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

0:00Welcome to the Proven 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 the 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. Anyway, 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. Hey, thanks for having me.

0:29So for the four of our people who don't know who you are, can you explain what you've done, what your success did. Sure. I'm the founder and 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. And so we have basically an AI that will join your meeting, record it, transcribe it, summarize it, write the notes, write the action items, 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 doing 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 uh 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 And AI has completely upended how we think about building software.

1:30Yes. Made it much more of like an R &D process now, whereas before it was more of like a manufacturing process. It's also made the failure rates much higher, right? Like, you know, it takes a long time to sometimes ship an AI feature because it'll 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, move our business forward. We actually have a goal at Fathom of getting to 100 million in revenue while staying below 150 employees. And so we have this big emphasis on efficiency and automation.

2:03And it's interesting because we had this, you know, I just gave this talk where I expected to give a 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 things actually work? Damn you, man. You've ruined it all for us forever. I'm so sorry.

2:33So as we go into these, you're talking about failure. 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, I will get on a plane that has a 62 % failure. What do you mean there's a 62 % failure ratio in AI? I mean, so actually there was this MIT study that just came out and said, like, 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.

3:02It's like, in AI land, it's easy to get it to produce something. It's easy to get the AI to spit out something. Right. Our part is getting it to spit out the right thing. And what is the right thing? So, for example, in our business, right, you know, I could, you could build an AI that gives you an accurate summary of a meeting that's six pages long. but actually it may not be enough. Like that's too verbose. I don't want a 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?

3:33We're used to software as binary. It works or it doesn't. I click the button, the thing moves on the screen, right? And now we're in this world where I click the button and 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 hire, right? It's more like a hire because you're basically buying thinking, not features now. And so it kind of upended how we think about purchasing products.

4:05So I can't even get ChatGPT 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 significantly higher. How do we get it to produce content that we actually want or go from that 10-page dissertation that's so verbose into what we want? How do we do that at the home level for your everyday consumer? And then also, as the CEO, as a very successful company, because every single meeting I'm in, your damn software is there before anyone else joins. Thanks for that. I'm a little angry about you with that one.

4:39How 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 ChatGPT is like actually 40%, which is still not great, but way higher than 5%, right? And I actually think, I think AI is actually easier for individuals to use because individuals are basically taking ownership of that output, right? Like it's like, oh, it's writing this email for me. And yeah, I hate that it always puts the end dashes in there too, but I can at least 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.

5:12Right. You know, we have a whole team at Fathom 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 as like all day we are experimenting with like, you know, basically models and use cases. Right. And does this model good at this use case? Can this model find action items from a transcript? And I call it Jenga because like if you push on a block and it gives any resistance, you give up. You find another block that moves smoothly. Right. Because there's a weird kind of like problem you've got now where you've got so many models with differing kind of performance parameters, cost parameters.

5:50And so we want to do. So it's a really big problem. You don't need a full-time team if you're building stuff. 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-day pilot for AI. going to have a whole team that QA's it. And when we don't do that, it almost never works. So when new GPTs 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, do that.

6:26And I have very specific calls for it to do that. When a new one comes out, do you guys over at Fathom have the same puckering motion that we have on our side? We're like, oh God, everything's about to blow up again. Is that something you guys are facing as well? Yeah, on two dimensions. 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. Hallucination 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.

6:58But it causes also other problems in that none of these models are 4-compatible, right? You get something working on GPT-4. It's not necessarily going to work the same on GPT-5. And even more problematically, and I think this is something that everyone in the industry is starting 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.

7:41And 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 land. it's it's it's one of those things and i'm going to date myself here but the original warcraft 2 because i'm that old before you can see by the smile you played it before i would go and i would attack the orcs or i would attack the knights or whatever it was i would save my military formation okay if this doesn't go well i'm gonna go attack and i'll die i can just go back again i wish that existed inside check gpt where or any gpt that we're going we're like okay it's, I should try and do this, quit giving me dashes, or I want you to work it this way.

