The Vault Unlocked - Why Building With AI Got Easy and Maintaining It Got Brutal with Fathom CEO Richard White

Episode Date: July 29, 2026

Building software has never been easier. Keeping it alive has never been harder. Most founders adopting AI right now have only priced in the first half of that sentence. Richard White is the founder and CEO of Fathom, the top rated AI note taker on G2. He started the company just before 2020 on two bets almost nobody agreed with: transcription costs would fall to zero, and AI would get good enough to do something useful with what it heard. Both were right. He breaks down what actually changed, what didn't, and why the maintenance cycle is the part nobody warns you about. A new frontier model lands every three to six months. The other side of that coin is that a model gets deprecated every three to six months too. Build on one version and you have about six months before you rebuild on the next. Richard explains why Fathom is moving workloads off frontier models and onto open source, not to save money, but because the upgrade cycle is unsustainable for anything you intend to maintain. He walks through why a purpose-built pipeline running five or six models still beats a single general purpose call, what happens to accuracy when you're searching for something that appears in one percent of your meetings, and why the GPT-5 release that landed flat commercially mattered enormously to anyone solving retrieval problems. Then he flips it. Fathom operates like a Formula One team because it competes at the frontier and throws away the engine after every race. A normal business isn't in that race. Move your build from one model version to the next and it'll be slightly worse and close enough that you won't care. The maintenance cost is real. It is not a reason to wait. This is for founders and operators making real decisions about AI inside a business that already generates revenue, and for domain experts sitting on knowledge they've never been able to productize. Software markets that were never worth raising against are now buildable in a weekend by the person who already understands the customer. Questions Answered Why has building with AI become easier while maintaining it has become harder? Why is Fathom moving from frontier models to open source? How should a business owner adopt AI without it becoming a full time job? What replaces the meeting when AI captures and routes the information for you? Why doesn't dumping all your transcripts into a chatbot work? What does managing AI agents have in common with managing people? How does model capability map to what you can safely delegate? Can a domain expert now build profitable software without funding or a team? Is headcount still a useful proxy for company size? Looking to dive deeper into these conversations and connect with our host and guest? Follow Richard White: LinkedIn X Learn more about Fathom Follow Kayvon: Instagram Facebook LinkedIn TikTok     Want to go deeper with Kayvon? Subscribe to the newsletter Book a discovery call Get your Revenue Engine Scorecard™️ Hire the right salespeople

Most 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 note taker on G2.

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 vaults unlock.

Let's unlock it. Richard, welcome to the world. 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 how Richard White is. I'd like to think I'm a product designer and kind of technologist. No one's let me write code of production in, gosh, maybe 10, 15 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 startups. I worked at the first patch of Y accommodator if I want to date myself, did a product before this called User Voice. 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 G2 AI note taker 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 will have and use the product every day. Yeah, I mean, I've used a lot of different AI note takers. And I've used Fathom before and then we know, we switch and now I'm back to Fathom and I'm I'm, I'm, you know, I'm actually,

I'm sold. It's like it's, to me, it's, I find it's the most, uh, easiest, uh, interface, uh, it just 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 to 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. Honestly, it was working on a different product. It 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 20 minutes, almost back to back to like interview someone, demo something, get their feedback, rinse and repeat. And it's kind of one 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 kind of thinking how kind of crazy it is the way we kind of share knowledge out of like meetings and stuff, right? It's like, oh, I meet with someone. I had this great experience.

They tell me some really interesting quotes or facts or whatnot. And then I heard where we scribbled down notes and then try to like clean them after the meeting and remember exactly what they said. It's a very stressful situation, right? It's like being a court stonographer, right? And also being the lawyer interviewing the person on the stand at the same time. Right. It's like you're kind of doing both. And no one likes it, right? No one likes taking notes. No one likes reading notes. Notes were like a really poor artifact. I'd 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'd kind of shrugged their shoulders. Like, okay. Right. So I just remember looking at this, me like, there's something, don't we have

the technology to fix this at 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 Gog and stuff like that. And they're really expensive. And they're candidly kind of mediocre, right? It's like, oh, it took you of 30 minutes an hour to get the recording afterwards. It was 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 kind of looked at that space and we kind of had this think, thought, like, gosh, where is this space going? We kind of had two core hypotheses that really got us excited. It got me excited about what turned and fathom. That was transcription five years ago, actually still pretty, still pretty. expensive, right? It's like three to four dollars an hour to transcribe content, which doesn't sound like a lot. But if you imagine, if you can build a product and transcription, build product

of meetings, people are easily going to do 10, 20, 30 hours a month on it. Gosh, your hard cost for that products are already like $50 a month, right? So the fact that Gong and Fuchsickick that we're charging $150 a month makes sense in that context, right? I was like, why is it so expensive? Oh, right? The input costs are expensive. And so we kind of look that. We think this is kind of commodity. Like when I, we tried a bunch of different vendors. I kind of made a little prototype and tried a bunch of different vendors like Amazon and Google and I think one is called Rev. I was like, these are all pretty good. They're not great, but pretty good.

