Made it much more of an R&D process now, whereas before it was more of a manufacturing process. It's also made the failure rate much higher, right? Like, you know, we, it takes a long time to sometimes ship an AI feature because it will fail three times before you get something to work. And so that exists for both when we're building features for our product. It also exists like when we're trying to buy AI products to basically, you know, you know, move our business for it. We actually have a goal of getting to 100 million revenue while staying below 150 employees. And so we have this big emphasis on efficiency and automation. And it's finishing because we had this, you know, I just gave this talk where I expected to talk about how, you know, we've transformed everything with AI and we actually have like a 60% failure rate on AI initiative. So I think there's a lot of really interesting gotchas when you're trying to build or deploy AI solutions. So what you're trying to tell me is that AI isn't the holy grail. All of a sudden, I'm not going to start floating and curing cancer because I was bored on the toilet one day. That's not how it's exactly where you're at. You've ruined it all for us forever. You're so sorry. So as we go into these, you're talking about favorite, what do you mean by failures? I mean, 60% that's, I mean, I wouldn't get on a plane that had a 60% failure. I mean, I would get married because that's a 62% failure ratio. But okay, we'll get on a plane that had a 62% failure. What do you mean that a 62% failure ratio in AI? I mean, so actually, there's these MIT studies came out and said that the average company right now is actually a 95% failure rate on like AI initiatives. What I mean for us is basically like it produced the outcome we wanted. And I think that's actually the hardest part is like in AI land, it's easy to get it to produce something. It's easy to get the answer to that something. Right. Our part is getting it to get it to the right thing. And what is the right thing? So for example, in our business, like, you know, I could, you could build an AI that gives you an accurate summary of a meeting that six pages long, but accurate may not be enough. Like that's two for both. I don't want the six page. You know, it was a 10 minute meeting. I don't want six pages. So there's like this whole new nuance of like quality that I think is hard for us to judge. We're not used to judging it. Right. We're used to software is binary. Your workster doesn't. I clicked the button. The thing moves on the screen. Right. And now we're in this world where I click the button. It spits out some words. I'm like, are those the right words or not? Right. It makes a judgment call. Is that the right judgment call or not? And so I think one of the things that's really changing everything is we have to rethink how we evaluate tools because we have to actually get in there. And it's almost like evaluating a higher. Right. It's more like a fire because you're basically buying thinking not features now. And so it's kind of upended how we think about purchasing products. Right. So I can't even get chat GPT not to put dashes in the damn responses that it gives me, which I can't tell you how many cursing that I've done at that thing. You're talking something significant higher. How do we get it to produce content that we actually want or go from that 10 page, you know, dissertation that's so verbose into what we want. How do we do that on at the whole level for the your everyday consumer thing? And then also, you know, as the CEO is a very successful company because every single media I'm in, your damn software is there before anyone else joins. Thanks for that. I'm a little bit more angry about you with that. So how do we do that in both the personal level and the professional level? Yeah. I mean, it's actually that same study said that like the success rate for things like chat GPT is like actually 40%, which is still not great, but way higher than 5%. Right. And I actually think, I think it's easier for individuals to use because individuals are basically taking ownership of that output. Right. Like it's like, oh, it's right. It's no for me. And yeah, I hate that always puts in dashes in there too, but I can always remove them. Where it becomes problematic is when we're using these things at scale. And no one's basically been properly equipped to QA the thing. Right. You know, we have a whole team at fact that all they do all day is play what I call kind of like a, you know, AI version of Jenga, where we think about this is like all day we are experimenting with like, you know, basically models in use cases, right. And does this model good at this use case can this model find action? I'm from a transcript and I call it Jenga because like we push on the block and it, you know, it gives any resistance. You give up. You find another block that moves smoothly, right? Because there's like, right, weird kind of like, probably you've got now we got so many models with differing kind of performance parameters, cost parameters. And so we want to do. So it's really a big problem. You know, let's need a full time team if you're building suffered either you're building it or evaluating it to like, you know, evaluate multiple vendors in parallel and try, okay, we're going to hire three vendors. We're going to put each of them on a 90 day pilot, which by the way, we make every vendor give us a 90 pilot for AI. And I'm going to have a whole team that QAson. And when we don't do that, it almost never works. So when new when new GPs or new models come out, there are so many times where I personally, I've spent so much time training my old model and trying to teach it and say, Hey, do this through that. And I have very specific calls to do that. When a new one comes out, do you guys over-advast them have the same puckery motion that we have in our side? Like, Oh, God, everything's about to blow up again. Is that something you guys are facing as well? Yeah, on two dimensions. Well, I mean, one, we get excited because usually the new models unlock something for us, right? For example, GPT-5 for the lackluster kind of reaction it got from the market, did actually solve a significant problem for us, whose whose initial rates are way down. And that actually ends up a whole new class of problems that we were trying to solve before but couldn't. But it calls also other problems in that none of these models are for compatible, right? You get something working on GPT-4. It's not necessarily going to work the same with GPT-5. And even more problematically, I think this is something that everyone in the industry started to realize, the EOL cycles on these LLMs is now measured in months. So Anthropic puts out Sonnet-3-5. They put out six months later Sonnet-3-7. Sonnet-3-7 is more powerful. But now there's a limited number of GPU compute in the world, right? And so they're shifting all of their compute to this new model. So now you end up on what we call the LLM treadmill where if you don't upgrade your models, all of a sudden you find out you're getting all these errors because there's no compute to