Why Building With AI Got Easy and Maintaining It Got Brutal with Fathom CEO Richard White

Kayvon Kay0:00Most people are reacting to AI. Our guest for this episode built for it three years before it arrived. Two bets. Transcription costs would fall to zero, and AI would get good enough to actually do something with what it heard. Both were contrarian then. Both were right. Fathom is now the top rated AI notetaker on g two, and Richard is one of the few people who can tell you what actually changed and what didn't. We get into why building software has never been easier, and maintaining it has never been harder. Why your years in business are an advantage in this shift, not a liability. And why the real bottleneck right now is not the technology. It's what you can see. If you have been waiting for the right moment to move, this is it. Richard White's background is engineering and product design. This is the vault unlocked. Let's unlock it.

Kayvon Kay1:04Richard, welcome to the show. I'm excited to have you. I just for the for the guests and the viewers listening, why don't you tell us a little bit of who you are? I'm excited because I use your product. I love your product. It's in our business today. I've seen you've changed it quite a bit, and I'm excited to have you here. But for the listeners that, may not know, tell them who Richard White is.

Richard White1:30I'd like to think I'm a product designer and kind of technologist. You know? No one's let me write code of production in, gosh, maybe ten, fifteen years. So I'm not sure I can claim being a technologist as much anymore, but that was my background. Originally kind of in engineering design, done a couple of startups. I worked at the first batch of Y Combinator if I wanna date myself. Their product before was called UserVoice, but as you kind of alluded to for the last five, almost six years, we've spent working on Fathom, which is the number one kind of rated on g two AI notetaker for people on, you know, lots of back to back meetings. It's been a really fun ride with a really great team, and the most fun part about it is talking to folks like yourself who love and use the product every day. Yeah. I mean, I've used a lot of different AI Notetakers,

Kayvon Kay2:14and I've used Fathom before, and then, you know, we switched, and now I'm back to Fathom, and I'm I'm I'm, you know, I'm actually I'm sold. I it's like it is to me, it's I find it's the most easiest interface. It just the usability of it. And I and I love that. I just feel like it's not overbuilt. It's just built, like, just exactly for what it is. Take us back to where did this start? Like, where did you see that this was needed? Because the one thing I do know about Fathom was way before this huge the AI craze and everything. So you you saw something way before. That's what I'm interested in, like, the vision and the strategy you saw and how you brought it together. Sure. Yeah. I mean, it was actually even right just before COVID.