So this hypothesis is like transcription costs will go to zero because they're all good enough. And it costs always turning 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. very contrarian take because it's hard to remember, but there was a wave of quote-unquote AI companies like 2015 to 2020 that were terrible, right?

That 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 reading a transcript. I don't want to read. 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 it. find trends, find themes, it'll work me 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 costs go zero and AI gets really good, could we be the first people to give away this product for free? Right? And the space where people are showing you a hundred feet dollars a month. What if we just gave away for free? Because we actually don't think the values 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 thesis of like, we're going to 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'm not in the meeting taking notes. I'm outside the meeting and I want to know the important things that are happening. I want to know there's a pricing discussion that doesn't go well. There's an argument that happened at the engineering stand-up. There's, you know, a deadline that

slipped three times. But I don't have time to sit and listen to every meeting, right? And so I got really excited about this business because one kind of fit the hypothesis of where I thought the world is going. But two, it had this really awesome kind of two-sidedness to it. We had 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 a 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 is 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 jump in. But like any technological revolution, the best companies like build towards a hypothesis couple years out and they do all the other stuff, right? 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 wasn't very much a go to where the puck is going kind of thing, not like wait for it to get there. then so when you guys are doing the hypothesis like this was like back in 2021 uh you know COVID days I don't like to use that word I haven't I hesitate to say like I feel like we just don't use that word anymore I know I don't I don't use I hate using it I mean it's funny because like sometimes my brain I keep thinking like I was only like a couple years ago but like no it's like that's like almost six and a half years ago now like you know um 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 how do you see where AI is going? I mean, even just with a note taking, let alone what is that next vision that you have for where this can go? Yeah, it's kind of funny. I mean, like I feel like it's been a tale of two businesses, right? There's a, I just will talk and I show my revenue graph.

You could see the point where AI actually shows up. And for us, that was kind of like GPT4 level of AI. That was a point where the AI can write better notes than a 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 kind of cool. And now we kind of are seeing this like, you know, the capabilities increase every six to 12 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 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 the state of the UF's 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, 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, just ask the AI. And now we're at this point where that actually works. We can be like, hey, we've got a new engineer. And they're wondering about why we built the system the way. we did. Can you give me a history of transcription engines at Fathom and it'll go over four years

of meetings and it'll write a six-page memo? Like, you know, 10 minutes. So I think it's pretty cool we're moving this world where I imagine two fun things are going to happen in meetings. One, I just imagine meetings are going to get really good, right? Like, this has been my weird mission for someone who hates meetings. It's like, how do you make meetings actually fun? One, we remove all the work, right? So, like, you don't have to be a stographer, but also you don't have to get off a meeting and then have more work than when you started, right? I think that's where this is going. It's like, everyone hates meetings today.

Even have a great meeting, I still at the end of the meeting. I'm like, oh, crap, now I've got to go do all the stuff we talked about. We're not too far away. You get off that meeting, two terms of it's already done. The email is drafted. The follow-up is scheduled. You know, the presentation we went to build out has 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 sorry, their inability. They're in a billion of meetings, right? Oh, and a billion. Yeah, yeah.

Yeah, we're all in tons of meetings. And it's because it's like the 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 lost it, right? Because you don't want to sit through a 30 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 not. going to 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 in charge of, that information finds that. 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 work yesterday will happen today. And it's telling you, hey, here's some updates around their work. 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, there's 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 to get back to building stuff again, right? And doing work. Is that what you're working on? Is that the, that's is that like so is that a different company or is that what fathoms no that's that's that's that's our state of 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 it's interesting because i i was just thinking so basically all these people i just say all the different all the different departments, all the different roles are having meetings throughout the day. I just want to understand this because I think it's wow. And then at the end of the day, all of that's curated into a 20, 30 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. And 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 it's not like a keyword. It's just like, hey, I want to know anytime a pricing discussion doesn't go well. Or I want to know any time there was a heated debate in like an engineering standard. stand up or it understands tone, understand semantics, and it will compile all those clips together and either daily or weekly, it'll be like, okay, here's every competitor mentioned, here's every pricing discussion that go well, here's the themes 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 going to 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 job title on your badge and kind of says like, 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 it to you. So kind of like, kind of like a meeting notes themselves. Like, I think we've got