service them. And so now you're spending as much time upgrading your models as you are basically building new stuff from scratch. So the maintenance load on these tools and processes is way higher than anything you've ever seen in software LLM. It's one of those things and I'm going to date myself here, but the original Warcraft 2 because I've that old. Before you, okay, so you see by this model, you played it. Before I would go and I would attack the orcs or I would attack them nights or whatever it was, I would save my my military formation. I would get it. This doesn't go well. I'm going to go attack if they all die. I can just go back again. I wish that existed inside chat GPT where or any GPT that we're going were like, okay, I should have probably tried to do this quick giving me dashes or I want you to work this way. And then for some reason AI becomes always incorrect and it just goes off on a tangent on excuse or can you just go back 30 seconds. That would be nice. And then I'd sound some what you're saying is, hey, I did this great game. Can I pick it up and drop it in over here as well? And it seems like both of those things are absent in the market even at the highest levels, which is where you are. Yeah, that's right. I mean, I think a lot of advice I give to companies like if you can try to solve a problem with building something in house, but know that in house solution has like six to nine months of shelf life and know you're going to throw it away and probably buy a vendor at some point. But by building a house, you have a better sense of like, cool, we at least know we got it to do one small critical thing to do. A lot of vendors throw a lot of things at you. We've 10 different features and two out of 10 of them work sort of thing. But yeah, this is it's kind of like this whole new, again, this whole new paradigm. It's very much an R&D lab. It's very much a not a simple line. It's not as predictable as what we had before this in SAS. I wish this was something new in a sense of tech because I remember because I'm old enough to remember when we did the dot com boom and everything was going out with the internet right. Oh, there's going to be amazing and then you know, pest dot com is going to be amazing and this is going to be amazing. I was going to do to blew up all the time. So not just on a personal level, but professional level companies you thought would be fortune 500 companies are going to be there forever would be gone two through weeks after. Are you seeing that with established companies are sitting there going, oh shit, we've got, you know, there's a, the lives of the tunnel is not a light. It's a train. We got to adjust because what work today just one evening is this and how short is that time for I mean, I think the exciting thing is an entrepreneur right now is that a lot of the big companies are really struggling to release good AI features because it breaks their paradigm of how do you software right there. Use again, this template line where it's like how do we build software? We say we want to build this feature. We spec it out. We build it for three months and then oh, you know, we cooked the button and the moves, you know, 10 pixels to the left were done, right. And it requires a whole new way of doing QA that most of these companies are good at doing, which is why I think if you look at most of the big new AI features from all of these companies, they're really mediocre, right? Because they just don't know, they don't have the muscle in the company, which is what is quality, right? They don't know how to judge basically like subjective quality and they're still looking at from there kind of like objective like did it do the thing? Did spit out words? Yes, great. Past QA ship it sort of thing. So I actually think this is a challenge you're buying software because a lot of them the bigger incumbents actually have inferior products to the new startups. New startups have their own problems, right? Of like, you know, instability, what not. But if you're an entrepreneur, I actually think it's a fantastic time because it's like the incumbents are completely out of their depth and how to build software in this new era. And so I think I'm exciting actually as much as it's also terrifying. Yeah, I think the best example I've heard of this is imagine you're on a train that's one as fast as possible and you're on one car of the train and you're fixing as much as you can, but all the sudden it's going to unlock and that car is going to be gone. So you better jump or good luck, I wish you nothing but the best because that's just the reality that we're going to be in. So as someone who's kind of tipped at the spirit who has been to come very successful with what you're doing and has created a company that as much as I do hate your things, you know, all the means is something that everyone uses. Where do you see AI? Because everyone's like, oh my god, it's the greatest thing since fire and there's other people who are like, oh my god, it is fire. It's going to burn down my house. There seems to be people who are very polar opposite you, you're completely madly in love with AI or oh my god, it's the devil incarnated and they have this paradigm shift. Where do you see it going? Since you are, again, you're in there, you're with the CEOs, you know what's going on there than even someone the regular person would be, how does this look in five years? Yeah, I mean, what the devil says, this is to me the greatest technological shift of my lifetime. Bigger than bigger than mobile, bigger than social. You know, I don't see them say bigger than they're itself, right? There is real right there, right? Like for all the failure rates and stuff like that, they're also the denominators huge, right? Everyone's trying to stuff because this is the closest thing I've seen to magic. One of the challenges is that it's like, yeah, what is, you know, like board meetings and we're kind of talking about like what, you know, what's our five year plan, what's our 10 year plan? I don't know if you get to AGI in five years. Does anything really matter? Can you really plan on AGI type things? Smarter people than I, I think the real question is kind of the question right now in the market is, you know, my kind of core framework, the same folks that I kind of leaned on five years ago before Gen AI got good to make me feel confident building a business betting on Gen AI, getting really good. It's kind of like we started this company in 2020, 2021 we launched, we put AI in the name of the product and all my investors are like, what are you doing? Everyone hates AI. It's easy to forget. It was only four years where AI was being marketed in 2015, 2016, 2017 and it was terrible, right? It was not an eye. It was, you know, it was basically fraudulent kind of stuff. But now we're at this point where everyone's like, oh my god, AGI is going to happen in two years. And, you know, there's some people still believe that we're going to keep accelerating. I think that group of people that I'm kind of surrounded with things about 50-50 between like, we're going to reach a plateau of what you