Richard White2:56Honestly, was working on a different product. I was working on a totally different product and totally different space and just found myself on a ton of Zoom meetings. Like, I think it was like 15 to 20 a day. A lot of them were research sessions, right, where I've got twenty minutes almost back to back to, like, interview someone, demo something, get their feedback, rinse and repeat. And it's kind of one of those things where, like, you know, if you run into a problem once a day, you don't maybe do anything about it, you run into it 20 times a day, you're like, oh my god. This is really painful. I need to, like, I don't want I need to fix this. Right? And so, you know, I remember just kind of kinda thinking how how kind of crazy it is the way we kind of share knowledge out of, like, meetings and stuff. Right? Was like, I meet with someone. It's a great experience. They told me some really interesting quotes or facts or whatnot. And then I heard we scribbled down notes and then try to, like, clean them up for the meeting and remember exactly what they said. It's a very stressful situation. Right? It's like being a court stenographer. Right? And also being the the the the lawyer interviewing the person on the stand at the same time. Right? It's like you're kinda doing both and no one likes it. Right? No one likes taking notes. No one likes reading notes. That's also like a we're like a really poor artifact. I share with my team and a lot got lost. You know, I'd have this amazing conversation. I'd share the notes to my team and they kind of shrugged their shoulders. Like, okay. Right? So I sort of look at this and I guess there's something don't we have the technology to fix this at this point? Right? And, you know, if you go back to 2020, there were tools that were doing call recording. Nothing with AI yet, obviously. You know, most of the products are in the sales space, like companies like Gong and stuff like that, and they're really expensive, and they're candidly kind of mediocre. Right? It's like, it took you thirty minutes an hour to get the recording afterwards. It's mostly just a transcript. No one wants a transcript. What I wanted was just like, I get off the meeting, there's instantly some notes. Great. Like, I don't have to do this job sort of thing. And we kinda looked at that space and we kinda had this think thought, like, gosh, where is this space going? We kinda had two core hypotheses that really got us excited, got me excited about what turned into Fathom. That was transcription in five years ago, actually pretty still pretty expensive. Right? It's like 3 to $4 an hour to transcribe content, which doesn't sound like a lot. But if you imagine, if you build a product in transcription, build a product in meetings, people are easily gonna do ten, twenty, thirty hours a month on it. Gosh, your hard costs for that product are already, like, $50 a month. Right? So the fact that Gong and Fuchsig that were charging a $150 a month makes sense in that context. Right? I was like, why is this so expensive? Oh, yeah. The input costs are expensive. And so we kind of looked at it like, well, we think it's kind of commodity. Like, when I we we tried a bunch of different vendors, like, kind of made a whole prototype and tried a bunch of different vendors, like Amazon and Google and I think one was called Rev. These are all pretty good. They're not great, but pretty good. So this hypothesis, like, transcription costs will go to zero because it's they're all good enough and cost is always trending down. We think it'll go to zero. And more important than that, it's like and we think AI is going to get really good. And it's kind of funny now because it's kind of an obvious thing, but go back five years, very contrarian take because it's hard to remember, but there was a there was a wave of quote unquote AI companies like 2015 to 2020 that were terrible. Right? That Yeah. Promised you the world and delivered almost nothing. Right? And so but we're because I was like, no one wants a transcript. I don't want to get off a media and read a transcript. I don't want to read yeah. Well, nothing to do with the transcript, but the AI will need a transcript to do all the fun stuff I think it could do in the future. Write your notes, write your actions, fill in your CRM, find find trends, find themes, work new when certain things happen. All that stuff needs a really good high quality transcript. So we started the company with those two ideas and said, gosh, if those two things are true, transcription cost goes zero and AI gets really good, could we be the first people to give away this product for free? Right? And there was space where people were shorty a $150 a month. What if we just gave away for free? Because we actually don't think the value is in the meeting itself. It's in building up this database then you build a bunch of AI features on top of. And so we always have the seasons of it. We're going give away this product for free to individuals with the hope that that gets us into a bunch of companies where we can then sell a different product to the managers of those people. Right? Because the managers have a different problem, which is I I'm not in the meeting taking notes. I'm out the outside the meeting and I want to know the important things that are happening. I want to know there's a pricing discussion go it doesn't go well. There's an argument that happened at the end at the engineering stand up. There's, you know, a deadline that slipped three times, like but I don't have time to sit and listen to every meeting. Right? And so I got really excited about this business because it one, kind of fit the hypothesis of where I thought the world's going. But two, it had this really awesome kind of two sidedness to it. Have one part where you can give away a lot of value for free and feel okay about that because you don't have to like charge people later because there's just nice kind of complimentary business built on top of that for their managers. That's kind of how we got started. Right? It's kind of funny you mentioned that we were kind of ahead of the curve and I think that's probably true because we had a third corollary to those hypotheses which was if you wait to win transcription cost at zero and AI is really good, you'll be two to three years too late to start this business. Right? It'll be kind of obvious to everyone and everyone will jump in. But like like any technological revolution, the best companies, like, build towards a hypothesis couple years out and they do all the other stuff. Right? Like we spent two or three years building all the foundational work and the product experience that you talked about, the good user experience, good usability, the reliability, the obviously, distribution channels, all that sort of stuff. And so it was a very much a go to where the puck is going kind of thing, not like wait for it to get there.

Kayvon Kay8:30Then when so when you guys are doing the hypothesis, like, was, like, in back in 2021, you know, COVID days. I don't really like to use that word. Even I I hesitated to say it because, like, I feel like we we just don't use that word anymore. I don't I don't I don't I don't really use I hate using it. I mean, it's funny because, like, in sometimes my brain, I keep thinking, like, it was only, like, couple years ago, but I know it's like that's, like, almost six and a half years ago now, like, through you know? So today, there's a lot of players in the marketplace, but you you've had the market share. So are you seeing competitors, like, coming in and taking over? Are you are you guys adapting your product now more with AI? Like, how are you staying in the trends, and and how do you see where AI is going? I mean, even just with the note taking, let alone what is that next vision that you have for where this can go?