the V1 today, but I think where it's going is going to be kind of mind-blowing. Yeah, 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 that 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 a, there's an issue here. Like, right? This is a,

things 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'm glad you mentioned Tonaday because, you know, 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, by background on his engineering, but I ran our sales team for a minute, my last startup. And, you know, tone is everything in sales. Yeah. Yeah, they said they're going to buy. You know, play me that clip of them saying that, Right.

You'll know from that clip, like whether they're going to 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 engage our people and stuff like that is something we'll look at in the future as well. I haven't done research. Like, how big is Fathom now? Like the company itself. By employees, about 100.

Okay. Okay. But we're also kind of, you know, one of my internal goals is I would like us to get to 100 million revenue with less than 150 people. people. Yeah. I actually have a lot. I think actually like we're now in this era where it used to be that, you know, no one wants to talk about the revenue. No one's like going to be like, oh, here's where revenue added. Here's where it's where growth. So I've heard just use as 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 $100 million in revenue sort of thing.

No, no, you don't. Again, that's the power. Like, I mean, as an engineer is someone who's incorporating AI into your product and you've been incorporated 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 say. It's still not there. Like if you ever had to like if you ever actually ask whether it's Claude or Cloud Code or GPD to actually do something, it doesn't get it right every time.

Like you're 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 i kind of look at it as like kind of 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 chat chippee and like get decent outcomes especially for personal request stuff like that but there's still a lot of room to basically engineer a better answer or a better output

by being really intentional about which models you use and which order and whatnot. And so I think like we're seeing as 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'll get to 0.5, 10 years where it won't matter, right? And there's like, ah, 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. And I think vendors like ourselves, where we have a whole AI team that is nothing but an R&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 going to throw them all in the quad and I'm going to ask it some trend in questions. I'm like, you could do that. It will not succeed. Here's your transcripts. Like for us to get to the things I was talking about earlier, like those tracker concepts and be 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. I understand 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 a bunch of their transcripts in, say, Claude and say, give me the, you know, the feedback. But it's, but it breaks. And there's a nuance that misses.

And it hallucinates. I mean, I mean, I'm working with it right now. And it's like just nonstop hallucinating. I'm catching it. But for some people that don't know how to use AI properly, like it's not as perfect as people think it is today. Yeah, that was one of the biggest challenges,

you know, even us kind of productizing 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 your meetings have that?

Maybe 1%? Hopefully it's not like 20%. Right? I would say it's like 0.2%. Well, gosh, then you don't need a really high hallucination rate for most of the 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, and so, you know, it's kind of funny. GPT5 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, 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 quad doesn't work is because one the longer the context window gets the less quality it gets but too

sometimes 10,000 meetings just not going to fit into that context window and so you have to employ a multi-step 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 going to 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 opus 4.8 is now out like it's great it's like it was son it's it the the the speed at which i is is being produced and building i i've never seen it before no me either in and i think and i feel like people are like not like seeing it i is 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 going to live

in a world that is like that you think is going to exist. It's not like the new world. 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 going to be in the next five years. There's going to be new jobs, new role, new new new things that we don't even have an idea or concept of that we're going to 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, 10 years? I mean, I think these are a couple shifts. I mean, one, my buddy Emmett, who used to run Twitch and now rooms 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 GPT3 was like a eighth grader, right? Yeah, GPT4 was like a high school student. GPT, five, you know, like, you know, it kind of 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? Not a ton, right? Okay, high school student?

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 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 mindset on all these things, right? You know, they're still going to make mistakes.

And that's where I think, 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 like this kind of world where we kind of think you know youth will always inherit the world sort of thing but I think for a lot of us that have been in business for a while

there's incredible 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 contacts they need autonomy they need like you know guardrails but also not micromanagement. It's kind of this interesting balance. It kind of 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. I. And that's where, again, goes to say where you need, you know, a hundred million dollar company maybe needs a hundred engineers now, even maybe less, right? Like there are people saying that there's going to be a billionaire, you know, a billion company with maybe two people, three people working out.