can do with the current tech. And we're going to find kind of more of a lost dial the next step up. It's clear that we're getting diminishing turns from the current generation of trans-cantabase AI like GPG-5. I think everyone comes to these all the latest models are now more optimized for efficiency. They're not like, wild, we smarter than the previous model, but they're cheaper to run, which is important. I'm just running. Yeah, for their margins and all that sort of stuff. I've kind of taken approach of what we have to kind of assume that things are going to kind of slow down because we assume they're going to continue accelerating. It's almost impossible playing for anyways. And we're kind of, again, I think GPG-5 was one of those was a good data point of like, okay, like seems they were plotting towards a plateau and we're waiting for whatever the next thing is after transform the models alone. But it is the most volatile market I can ever imagine. We've been on by this company's been our objectively a rocket ship by the last 10-year standards. And we're now just doing pretty good by modern standards where you see companies go from zero to a hundred million, a billion, a revenue in two years. And then go back down to zero two years later. We'll get the geographers and stuff like that. So is insanely volatile market full of tons of opportunity, but how long will those opportunities are I think it's to be seen? Yeah, I think to your point of what does this mean to the human race? I will give a little bit of pushback. I don't think it's better than internet. I don't think it's better than industrial revolution. I think it's better than the only thing better than this is fire. That's as far as human race is concerned. This is this is fine as far as what I can do. Now, fire was good and bad. It can burn down your entire village. Yes, but it also makes good food. We can do these things as far as what I'm concerned. What I've seen with it, AI is as good as fire. Now, what that means going forward. Good luck. I wish you nothing but the best because it's going to be pretty interesting. You mentioned there's companies that go from zero to a billion dollar valuation and then two weeks later gone. Do you think we're going to see in our lifetime the first hundred million dollar company run with us a single employee? Do you think that's going to happen? Yeah, I mean, I think Sam Altman talks about the first billion dollar company with a single person. Right. I think that's right. I way possible. Then you can extrapolate all the concerns you have about like societal people and wealth inequality and from that pretty easily. But yeah, no, I think that's perfectly reasonable to expect. Yeah, I think when it and this is something that people don't understand, this is no longer a luxury. We don't get to sit back and say, hey, I wonder if this is going to happen. I wonder if this is going to affect me. This is going to create wealth distribution issues on the equivalent to basically India. When you look at how people are distributed, especially here in the United States, you're going to see that. So if those of your playing at home who might not understand everything that Richard's talking about and what he's doing, you do not have a luxury to sit on the sideline. So either you're going to be panhandling or you're going to embrace AI because this is just this is what it is. This is electricity. So if someone's walking into that and they're like, oh my god, this is terrifying. You know, you're telling me that hey, I need to embrace it. But then you're telling me the company's going to disappear in five months. When you're an entrepreneur, you're like, oh god, I have to go into this. I know I have to go into this, but I could get punched in the face or most likely will. So how do you advise entrepreneurs? How do you advise business owners and hates? Do you just improve in tactics that work? Let's do these. Just do these for now. Make sure that if you do get knocked on your butt, you can get back up somewhat gently and go for there. What are the things you would advise? But I mean, honestly, I think it's never there's never been a better time to start something that's really narrowly focused. Right? You hear a lot about the big, you know, the big platforms that are, you know, again, going from zero, like a jazz program, going to zero to 100 million right back down. But the real beauty of this stuff is like it can get you can really tailor the stuff to specific use cases, specific problems. And you can build faster and cheaper and better than you ever have before. Right? It's completely up here. You can, you don't have to have a CS to do. I have a team of six engineers anymore to build something useful. You can just be a pretty good, you know, hobbyist, prompt engineer plus some magic patterns and some prototyping tools. And you can build something of value, right? And so, you know, I remember 10, 15 years ago, I was kind of doing like the, you know, the, was it the lean startup stuff? They're like, oh, you know, they're selling stuff before they really even built it. And, you know, that got taken to extreme, but now you would really can really narrow down and find a very specific niche. And you could build a really good like, and I know this is kind of a majority of the lawn markets, but like lifestyle business out of like, great. I've got the best new software that solves this one-burning problem for car washes, right? Like, yes. And I actually think that's where a lot of the gold is. I actually think a lot of the gold is at the application layer. A lot of the investment in noise and all the stuff is all kind of at the like foundational layer. It's all about who's building the big infrastructure stuff. But that's a, that's a, you know, billionaires game. You need a lot of money upfront to do that. I think there's a lot of money we made at the application layer sitting on top of these tools. And if you can get good at bringing them. And that's where I think, I think that person that's going to be the, you know, the single person company doing a hundred million revenue, I don't think they're going to be a foundational model. I don't think they're going to be something like father. I think they're going to be something that sits above something like that, right, or above these foundation models, right? Just finds a really good niche that just happens to catch a wildfire. So I think that's for the entrepreneurs. I think for the employees, there needs to be this conversation of what's happening because you're seeing in their orgs. They're seeing people who are in tire divisions, they're going to eradicate it. People with masters degrees from high-medium schools or, you know, trying to get jobs at McDonald's right now. And they're terrified. And I rightfully think they should be this welcoming this new world. When we were meets, when I was a being an entrepreneur, it's not sexy. They did not like that idea. It'd be in the comic books, not sexy, being a dork, not sexy. And all of a sudden, now like, it's our time. It's our time as common, since they're entrepreneurs, the employees that I know