Richard White9:19Yeah. It's kinda funny. I mean, like, I feel like it's been a tale of two businesses. Right? There's a I I do this whole talk and I show my a revenue graph. You could see the point where AI actually shows up. And for us, that was kinda like GPT four level of AI. That was a point where the AI could write better notes than human. Right? And that's where we went from being a meeting recording business to being a meeting AI business. Right? And it really takes off. And this whole second act of the business is not about hypotheses and stuff like that. It's actually about, like, how do we get really good at building AI functionality? Because it's actually very fundamentally different than building traditional SaaS or just software. And I can talk about that. But so it's been kinda cool. And now we kind of are seeing this, like, you know, the capabilities increase every six to twelve months, and now sometimes it's even, like, two to three months. Right? And so we're constantly now seeing, like, okay. Two years ago, state of the art was we can write a really good summary for a meeting, and we can figure out the action items. A year ago, it was, oh, we can look across not just one meeting, but every meeting you've had with Acme or, you know, every meeting you've had in this with this prospect. And we can surface, like, risks. We can surface trends. And now let's say the odds moving to, oh, no. No. Now we can actually look across every meeting you've had over four or five years, right, across your work and tell you trends about competitor trends, internal knowledge management type questions. Like, you know, we asked it the other day, like, hey. We don't like to do a lot of documentation here at Fathom because we just assume that to the point, you just ask the AI, like, why generate documentation and maintain it? Just if you need to answer a question, you just ask the AI. Now we're at this point where that actually works. We can be like, hey. We got a new engineer, and they're wondering about why we built the system the way we did. Can we you give me a history of transcription engines at Fathom? It'll go over four years of meetings and it'll write a six page memo. Like, you know, ten minutes. So I think it's pretty cool we're moving this world where I mentioned two fun things are gonna happen in meetings. One, one, I just imagine meetings are gonna get really good. Right? Like, this has been my weird mission for someone who hates meetings. It's like, how do we make meetings actually fun? One, we remove all the work. Right? So, like, you don't have to be a stagographer, but also you don't have to get off a meeting and then have more work than we started. Right? I think that's where this is going. It's like, everyone hates meetings because I even if have a great meeting, I still the end of meeting, I'm like, oh, crap. Now I gotta go do all the stuff we talked about. We're not too far away. You get off that meeting and two thirds of it's already done. The email is drafted. The follow-up is scheduled. You know? The the, you know, the presentation we need to build out is already stubbed out. Maybe it's even 80% built. Right? So, like, one is this kind of magic of you speak things into existence on meetings. And then the other thing that I think where we're going and where the space is going is kind of like information finds you. So the other thing people hate about meetings is they're in a billion of them. Right? They're they're sorry, their inability? They're in a billion of meetings. Right? Oh, like, a billion of that. Yeah. Yeah. We're all in tons of meetings. And it's because it's like a primary way we disseminate information in organizations. Right? It's like, if you weren't there for the meeting, you're not watching the recording. You you lost it. Right? Like, because you don't wanna sit through a thirty minute recording or read the transcript. It's just on. Right? And so if one time you're needed on a meeting, well, shit. Now you're gonna be on that meeting all the time. Right? I actually think there's a not too distant future here where, like, hey, we have really small meetings. And if someone not in that meeting needs to know something about that because we talked about a project they're related to or we reference a customer that they're they're in charge of, that information finds them. I actually imagine a world where, like, you only have two, three meetings a day, but you have an amazing podcast you listen every morning that's basically curated from everything that's been happening around the world yesterday and what happened today. And it's telling you, hey, here's some updates around the world. You might want to go talk to Tim about this update or that. Wow. And so I kind of think that's a world where you've got, you know, AI native teams. There's smaller teams. There's less meetings, but there's actually paradoxically less meetings, but more shared context throughout the org. And so I think those two things, the work gets done for you and the information finds you, puts us in this, like, really exciting world where people can get out of meetings and get back to building stuff again, right, and doing work. Is that what you're is that what you're working on? Is that the Yep. That's is that, like so is that a different company or is that what fathoms No. That's that's that's our stated mission. Right? Our mission is to, like, make meetings amazing by kind of continuing down their source of intelligence that finds you, and we do the work for you. Or we a lot of times now, we partner with agents that'll do it for you. Right? So we have API, MCP, all that stuff, so they can do some of those action for you.