8:26And then for some reason, AI becomes always incorrect, and it just goes off on a tangent. I'm like, excuse me, sir, can you just go back 30 seconds? That would be nice. And then it sounds like 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 in 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 right uh but by building in-house you have a better sense of like cool we at least know we got it to do one small critical thing that you had to do right a lot of vendors throw a lot of things at you right 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 at some point right it's like 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 you know we did the dot-com boom and everything was going out with the internet right oh this is gonna be amazing and then you know pest.com is gonna be amazing and this is gonna be amazing obviously 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 three weeks after are you seeing that with established companies are sitting there going oh shit we've got you know there's a the light of the tunnel is not a light it's a train we got to adjust because what worked today just won't even exist and how short is that time frame i mean i think the exciting thing as 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 to do software, right?

10:13They're used again to this assembly 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 click the button and it moves, you know, 10 pixels to the left. We're 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 a lot 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?

10:43They don't know how to judge basically like subjective quality. And they're still looking at it from their kind of like objective, like did it do the thing? Did it spit out words? Yes, great. Passed, UA, ship it sort of thing. So I actually think there's a challenge if you're buying software because a lot of times the bigger incumbents actually have inferior products to the new startups. New startups have their own problems, right? Of like, you know, instability and whatnot. 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 in how to build software in this new era.

11:14And so I think it's exciting, actually, as much as it is also terrifying. Yeah, I think the best example I've heard of this is imagine you're on a train that's going as fast as possible, and you're on one car of the train, and you're fixing it as much as you can, but all of a 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 tip of 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 thing showing up to all the means is something that everyone uses um where 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 either 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 you you're in there you're with the ceos you know what's going on better than even someone the regular person would be how does this look in five years yeah i mean one thing i will say is this is to me the greatest technological shift of my lifetime bigger than it's really bigger than mobile bigger than social you know i don't seem to say bigger than the internet itself right like there is real there right like for all the failure rates and stuff like that they're also the denominator is huge right everyone's trying stuff because this is the closest thing I've seen to magic.

12:34One of the challenges is like, yeah, what is, you know, I have 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 beyond AGI type things? Smarter people than I, I think the real question is kind of the open question right now on the market is, you know, my kind of core friend group, 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 uh 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 were like what are you doing everyone hates ai it's easy to forget it was only four years right 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 it was basically fraudulent kind of stuff.

13:26But 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 thinks it's 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 style the next, you know, step up. It's clear that we're getting diminishing returns from the current generation of transparent-based AI, like GPT-5. I think everyone kind of sees all the latest models are now more optimized for efficiency.

13:56They're not wildly smarter than the previous model, but they're cheaper to run, which is important. Companies running for their margins and all that sort of stuff. I've kind of taken the 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 to accelerate. It's almost a possible plan for anyways. So, and we're kind of, again, I think GB5 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 transformer models alone um but it is the most volatile market i can ever imagine right like you know we've 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 100 million a billion in revenue in two years right it's right and then go back down to zero two years later right like look at the jayers and stuff like that so is insanely volatile market full of tons of opportunity but how long lived those opportunities are i think is to be seen yeah i think to your point of what does this mean to the human race um i will give a little bit of pushback i don't i don't think it's better than internet i don't think it's better than industrial revolution i don't think i think it's better than the only thing better than this is fire that's as far as the human race is concerned this is this is fine as far as what can do now fire was good and bad it can burn down your entire village yes but it also makes good food we can you know 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 it's going to be pretty 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$100 million company run with just a single employee?

15:49Do 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 highly possible. And then you can extrapolate all the concerns you have about societal upheaval and wealth inequality and from that pretty easily. But yeah, no, I think that's perfectly reasonable to expect. Yeah. 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 of basically India.