are terrified. They are fundamentally like, hey, and they go back to their old model, which is, I'm going to agree. I'm like, that's not going to help you. That's over. Those times are gone. So what do you say to those, you know, mid-level managers, kind of just, you know, senior directors, VPs? What do you say to those guys who have said, like, I built and I, you know, busted my butt to fit into this model of this process of this American dream. And as George Carlin said, really, well, he goes, it's called the American dream, because you have to be asleep to believe it. If you no longer believe this model, and you are no longer built for this, and the thing you were built for does not exist anymore. How do you adapt? Yeah, I mean, that is the question, like, that will be the question of the next five, 10 years, right? I remember, you know, I was a big proponent of like, I was telling everyone, I listed about UBI 10 years ago, and I was worried about truck drivers, but in fact, that was like truck drivers. Number one profession in like 30 or 40 states, right? And it's going to, you know, it's going to go away soon. And it's kind of funny. It's really hard to predict these things. I think everyone would be sure that that was the first thing, the first kind of like industry get through. And usually here we have 2025, and actually it's no, it's artists, it's copywriters, it's pre-sune, going to be warriors, middle-level management. It's all knowledge work. Fair costs. Yeah. Yeah, exactly. And so, so, you know, what would I say, you know, honestly, it's like, there are no, I would tell you like, your fear is well-founded, first of all, right? And unfortunately, like, I'd love to sit here and tell you that you've had nothing to worry about. And I think you do, right? You know, I think what you're seeing, when you look at what's happening at, you know, college enrollment is down. Trade school enrollment is up. And I think like, you know, people that are kind of solving this first principles, the folks come in at a high school or look at that saying, gosh, you know, there have been a better time to be in the trades. Now, am I going to tell some VP to like, hey, you know, you should go back to New College and become a, you know, a plumber? You know, I think that's a tough sell too. I think there's like a middle ground where if you really become a student of this stuff, I still think there's a lot of opportunities in the next couple of years, again, at the application layer where you could be the person that helps companies get from a 5% success rate that we're seeing through a 20% success rate. And there will be a lot of opportunities there. I think it really depends a lot where you are in your career. I mean, I, you know, I've been building software for 20 years. And I've always thought that like, you know, I always fall back. I know how to organize people to build great software. I'm not sure that would even be a skill set in five. No, right? That's good. You know, I very much play like if I don't have kind of a exit or retirement plan over the next five, 10 years, we need to be thinking about what we can, what value can provide beyond that. But I do think very tangibly, I think trades will be coming back in a big way. I think, you know, there's a lot of opportunities for people to learn how to become experts of you can be an expert replacing your own job, but they high that gives you a job over the next couple of years. So, you know, we talked about entrepreneurs. We've talked about employees. We talked about where we think this is going and how this is the new fire. What are some of the conversations that none of us are having? Let me, let me, for very excess. None of us other than you are having in these boardrooms with these people who are, you know, very much a tip of the spear. What are the things that you guys haven't made as public yet? If you can, this is, hey, this is what we're talking about. And these are the things that keep up with us at night because we know what keeps the entrepreneurs up at night. We know what keeps the employees up at night. Here are us as, you know, founders. This is what keeps us up at night as well. I mean, I think, you know, the, I think the boardroom conversations are more about like pace of AI change and kind of like, you know, how quickly will, it used to be build software company. And usually, I had at least 10 years before someone really disrupted you. And then, you know, in the start, now it's like five years, pretty soon, be two years. We're like, there's so much technological change. It's just unduz. You know, if you, valuations for SaaS businesses, you look at them today versus five years ago. So I think there's a, the boardroom with you is a lot of conversation with that. Again, about like, AI and like, what would that mean? Could that just, you know, render a lot of businesses irrelevant? I think the conversation we should be having is the one we're kind of tip-toeing around, which is like, how do we, as a society, handle this? There's a really good short book called Manna, M-A-N-N-A, by the Sky Martial Brain. Do you remember how stuff works?com? Awesome website. The guy's actually from my hometown around North Carolina. He wrote this like 25 page book. And it was kind of a tale to cities. One city actually set in the US. It was like dystopian AI future where like the robots are in the ears of the humans telling them exactly what, you know, walk 10 steps this way, turn over the burger, that sort of thing. And another city where it's like, oh, no, a lot of the gains from AI are more shared in society. It's like, it's a little hyperbolic, right? But I think a really interesting thought experiment of like, this is coming. And which, you know, I don't know that we'll get as dystopian as one example, or as utopian as the other. But I don't think we're, I think we're, everyone's busy fighting trends, put the genie back in the bottle. The genie's not going back in the bottle. We need to talk about what's, where do we want to like put gargres and push the genie in one way or another? Right. Like, and so, I think the other thing people are talking about is also kinically like AI regulation. The other thing is like, you know, I think a lot of folks in tech land voted for Trump. And one of the reason they voted for Trump is because he wouldn't regulate AI. And a lot of folks see that the basically there's an arms race between us and China around AI. And if there's this belief right or wrong that if China gets to AI first, if you believe in Western style democracy, bad things happen, right? And so I think that's another, there's like, you know, kind of so many of our levels to this upheaval, but those are the three I would think about. So where do you think things are going? Because people do have this dystopian fear that all of a sudden it's going to be terminator, right? You're going to have the day it cuts over and then the world else are going to take us over and turn us into cottage cheese. Where do you think and what's more realistic for that? I think all the paths are still open. You know, I don't, you know, I think it's not the