Kayvon Kay13:49It's interesting because I I I was just thinking so, basically, all these people, I just say, the different all the different departments, all the different roles are having meetings throughout the day. I just wanna understand this because I think it's wow. And then at the end of the day, all of that's curated into a twenty, thirty minute podcast maybe. So in the morning, all employees basically or anybody can, like, hey, what's going on in the company? You listen to it. You have full idea of what's going on in all the departments.

Richard White14:20And I love what you said information finds you. So if something is happening on the department in a meeting you're not even part of and your name is mentioned or whatever it might be, you would get a notification saying, hey, even though you had nothing to do with it, to either be ahead of it, to understand what's going on, whatever that might be. And you're actually you guys are working towards that right now. Yeah. I mean, we already have a version of this today where you can put in what we call trackers, and not like a keyword. It's just like, hey. I wanna know anytime a pricing discussion doesn't go well, or I wanna know anytime there was a heated debate, you know, like an engineering stand up. Or it understands tone, understands semantics, and it will compile all those clips together, and either daily or weekly, it'd be like, okay. Here's every competitor mentioned. Here's every pricing discussion that go well. Here's the themes of of of what these topics were, right, in cases like that. And so we already have today that it can go find you, but you have to kind of declare what things you care about. Right? We'll opt you into a standard set, but, like, but I imagine we're we're gonna keep going beyond that to, like, not only do you just kind of explicitly say, here's the types of moments I'm interested in, but the AI eventually just, you know, looks at the the job title on your badge and kinda says, oh, given you and I know the projects you're working on, like, I'll go set up a bunch of these myself. Right? Like and I'll listen to all these trackers, and then I'll synthesize them and give them to you. So kinda like kinda like the meeting notes themselves. Like, I think we've got the v one today, but I think where it's going is gonna be kind of mind blowing.

Kayvon Kay15:40Yeah. I was just as you're thinking as you were saying all that, I was thinking the next layer too is it could be an intelligence for the business owner, like for the owner or the, you know, the board of going, what what's the energy like in the company? What you know, are people happy in the company? Are people dissatisfied? I mean, obviously, people watch what they say on the meetings, but there is tonality. There's facial expressions. There's things that are happening

Richard White16:08that as a business owner, you can just get a report at the end of the week and be like, hey, you might you know, your engineering team, there's there's a there's an issue here. Like, this thing's about to explode. Yeah. There's not a lot of folks speaking up. There's, you know, very contentious meetings. There's a lot of stuff. And I I'm glad you mentioned tonality because, you know, when we first got in this business, everyone wanted to just, like, sentiment analysis on transcripts. And I'm like, so much is lost when you don't have tone. Right? Like, especially in business. Right? In business, it's all about tone. Right? I my background is engineering, but I ran our sales team for a minute in my last startup and, you know, tone is everything in sales. How yeah. Yeah. They said they're gonna buy. Play me that clip of them saying that. Right? Like, you'll know from that clip, like Yeah. Whether they're gonna do it or not. Right? So, yeah, it's pretty impressive what they can do now. And we're not doing it yet, but I also imagine, yes, facial recognition, like, you know, how engaged are people and stuff like that is something we'll look at in the future as well. I I'd haven't done research. Like, how big is Fathom now? Like, the company itself?

Kayvon Kay17:07By employees, about a 100.