I fundamentally think that too. Yeah. Yeah. So my goal, my goal was, okay, that's to be true. And I do believe it to be true. Well, how many million dollars, how many $10 million companies will have four or five 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 want to take the responsibility. Are you seeing that as well? 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, the 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 rebuild that on Opus 4.8 because the finite amount of compute in the world is sloshing back over the 4.8. And even though they haven't technically EOL at 4.6, it 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 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, 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, we'll work for 4.8, but like, you want to start from scratch. If you want to get high quality, right? And so you're just constantly rebuilding. You're constantly rebuilding. And 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 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 deck is what I want. This works. And yet that thing, you'll have to rebuild every six months is almost the new thinking. I just want to make that sound a 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 do, and I'm seeing that in some of the products I'm building myself is I go, 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's efficient, effective, stabilize. You need the, the AI engineer experts. Yeah.

And the other interesting part is like 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. And 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 want to, you know, it's never been easier to build, but we want to focus on the things that are just became easy to build thanks to new release extra why. And so, you know, I think our AI team spends half their time just reading white papers and keep up today on the newest launches. So you can figure out great, what was hard last week that's now easy because that's the stuff. want to be building. That's that's the thing that I'm scared. How do you keep up? Like I you know, if you're a business owner sitting and you're listening, right, business podcast and you got a, you know, a small, medium size business and you're, you're just trying to make the business

exist, right? And work and you're, you know, and now you're having to deal with all of this AI. It's not just about adopting the AI. It's about adopting the 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 following behind, but still incorporate as much AI into their business without it being something now a full-time job. Yeah, I would, I think there's two, like, well, comparing us to, that, that scenario, I think is like comparing like a F1 racing team to kind of like, you know, me hitting the track on the weekend, right? So like, we 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, I actually think the market, it looks very different. And that like, you don't really, you could take the thing you built on Opus 4.6 and move it 4.8. It will 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. I think everyone, if you haven't had a chance to use an agent or like a Claudecoe or something and just start building something, you just got to get started. Like there's no, do not let the maintenance cost. Yes, it's there be at all impediment to getting started because you will be blown away by that stuff

you can do. I've talked to so many friends who are not technical who are now automating whole parts of 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, I barely can email and are yet like, hey, I built a swel operating system for my marketing team. It's my one, right? You're talking to someone here. Like I'm a sales guy, you know, traditionally a sales guy who turned into a business owner around sales who's now full on AI developer. I developed like four products. One of them

we're talking to big companies just under some NDA but like and it's kind of it's like four months ago if you said you're going to be doing this I would never believe it. It's insane. This is why I tell me 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 was out 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 past and he kind of just got fed up and looked at me straight in the eye and just said, hey, he almost was kind of 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 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 got to go and ask that. Literally ask, what does all in mean in AI? And then next thing you know, I'm seeing how it's working. You don't need a beast, like, you need patience, you know, and not to be

afraid to ask the question. So it's interesting to me because I feel like there's going to be a lot of these coming. I could be wrong. A lot of these, like a lot of companies are going to be coming out. And it's going to be a race to getting customers and a race to who has the best story

or marketing. But the products are going to be half ass and then there's going to be good products where the big guys are just going to gobble up. I just think we're going to 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-1 race team that are working on Sundays every day, you know, like you said, throwing out the engine.

Right. Well, and then, again, because we're kind of building platform stuff that other people can build on. on. I think for the for the small business like owner user type, it's never been a better time to be a domain expert because because the cost of building the software has gone down so much, it now means it's viable to build software in places you wouldn't be for. All sorts of niches or small verticals or very specific use cases. Right. Hey, look, I don't know everything, but I know exactly how these 20 farmers do their business and what they need to do. 10 years ago, you could, you've got to go raised 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 a 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 going to go build the f1 car for you're going to try to be one of these foundational platforms several else is used to build on but if you're just trying to solve a problem that you know like the back of your hand oh boy are you this is going to be a gold rush for you right Because if you have the expertise or yourself, you got those connections, you know the problems people have, you don't need to hire a 20 person team and raise $5 million to get off the ground. You can just get it done this weekend. And I think that's going to be amazing.

I'm going to leave it here because I believe we're saying the same thing. 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 visual. 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. I would 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 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 want to make sure you understand.

And if you are using meetings, if you're on Zoom, Google, whatever 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. Any last notes or any last thoughts? No, and it's mostly free.

So no reason I'll check it out. Yeah. You don't, like I always say, you don't got a $50 problem. No business in the world has a $50. problem. Again, Rich, thanks so much for being here. Appreciate you. Thank you for having it.

This was fun.