answer I wanted to hear, but okay, I just beat on myself a little bit. I think we would be foolish. I think there's a lot of folks in the island that are concerned about AI safety. Like a lot of the, a lot of the kind of open revolt that they had at Open AI a year ago was about the fear that like this thing was founded on the premise of AI safety and it seems to gotten off that mission sort of thing. So a lot of people way smarter than me seem to be very concerned with that. And so I think, you know, don't want to be alarmist, but I think we should all be like alive to the danger. This feels like a, the critical moment in like a, in human civilization and everyone needs to educate themselves a little bit and, you know, do what they can't and make sure no G ourselves in the right direction. So for all of you that have just caught the podcast, we've decided that we're all going to die. We're all going to be out of jobs and it's completely over and it's a horrible time to be like, okay, let's try to give people a little bit more hope about what what's done. So there's this lot of conversation about what AI can do and what AI's done and not only just the basic stuff with business, but what's been done medically. Like hey, we've made ex-marriage and discoveries and we've pushed the envelope with that and hey, how we've looked at a problem that couldn't have been solved by humans for a hundred years. It's in 27 seconds. So there are some amazing things with AI. Can you kind of share some of your favorite ones that, you know, you've seen that of kind of person? I'm like, oh my god, I can't believe it just did that or it figured out that. I mean, I think you just touched on the big one, just like a lot of the stuff you're seeing happening in healthcare, right? We're like weak things that used to be really expensive, right? Like analyzing scans, early detection, like our healthcare system, my father was in Mercy Medicine for 30 years. He was first one tell you we are really reactionary in healthcare. For a number of reasons, but first and foremost, it's like it's very bit expensive to be basically proactive in healthcare because you know, someone's got to analyze the scans, they get a look at these blood markers, they got to do all these things. Both on though, I can kind of like the preventative maintenance preventive medicine stuff as well as research. And this is going to try to done the cost of all that stuff dramatically. The point where you know, you don't have to be rich to get kind of life extending care well ahead of some acute medical crisis. I think there's a lot of, I think that's going to be the thing we're going to look back at and be like, wow, we're going to cure, you know, hopefully cure or greatly reduce the harm on a lot of diseases in a very short period of time. But it's going to be kind of the wild west in the meantime because also our medical regulations that have really caught up with that, right? We don't have one on a handle. But I think that's probably one area you can look at and point to and be like, excuse me, I don't want to get done there. I think you know, for all the destruction that we're going to see with self-driving cars, that's also going to place where you're going to point to, right? Like, you know, the number one cause of death of people, the number one use of like urban land, like you think about housing affordability, think about what happened when you don't have to dedicate, you know, 40% of your city to parking. Think about it and, you know, people aren't getting car accidents left right in the center. So I think there's going to be, you know, on the other side of this crucible, there are a lot of things that we look forward to. In the same way, you look at the same thing like the industrial revolution and stuff like that. There were a lot of painful things in that trend and a lot of terrible things happened. Humanity was better for that transition in the end, right? But it will be- I don't think we have to go as far back as the industrial revolution, either even with the IT boom. When technology kicked in, people are like, oh my god, these are going to wipe out jobs. Yeah, they did. When tech rolled out, when we had the dot com boom and everything took off, they didn't- it wiped out walls of jobs. But the job that you at right now did not exist before that. The jobs that I did that- the careers I had. So yes, it will wipe out a ton of shit. We'll also create a ton. So I think there is a- and I think to your medical point, now there's a different- our DNA and DNA, there's different- with that we have to measure those things. Some things don't change because even if you die of cancer, your DNA, that's your DNA. But the other stuff we can analyze and say, hey, you know what? We say that everyone should take these medicines. However, say stuff, your stuff, your individualized goodies, you should be taking this. I was sitting with the CEO and the company said, does that? We broke down. He's like, yes, let's run your blood work. And within a day, he's like, okay, this is what you need to stop eating right now. I was like, I'm sorry, what? He's like, yeah, I'm like, yeah, but that's supposed to be healthy. He's like, yeah, for everyone but you don't eat that. He regrettably did not say that I could have ice cream every day. So I'm still mad at him, but that's for this little- I was like, why can't I have ice cream every day? What the hell? So there is that. So we get- we understand, I think, you know, for every single level that we're at, be a deploy, entrepreneur, founder, there is this optimism and there's also a little bit of fear. So as we get through that, I think having the tools and the techniques right now, like what are the things, what are the tools that you're using other than obviously everyone needs to use a software? I get it. I think please stop using my meetings, you bastards. So everyone needs to use their software. What are some of the tools that you use every day and how to use them differently than everyone else? I mean, I think that I think everyone thinks that in Silicon Valley, we have a whole different set of tools that everyone else, we actually don't. I think there's, you know, we're all using, we're using chat, EPT, we're using things like magic patterns and other one I love. It's like an easy way to kind of just like, you can basically, it's an AI for generating prototypes. Like if you want to use your interface to something, so it would build a lot of prototype tools. You know, at the, at the, at the high end, I think that the secret is to actually build good products with AI, you're actually using multiple models, like any journey in Fathom, whether it's generating meeting summaries or finding action items or, you know, answering questions based on transcripts, there's a pipeline. We're using four different models from different providers in that pipeline. We use, you know, some of them Gemini, some R&D, we use some self-hosted ones. So at the high end, when you're actually building really sophisticated stuff and trying to build, you know, the highest quality AI right and take it to market, it's a whole different