Richard White17:09Okay. Wow. Okay. But we're we're also kind of you know, one of my internal goals is I would like us to get to a 100,000,000 revenue with less than a 150 people. Yeah. I actually have a lot I think actually, like, we're now in this era where it used to be that, you no one wants to talk about the revenue. No one's, like, gonna be like, oh, here's where our revenue added. Here's where our growth. So I've heard this uses employees as a proxy, but I feel like that proxy is getting broken. Right? Because so many companies now are like, gosh. I don't need a 300 person sales team now to get to a $100,000,000 in revenue sort of thing. No. No, you don't. And again, that's the power. Like, I mean,

Kayvon Kay17:41as an engineer, as someone who's incorporating AI into your product, and you've been incorporating it and obviously at the next level, where are you seeing the like, where where does the AI stop at some point? Because the one thing I've realized is, like, as great as it is today, it's still like, I don't care what I normally say. It's still not there. Like, if you ever had a like, if you ever had actually asked whether it's Claude or Claude Code or GPT to actually do something, it doesn't get it right every time. Like you sit there fighting with it. Where do you think it gets to the point where like you don't even you just kind of like, you're just talking and it's literally listening and it's literally building. And where when does that stop? Like how does that, you know, what's the negative impact of that? I mean,

Richard White18:23kinda look at it as like a kinda going back to, like, the command line versus, like, some package software. Right? Where it's like, I think we're getting this points where anyone can open the command line that's a Quad or JWPT and, like, get decent outcomes, especially for personal requests, stuff like that. But there's still a lot of room to basically engineer a better answer or a better output Mhmm. By being really intentional about which models you use and which order and whatnot. Right? And so I think, like, what we're seeing is kind of the, you know, the clause and whatnot are great general purpose solutions when you're like, I know I want this specific thing. You can get better speed, better accuracy, whatnot out of purpose still purpose built systems. Maybe we hit the point five, ten years where it won't matter. Right? And there's like, there's like a general brain. It's good at everything. Right? But at least for the next handful of years, there's still a lot of value in, I think, vendors like ourselves where we have a whole AI team that is nothing but an r and d lab that's constantly figuring out. You know, everyone thinks you know, all the time people are like, hey, give me all my transcripts. I'm gonna throw them all in the cloud, and I'm gonna ask it some trending questions. I'm like, you could do that. It will not succeed. Here's your transcripts. Like, for us, you'll get to the things I was talking about earlier, like those tracker concepts and able to, like, basically give answers across tens of thousands of meetings. There's a lot of engineers, a big pipeline of different AI steps we have to take. Right? It's not like one agent's doing this. Think about, like, it's a whole team of agents that are taking on different parts of this task.

Kayvon Kay19:47I I understand Yeah. What you're saying. It's not as easy as just throwing it up. But let's talk about that so people understand because I know people do that. They would throw up all bunch of their transcripts, you know, say Claude and say, give me the, you know, the feedback, but it's but it breaks. And there's a nuance it misses and

Richard White20:05and it hallucinates. I mean, mean, I'm working with it right now and it's like just nonstop hallucinating and I'm catching it. But for some people that don't know how to use AI properly, like, it's it's not as perfect as people think it is today. Yeah. I mean, that was one of the biggest challenges, you know, to even us kind of prioritizing things like this was, you know, when you're asking questions like, hey, tell me every time there's a price discussion that doesn't go well. Well, how many of your meetings have that? Maybe 1%. Hopefully hopefully, it's not like 20%. Right? I would say it's like point 2%. Well, gosh. Then you don't need a really high hallucination rate for most of content you get back to be hallucinated. Right? Like, the more you're looking for needles in a haystack, the more likely more painful the hallucination problem becomes. And so Okay. And so, you know, it's kind of funny. GPT five last year was kind of viewed, I think, commercially as, like, not a very impactful major release. But it was actually really important to us because they they one thing they fixed in that release was hallucinations. They dropped hallucinations by, like, 85%. And that actually opened up a whole bunch of use cases where it's like, all of our use cases, a lot of the interesting ones are needle in the haystack type problems. And that's why the dropping your all your transcripts in cloud doesn't work is because, one, the longer the context window gets, the less quality it gets. But two, sometimes 10,000 meetings just not gonna fit into that context window. And so you have to employ a multistep process and if one of those steps involves some agent that might hallucinate a lot, well, everything downstream from that part of that process is gonna be terrible. Right? Right. Yeah. Yeah. So it's funny you're talking about the new models. I just noticed, I don't know if I'm like I just woke up one day and, oh, Opus 4.8 is now out.