16:21When you look at how people are distributed, especially here in the United States, you're going to see that. So if for those of you who are playing at home who might not understand everything that Richard was talking about and what he's doing, you do not have the luxury to sit on the sidelines. 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.

16:49When 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 I most likely will. So how do you advise entrepreneurs? How do you advise business owners? And hey, these are some proven 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 from there. What are the things you advise with? I mean, honestly, I think there's never been a better time to start something that's really narrowly focused, right? You hear a lot about the big platforms that are, again, going from zero, like a Jasper, going to zero to 100 million and right back down.

17:26But the real beauty of this stuff is like, 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, you can, you don't have to have a CS degree like I have in 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, some prototyping tools and you can build something of value. Right. And so, you know, I remember 10, 15 years ago, everyone was kind of doing like the, you know, the, uh, was it the lean startup stuff where they're like, Oh, you know, like they're selling stuff before they really even built it.

18:02And, you know, that got taken to an extreme, but now you literally can really narrow down. don't find a very specific niche and you can build a really good like and i know this is kind of a majority of a lot of 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 and noise and all this stuff is all kind of at the like foundational layer. It's all about who's building the big infrastructure stuff.

18:37But that's a billionaire's game. You need a lot of money up front to do that. I think there's a lot of money to be 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 that person that's going to be the single person company doing 100 million revenue, I don't think there's going to be a foundational model. I don't think they're going to be something like Fathom. I think they're going to be something that sits above something like that right or above these foundational 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 you're seeing people where entire divisions are getting eradicated people with master's degrees from i'm unique schools or you know trying to get jobs at mcdonald's right now and they're terrified as i rightfully think they should be this welcome to this new world do you know when we were me when When I was there, being an entrepreneur was not sexy.

19:29They did not like that idea. Being into comic books, not sexy. Being a dork, not sexy. And then all of a sudden, now we're like, it's our time. Our time has come. And same thing with entrepreneurs. The employees that I know are terrified. They are fundamentally, they're like, hey. And they go back to their old model, which is, I'm going to be in another degree. I'm like, that's not going to help you. That's over. Those times are gone. So what do you say to those mid-level, medium men, mid-level managers, kind of just you know senior directors vps what do you say to those guys who have said like i've built and i've 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 you are no longer built for this and the thing you were built for does not exist anymore how do you adapt yeah i I mean, that is the question, like that will be the question of the next five, 10 years, right?

20:26I remember, you know, I was a big proponent of like, I was telling everyone to listen about UBI 10 years ago. And I was worried about truck drivers back then, right? I was like, truck driver, 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 assured that that was the first thing, the first kind of like industry to get through. And years ago, here we are at 2025. and actually it's no it's artists it's copywriters it's pretty soon going to be lawyers middle level management it's all knowledge therapists yeah yeah exactly and so um so you know what would i say you know honestly it's like it's there are no i would tell you like your fear is well founded first of all right like and unfortunately like i'd love to sit here and tell you that you've got nothing to worry about and i think you do right uh you know i think what you're seeing when you look at what's happening, uh, you know, uh, college enrollment is down, trade school enrollment is up.

21:24And I think like, you know, people that are kind of solving this first principles, the folks coming out of high school are looking at that saying, gosh, you know, there've 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. Uh, you know, I think that's a tough sell too. I think there's like a middle ground where if you really become I'm 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 to a 25 % success rate.

21:55And there'll be a lot of opportunities there. I think it really depends a lot where you are in your career. I mean, I've been building software for 20 years and I've always thought that like, you know, I can always fall back. I know how to organize people to build great software. I'm not sure that'll even be a skill set in five years, right? That's correct. um you know i'm very much playing like if i don't have kind of a exit or retirement plan over the next five ten 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 opportunity for people to learn how to become experts of you can be an expert replacing your own job with ai that gives you a job over the next couple 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 for a fair example none of us other than you are having in these boardrooms with these people who are you know very much the 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 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 as well.