game. But individual, frankly, I don't think there's a lot of, I don't, there's actually, I think, there's so much work of mouth adoption of these tools, right? It's wild. Let's go from zero to 100 million so fast because they're so good that there aren't a lot of like secret tools that people are using. Right. It is a lot of plot, Jets, EPC, you know, make, you know, et cetera, et cetera. Yeah, I think the other thing that's really important is when you pick a new tool, you have to understand what you used to do, how you use to operate will also have to change. And the simplest example I can give this is we gave very specific PowerPoint presentations that looked in a very specific way at a very specific class level for that. That took a ton of time. We used a tool called, and again, I don't, dispenserships are affiliate cyber, it's used to do it, so the system that's, we used to tool called gammas. And my team got a hold of it. And they're like, I was like, okay, this looks completely different. They're like, yeah, but we created 300 slides in a week versus a month and a half. And I was like, okay, I guess our slides now look different. So having that adaptivity adaptability was vitally important. What are some of the ones that you use that you're like, okay, yes, I used to do it like this. I don't know more anymore. That's how it's, that was actually the example I was going to give, right? Which is like, yeah, we definitely know all my slides, so like this, gammas, creating slides out are they going to be exactly what I had before? No. No, you, that's the thing. It's like, you know, it's a huge and chat GP and Google search is exactly what I got out of search results. No, it's actually better, but you have to be flexible and we're like, rethink what do I actually need out of this tool? Yeah, gammas would be the same as that one I do, right? Like I love creating, I honestly, I spent, I do kind of waste more time now on their generating fun AI images from it. I do too. I'm glad you brought it out because I didn't want to be the first handful want to say that. I spend way too long in there just messing with the images, because I'm like, yeah, I'm a, I'm a, put an image in two words on the slide kind of guy and our branding, actually, we just rebranded and we put astronauts in it. It's others can put astronauts in it, because I had so much fun in every deck we've had for the last nine months. I've got astronauts fencing on the moon, astronauts fighting monsters, astronauts, you know, math or their helmets on like it's, I love it, right? Yeah. Yeah. Not to be fun is not to be discounted in the workplace. It's worth doing. It's so bad to be fun out there. You get that rock and roll it. I'm glad that you you stepped up and said that you too are adorac like me. So I appreciate that you you stepped into that world for me. So when people are sitting there and they're looking at this, one of the things that they're concerned with is, you know, if I go to Google and I type in, you know, what's the best food in my city, I'm going to get thousands of answers, which at GPT, I'm going to get one. Right. People are a little afraid of that. Like, okay, we're now getting it. So I don't have the option to think of my own. I'm now being told and I've now had the data so synthesized down to this one thing. Is that something you're concerned with as well? Because if I go to the library and there's one book on history, I know I miss you not a lot. Yeah, I mean, there's a big concern about like, you know, we've already had this kind of bifurcation and I feel like of what reality or truth is in America. Certain grief, right? What do you mean? We're not going to get into that. But well, but it is interesting. Like, well, for as much as you have to be getting things right, there's certain corner cases where it's really, really bad. Right. You know, I think my girlfriend the other day was like, Oh, looking up some place that would like, I think, you know, sow something for her. Right. Oh, I need to like it. And it gave her three answers and all of them were completely made up. Like, right. I mean, that one's at least easy to spot because you can use a verify like, oh, that's not a real place. But it is a little scary because we are outsourcing judgment. Not like why we like it is because we're outsourcing judgment. Right. Because who wants to go through a thousand restaurant recommendations, right? I just want to bring three only pick three. But yeah, we're outsourcing judgment to this AI. And that's what I think. Again, I'm grateful at least that there are reasonable competitors. And it does seem to be that there isn't as much in building foundational models as we've thought. Now there's a ton of moat in that like, you know, from a consumer brand perspective, chat GPT has 98% of the market. But I would encourage people to like get a second, you know, whether it's Gemini, whether it's CAHOD, like, you know, when you're skeptical, ask us get a second source, CROC, you name it, right? Like I think all the smart people generally are diversifying, you know, they I don't just I don't rely on one line to answer the question right for that very reason. I also think if you are trying to trap and one ecosystem by your own choice, because no one traps that thing at this point. And to your point with it, you know, the girlfriend asking for place for sewing, like, yeah, okay, Shmucco, now go check Yelp and compare your options. You're going together. So having that cross reference is important. It's one of the things that I've coded into mine, which is one of the things that I love about GPT so much. I'm like, okay, if you give me an answer like this, always do this after. And outside of dashes, it seems to resolve it. I think everyone I know will just celebrate so much when the name dashes and the emojis are no longer included. Stop it. No one writes like that. That doesn't sound like a human. What is wrong with you? So if anyone, by the way, on a side note who's listening to this, knows how to get rid of the dashes permanently, please send me a message. I will pay you for it. It drives me out of my mind. So what's that done? You open AI actually don't even know how to get rid of the end dashes. I think I read that they they're aware of this. They're like, we're not sure how this got in there. It feels like it's the AI's fingerprint sort of thing. I don't know. It really is. Yeah. So and it's funny because I will sit there. I will tell it over and over and over and over and over. And now I'm just like, I'm dashed. Because it's just like, I'm not, I can't teach it. So when people are like, oh, AI is so intelligent, it can learn and is, no, it can't even get rid of dashes right now. So just the brain here, sweetie. So for those of you who are sitting there and okay, we've been tools, we've got adaptive. When those are going through and we talk about what's next for you, not in five years, but what's the immediate next 90 days for again, you're kind of typical of the spirit with what you're doing over and over and over. What is the next 90 days for you having conversation with your staff? Because you have to