Kayvon Kay21:46Like, it's creates like, you it was Sona. It's it the the the speed at which AI is is being produced and building, I've never seen it before.

Richard White21:58No. Me neither.

Kayvon Kay22:00And and I think and I I feel like people are, like, not really, like, seeing it. I just I try to explain to people, like, it it's scary if you're not understanding it, and you're just sitting back and thinking that, like, we're gonna live in a world that ex like, that you think is gonna exist. It's not. Like, the new world, we don't yeah. I'm sure you can agree, like, even you as being such a visionary and seeing the future, like, very hard to see what this world is gonna be in the next five years. There's gonna be new jobs, new role, new new new things that we don't even have an idea or concept of that we're gonna be doing. Do you have any suspicions or any have you thought of any ideas of things that you can see how it would be different for us in the next five, ten years?

Richard White22:41I mean, I think I think there's a couple of shifts. I mean, one, my my my buddy, Emmett, who's on Twitch and now runs this AI company called Softmax, talks about I think there's a really good analogy where he describes models as kind of like, you know, certain level of education where it's like GPT three was like a eighth grader. Right? Yeah. GPT four was like a high school student. GPT five, you know, like, it it, you know, it kinda says like, you know, again, four years ago, we were at eighth graders doing things. Okay. What stuff would we delegate to an eighth grader? No. Not a ton. Right? Okay. High school student? Oh, okay. Now we're at kind of like kind of like unlimited grad students kind of thing. Right? It's kind of like the state of the art. Right? And so you I think if you think about, like truly think about this as what would you hire a grad student intern to do? It really shifts your your mindset on all these things. Right? You know, they're still gonna make mistakes. And that's where I think the the one interesting part is like, what does the grad student lack? It lacks business experience, business acumen. Right? And so I do think there's this kind of world where we kind of think, you know, youthful wolves inherent in world sort of thing. But I think for a lot of us that have been in business for a while, there's credible argument to be made that actually we're in a better position to build a bunch of agents because managing agents a lot like managing humans. Yeah. They need context. They need autonomy. They need, like, you know, guardrails, but also not micromanagement. It's kind of this interesting balance. It kinda looks a lot like managing people. And so I actually think a lot about, like, how are you building kind of how are you treating the AI, and how are you, like, building processes around it such that, like, it is a lot like managing a good team sort of thing.

Kayvon Kay24:25I and that's where, again, goes to say where you need, you know, a $100,000,000 company maybe needs a 100 engineers now, even maybe less. Right? Like, there are people saying that there's gonna be a billionaire, you know, billion dollar company with maybe two people, three people working I fundamentally think that too. Yeah. Yeah. So my my my goal my goal was, okay, that's to be true, and I I I do believe it to be true. Well, how many million dollar how many $10,000,000 companies will have four, five, and and whatnot? But I also see a lot of the big companies are still hesitant on really fully adopting AI still in their practice, or they're looking for third parties to adopt their AI because they don't wanna take the responsibility. Are are you seeing that as well?

Richard White25:08I mean, yeah, I've seen two things. One, we still see a lot of hesitancy in the enterprise to do anything these things because they're really hesitant about their data being elsewhere now that they can see the value of what you can do with that data, right, with AI. But on the other hand, we've also seen that, like, it's actually way harder to build internal AI tools than people thought. I mean, thing you were just mentioning about, hey, there's a new model every three, six months. The other side of that coin, which I don't think people realize is that that also means there's a model getting deprecated every three, six months too. So you go build something on OPUS 4.6, gosh, you maybe get six months before you need to go rebuild that on OPUS 4.8 because the finite amount of compute in the world is sloshing back over to 4.8. And even though they have a technically EOL 4.6, doesn't you know, when you ask it a question, it doesn't work two thirds of the time. Right? And so there's this the other interesting thing that we're doing is, like, we're moving a lot off this frontier models and onto open source models, not to save money, though that's nice, but because, like, the basically, the upgrade life cycle on these things is insane. Right? And they're not forward compatible. A thing you build for 4.6 will work for 4.8, but, like,

Kayvon Kay26:16you wanna start from scratch if you want. Yeah. You're And so you're just constantly rebuilding. Rebuilding.