23:09I 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 a software company and usually at least 10 years before someone really disrupted you. And then now, you know, it started now it's like five years, pretty soon it'll be two years where it's like, there's so much technological change. It just undoes, you know, valuations for SAS businesses, you look at them today versus five years ago. Oh my God. Yeah. Right. Um, so I think there's a, the boardroom I think there's a lot of conversation about that again about like AGI and like what would that mean could that just you know render a lot of businesses irrelevant um I think the conversation we should be having is the one we're kind of tiptoeing around which is like how do we as a society handle this um there's a really good short book called MANA M-A-N-N-A uh by this guy Marshall Brain do you remember howstuffworks.com awesome website uh the guy's actually from my hometown of Raleigh North Carolina you wrote this It's like 25 page book.

24:07And it was kind of a tale of two cities. One city actually set in the U.S. that 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 amongst 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 utopian as one example or as utopian as the other but i don't think we're i think we're everyone's busy fighting trying to 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 guardrails and push the genie in one way or another right like and so um i think the other thing people are talking about is also candidly like ai regulation um the other thing is like you know i think a lot of folks in tech land voted for trump and one of the reasons 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 agi first if you believe in western south democracy bad things happen right um and so i think that's another there's like you know kind of so many different 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 cuts over and then the robots are going to take us over and turn us into cottage cheese where do you think and what's more realistic for that i i think all the paths are still open i you know i don't you know i think it's not the answer i wanted to hear but okay yeah i just peed on myself a little bit you know i i think we would be foolish.

26:00I think there's a lot of folks in AI land that are concerned about AI safety. Like a lot of the, you know, a lot of the kind of open revolt that they had at open AI a year ago was about this 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 critical moment in human civilization. And everyone needs to educate themselves a little bit and do what they can to make sure we're nudging ourselves in the right direction.

26:40So for all of you who 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, stop it. Let's try to give people a little bit more hope about what's done. So there's a lot of conversation about what AI can do and not only just the basic stuff with business, but what's been done medically. Like, hey, we've made X, Y, Z 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 100 years. It's in 27 seconds.

27:08So there are some amazing things with AI. Can you kind of share some of your favorite ones that, you know, you've seen that have kind of personally 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? Where like weak things that used to be really expensive, right? Like analyzing scans, the early detection, like our healthcare system, my father was in emergency medicine for 30 years. He always first want to tell you we are really reactionary in healthcare for a number of reasons.

27:38But 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. You got to look at these blood markers. You got to do all these things both on the, kind of like the preventative maintenance, preventative medicine stuff, as well as research. And this is going to drive down the cost of all that stuff dramatically. Oh, yeah. 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.

28:20Um, but it's going to be kind of the wild west in the meantime, because also our medical regulations haven't really caught up with that. Right. No, no, no. I don't know how to handle it. But I think that's probably one area you can look at and point to and be like, it's going to be a lot of good done there. I think, you know, for all the disruption that we're going to see with self-driving cars, that's also going to place where we'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.

28:46Think about what happened when you don't have to dedicate, you know, 40 % of your city to parking. Think about what happened when, you know, people aren't getting in car accidents left, right and 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 people look forward to. In the same way, you look at the same thing with like the industrial revolution and stuff like that. there were a lot of painful things in that transition. A lot of terrible things happened. Humanity was better for that transition in the end. Right. But it will be.

29:14I don't think we have to go as far back to the industrial revolution either. Even with the IT boom, when technology kicked in, people 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 the internet, it wiped out walls of jobs. But the job that you have right now did not exist before that. The jobs that I did, the careers I had. So yes, it will wipe out a ton of shit. will also create a ton so i think there is and i think to your medical point now there's a difference between our dna and dna there's different with that how we measure those things some things don't change because even if you die of cancer your dna is 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 based off your stuff your individualized goodies you should be taking this i was i was sitting with the ceo uh one of the companies that 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.