lead differently because now we're in an AI age. How do you lead differently? How do you show up differently in that environment? How do you build 90 day plans? Because anything beyond that, you're, yeah, come on. We don't know. I mean, you know, we've been fortunate in some ways. This kind of has come back to our strength, even from the beginning, it's company. I've always been like, we only build 90 day plans. I actually think that I think in a lot of companies, planning is just like art of self deception and like false permission, right? Where it's like, you technology, even before AI, you really can't know exactly where you're going to be in the year. And so it's important to have hypotheses about the future, right? We believe the future will take this and not this, right? You know, but then we kind of react, we're more reactionary on a local level. You know, I mentioned our goal earlier, if I want to get to 100 million revenue and have less than 150 employees, that's way easier to achieve when you start from 10 employees and you start from 500 employees, right? And we're also fully remote business. And so we're kind of pushing the envelope on two dimensions of like, how do you use AI to basically stream like communication in an honor, person or that doesn't ever see each other in person one year? But I'll tell you that, you know, right now it's still, I think, really exciting time. So I mean, we, for our business, the thing we've been really excited about is not just writing notes for meetings, that's never been our goal. Our goal is what happens when we get all of your meetings, all of your team meetings, all of your company's meetings, into one data repository. So it's a really big data set. It's really hard to move, you know, historically, never been captured, certainly not structured. But if you get all that into one place, we're finding a place where the modern LLNs can actually do really interesting things. Like we did an example with ProType the other day where we said, hey, you know, you know, you know, Fathom tells us what's the history of transcription engines at Fathom? And it went back to every all hands, every engine you meet for four years and it wrote a six page article about everything we've ever done. You think about it for knowledge management, right? Yeah. Yeah. We don't, also seen where your loopholes are and where your vulnerabilities are. Say, hey, you know, you've listened to four years of my conversation. I don't remember what I had some dinner last night, let alone anything else. So being able to sit there and analyze, okay, where are their holes in our things? What have we missed? That was mission critical. That's something that, because again, I love picking on file them because it shows up and it annoys me all the time. I said, I want permission. I'm like, bugger off. But the ability to do that and then query everything down the road, that data set is infallible. Right. Once you get the point where it's like, you know, everyone hates meetings, but we love having great conversations, right? And I think what we're moving towards a world where you can have meetings and just kind of speak things into existence. We could talk about it and we get down to meetings done. The SW email straff did the power, the game or PowerPoint is already queued out sort of thing, right? And we get to a world where we get this really interesting dissemination of knowledge across the world in like a fun way. One of the things we're experimenting with is like, you know, everyone hates sitting in all these meetings where like, I didn't need to see your most of this. How do we start building everyone like a customized podcast that listens to every meeting adjacent to your, like adjacent to your function and gives you kind of like having crossed the word today? There's just so many fun things you can do now that you literally couldn't do even six months ago with the LMS we had then. So I, so I think, you know, I still wake up every day feeling pretty optimistic. Yeah, I look at some of my window feel less optimistic, but like, I feel like we'll get there. You know, humans, humans always solve things at the absolute last possible minute, but we usually. Yeah. So the Churchill said it really well. So the Americans always do the right thing after they've done everything else. Exactly. So that's kind of where we are on this. And I'm like, oh, God, here we go. Here we go. All right, just survive and hold your breath long enough. Go on that one. How are you dealing with, because a lot of, and this is getting away kind of from the AI, you created a very successful brand, a very successful company. It's all remote. A lot of founders, a lot of owners of companies have problems with that. Be there. How do we keep my team motivated? How do I keep them honest? How we keep them unified? How do we build this cohesive culture? So how have you survived and thrived in that environment? I think, you know, so the one of the reasons why I have this goal around 100, a million hundred with less than 15 employees is I've had a lot of very successful friends that go IPO, get to road big companies. And all of them say, gosh, when I tell them we're like 80, 90 people like, oh, I missed that. That was so much fun. And I always ask them, when did it stop being fun? And they're like, well, you know, the answer is very hundred, hundred, fifty, two hundred, but it's all in that range. And I hypothesized from talking to them, like, there's some point at which you switch from a high trust environment to a low trust environment. And, you know, you know, I picked one 50 for our goal because that's like the Dunbar number, which is like this theoretical limit of how many real friends you can have. And so I kind of think when you get above that number, it's impossible for everyone to be friends in your and you're almost inherently going to be a low trust environment. And so I think it's interesting. I see all the same stuff. We're like, oh, I let my employees work from home and like, they're not really working that hard and that. Oh, that's got you have a low trust environment. And I don't exactly know what creates high trust versus low trust. I mean, I think it's a cultural thing, right? I think it's something you get, like, you know, I think it's a lot about like, maybe how we go eat and how we communicate and how we motivate folks. But I do know you should just be aware of when you have what environment you have. And you're right, if you have a low trust environment with your employees, one, maybe we should get curious about like, how did that happen? And two, yeah, I don't like that need to get people back in the office because if you can't trust that they're going to work, you know, put in the work, right? Instead of structures might be evaluated. But I think we've been very fortunate in that like we have amazing team that loves the work they do. They're each are given enough autonomy. And given trust, I think high trust environments happen because when we hire people, I say, I say, I tell our team tell our sex, you should trust by default. You didn't want to trust them by default. You shouldn't have hired them. You should drive by default. You should give them room to run. You should, it's kind of like a kind of game. You shouldn't be prescripted about the dec need to look exactly like this. Is it 80% what you thought it was, but 100% what it needed to be? Yes, right? And I think that's an important factor. 