Richard White26:21And so I think, you know, I still think there's a place for vendors like us because, like I said, for any feature we have, whether it's writing a summary, finding the action items, you know, answering questions, there's a purpose built pipeline there that usually has five or six different models in the mix, some from Frontier Labs, some open source, increasing more open source. But, like, it is not the the building cycle has gotten way easier. The maintenance cycle has gotten way worse. And so, like, it's never been easier to stand up a prototype pick. This what I want. This works. And yet that thing, you'll have to rebuild every six months. It's almost the new the new thinking. I I just wanna make that sound

Kayvon Kay27:00a little bit more for the everyday user because I think it's super important. The ability to build new products and services, SaaS, whatever it might be, has never been easier before, but the ability to now maintain them is actually harder, and that's because of the instability and or because of how fast AI is growing that the models are changing so fast that right when you even figured out how to build the product and actually stabilize that product, you're now going back to the rebuild. And I I do and I'm seeing that in some of the products I'm building myself is I go, okay. I get why I need an engineer team now. Like, I'm at that point where I can get it from, like, zero to five, but, like, you want to get it to the point where it it's efficient, effective, stabilize, you need the the AI engineer experts.

Richard White27:45Yep. The other interesting part is that we spend a lot of time thinking about what just got easy to build. Because there's a lot of times where you can go build a few like, oh, I want this thing to exist. So you can kind of almost, like, brute force it. Like, we've had a few features where we spent three to four months to find the right incantation of models and, you know, third party services to make a feature work. And then we wait six months and a new model comes out that just makes that like an afternoon project. Right? And so there's this other part about, like, just efficiency of building where it's like, oh, no. Not only do we wanna you know, it's never been easier to build, but we wanna focus on the things that are just became easy to build, thanks to new release extra y. And so, you know, I think our AI team spends half their time just reading white papers and keeping up to date on the newest launches so you can figure out, great. What was hard last week that's now easy? Because that's the stuff we wanna be building.

Kayvon Kay28:33That's that's the thing that I'm how do you keep up? Like, you know, if you're a business owner sitting and you're listening, right, business podcast, and you got a small medium sized business, and you're just trying to make the business exist and work. And now you're having to deal with all of this AI. It's not just about adopting AI. It's about adopting AI, and then it's changing so rapidly and so fast. What would be your advice or, you know, what could a business owner do it to to feel like they're not falling behind, but still incorporate as much AI into their business without it being something now a full time job? Yeah. I would I think

Richard White29:08those two like, well, comparing us to to that that scenario, think, is, like, comparing, like, a f one racing team to kind of, like, you know, me me hitting the track on the weekend. Right? So, like, do that because we are we are in a very competitive space. We're trying to beat the best in the world at this. Right? And we go out every Sunday and we do a race and, like, we throw away the engine after every after every race sort of thing. For the average business user user, actually, the market, it looks very different. And that, like, you don't really you you could take the thing you built on OPUS 4.6 and move it to 4.8. It won't be as good. No. But it'll be close enough that you won't care. Right? And the amount of gains you'll get today by just getting started today and building something will be insane. Right? And I think everyone, if you haven't had a chance to use an agent or, a Cloud Cowork or Cloud Co or something and just start building something, you just gotta get started. Like, there's no do not let the maintenance cost. Yes. It's there. Be it at all impediment to getting started because you will be blown away by not stuff you could do. I've talked to so many friends who are not technical, who are now automating whole parts of their businesses. Like, I've got friends that are salespeople that are building their own CRMs. I've got people that are marketing that are like, you know,

Kayvon Kay30:14barely can email and are yet like, hey. I built this operating system for my marketing team. It's it's my one. Right? You're talking to someone here. Like, I I I'm a sales guy. You know, traditionally, a sales guy who turned into a business owner around sales who's now full on, like, AI developer. I've developed, like, four products. One of them, you know, we're talking to big companies, right, just under some NDA, but, like and it's kinda it's like, if four months ago, if you said you're gonna be doing this, I would never have believed you. It's it's it's insane. This is why I tell you, it's actually insane what happens if you just sit at the desk and you just ask a simple question. How do I get started in AI? That's what I did. I I I was at a I tell people the story because I think it's very powerful. I was at an event in February and I was talking to AI expert like you who's just all in, all in. And I'm talking and just being kind of a pest and he'd and he kinda just got fed up and looked at me straight in the eye and just said, hey. He almost was kinda like, shut up. He's like, listen, you're either all in or you're not. You make the decision. And I went home that night and I and it was one of those things where it just sits and sits and burns and burns. And the next day I woke up, I said, I'm all in. So what does all in mean? Well, I gotta go and ask that. So literally ask, what does all in mean in AI? And then next thing you know, I'm built I'm seeing how it's working. You don't need to be like, you need patience, you know, and not to be afraid to ask the question. So it's it's it's it's interesting to me because I feel like there's gonna be a lot of these coming. I could be wrong. A lot of these like, lot of companies are gonna be coming out, and it's gonna be a race to to getting customers and a race to who has the best story or marketing. But the products are gonna be half assed. And then there's gonna be good products where the big guys are just gonna gobble up. I just I just think we're gonna have so many I'm seeing it now. Just so many note taking companies out there, but okay. Well, how do you decipher which one's the best? They all have a little nuance, but who's the actual best at it? I think the ones like you or the f one, you know, race team that are working on Sundays every day, you know, like you said, throwing out the engine. Right. Well, and then okay. Because we're kind of building platform stuff that other people could build on on. I I think from the for the small business,

Richard White32:28like, owner user type, it's never been a better time to be a domain expert because because the cost of building software has gone down so much, it now means it's viable to build software in places you wouldn't before. All sorts of niches or small verticals or very specific use cases where, hey. Look. I don't know everything, but I know exactly how these 20 farmers do their business and what they need to do. Ten years ago, you could you gotta go raise a couple million dollars, go build it. Well, that market's not worth more than a couple million dollars. Now you go build that in the weekend, and that's a very profitable business. And so it's now kind of democratized creating software. It's like you actually you do need folks like myself and my AI team if you're gonna go build the f one car, you're gonna try to be one of these foundational platforms everyone else is used to build on. But if you're just trying to solve a problem that you know, like, back of your hand, oh, boy, are you this is gonna be a gold rush for you. Right? Because if you have the expertise or, like, yourself, you got those connections, you know the problems people have, you don't don't need to hire a 20% team and raise $5,000,000 to get off the ground. You can just get it done this weekend, and I think that's gonna be amazing. I'm gonna leave it here because I believe we're

Kayvon Kay33:37saying the same thing, and I and I and I've been saying to people, like, with AI today, the only limitation is the mind, is what you can or cannot see at this point. There's nothing you can't do or can't build or can't visualize or can't even bring to fruition that AI can't do for you. The only thing that's limiting people is what's going on in their mind, I would agree and say. Yeah, 100%. Well, listen. I know that you do this. You're talking about you you don't need to be on these shows. You do this because, you know, you're you help podcasters like me and, you know, helping other business owners understand the power of it. I will just say this for anybody. If you are on meetings, this is not a plug. Never asked me to do this. I just wanna make sure you understand. If you are using meetings, if you're on Zoom, Google, whatever kite type of online meeting, you must have Fathom. It's very, very simple. There's no other product out there that is as easy to use, as efficient, as effective, and just awesome. Fathom is what you need. Alright. Any last notes or any last thoughts? No. And it's mostly free. So No reason to check it out. Yeah. Yeah. You don't like I always say, you don't got a $50 problem. No business in the world has a $50 problem.

Richard White34:50Again, Rich, thanks so much for being here. Appreciate it. For having me. This was fun.