80% of what you thought it was, 100% of what you needed to be. Right. And I think when hiring people, one of the best advice I ever heard was, would you trust this person to feed your children? In other words, if you got an accident and you couldn't provide for your family, would you trust that these people could do it for you? And if you can't say yes to that, then you have failed in the hiring process. So my, I guess my next question is, as you built this high trust environment, which takes time and it takes personalities and there's very specific things. Help with our view on getting rid of someone who does not fit into that environment. Our goals is 90 days. Like you generally, you usually know by 60, 45, 60 days and then just out of abundance of caution, like I think you can go as long as 90 days, you really can't go anywhere than that. But that's our goal. Right. I mean, I think it's generally pretty quick. The nice thing is once you have a high trust organism, the organism will reject any organs that don't seem to fit in with that. And they themselves, as long as you've got a good way to have listening posts that are not just, you know, like that's what gets harder, things get bigger. It's like, how do we, how do people trust they can tell me, hey, this new executive broadening is not like, is not all right, DNA sort of thing. But the organism knows if you can find a way to observe it. I'm, it's interesting that you do 45 days. I'm much faster on that. Yeah, we, you know, we, we're very quick. I mean, my grandmother said it really well. When you're dating someone, you will know within three weeks. And if you don't know, you know, and she, she's just bullet proof with that. And I miss her greatly. She's no longer with us. But when it comes to hiring someone, normally within the forced 48 hours, we don't pull the trigger that quickly. But within the first 48 hours, you've got enough of an icky, you've got enough of a, okay, this, I don't know if I want a second date. This might not, hmm, I don't get so I love that you have a big heart and you have high empathy. So model tough to you and near people. Well, what I'd say actually, we used to probably have, I would say that number used to be lower. But then everything looked at we said, the, anytime we find out it's not a fit in the first week, that is a real indictment of our hiring process. I thought I was in percent. And so I think now, now we're generally getting to things like, okay, we think our hiring process is pretty good, which means no one should be failing inside of three weeks, four weeks, right? We shouldn't be able to tell. We shouldn't be able to hit that like crazy. But you can't just for everything in the hiring process, right? That's what I think, like, okay, even with the best hiring process, those issues will show up a month and that's when, oh, they were all on their best behavior in the hiring process and we got a lucky in our references and stuff like that. Right. And we normally give people tests. We're like, hey, need you to do this, need you to do that. We kind of go through that process, like, hey, do these things. And we still have people actually test of what they need to do. And so that helps us out with what we're doing. So as we go through this and add things are changing as an organization and as for you, as you had a level of success that you never thought you were going to have, doing something you never thought you were going to do, what's next? What's the next big thing that you're like, hey, I really want to accomplish this. I think one of my superpowers entrepreneurs, like, I have like these built-in blinders sort of thing, right? I get really, I get so passionate about what I'm working on. I actually think like one of my superpowers is just getting passionate about things. I can get, I always say like, I always like to hire passionate people. Like, because passionate people get passionate about anything. You get passionate about plumbing. They came back to our like, you transition your career into it. You know, I think if you told me, like, hey, Rich, you're going to be a plumber. I would get so excited about fittings and the right stuff and stuff like that. And I think right now, it's like, there's just so much that like, it's the most fun time to build. It's the most volatile time to build. It's also the most fun time to build. I do, on a personal level, get really passionate about what I see happening in public discourse and what I'll hesitate to go politics. I will admit, I met with another entrepreneur yesterday who's told me he's running for city council. And I think he expected me to be disappointed. It might be kind of confused by that. I think that's amazing. I was like, that's amazing. I was like, politics, not enough, I think people of a high character, good judgment go into politics because they nudge it to be EV negative. And it is EV negative. That's not why you do it, right? You do it after you've gotten so much from the society that you feel like you should give back. And I, you know, I think there's a lot of stuff that I would love to do in that sphere in the future. Because I think, I think our country could use some help. I think it could use some, yeah, I judgment people that are not out for themselves. A thousand percent. It's interesting because it's a similar conversation I had over the weekend. We're talking about, hey, we've all been very blessed. We've all been very successful. Maybe it's time to get back and offset and maybe course correct some of the things that are going on that have been going on. Not just for this, this administration, but for many, many, many, many administrations. We're going back double digit. You know, it's like, oh my gosh, we got it. We have to pivot this and it's time to kind of have these people take over and do something different. So other than you're running for president in the next 27 minutes, if someone wants to track you down and they want to learn more about you and they want to connect because I'm just super grateful that you shared the stuff. What's the best way? How do they get a hold of you? How do they get a hold of Fathom? What's the best idea? Yeah, check out Fathom.ai. It's free to use. Please give it a shout. And then you can find me on the only social media that I use, which is LinkedIn. So find me the stodgiest of the social media. It's like, damn, nothing's here. I really appreciate you coming on. Thank you so very much. Charles is awesome. Thanks for having me. Actually. All right, guys, that wraps up our episode with Richard. I want to thank him for going out and sharing some insights and where things are going and the unforgiving truth of what's next with AI. I would ask two very specific paths and it's an our ability to dictate where that goes. All right, guys. I'll see you in the next one.