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

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. Thatham is now the top rated AI Noteaker 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 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 a quite a bit, and I'm excited to have you here, but for the listeners that may not know, tell them who we are, Richard White is. I'd like to think I'm a product designer and kind of technologist.

You know, no one's looking right code of production and 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 of startups.

I've worked the first batch of white commentator.

If I want to date myself, they're probably before this called user voice, but as you kind of alluded to for the last five, almost six years and spent working on Fathom, which is the number one kind of rated on G2 AI note ticker for people and 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 at yourself who love 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 switch, and now I'm back to Fathom,

and I'm, you know, I'm max, I'm sold. Like, it's like, it's, to me, it's, I find it's the most easiest interface. It just, the usability of it, and I love that. I just feel like it's not overbuilt. It 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 saw something way before.

That's what I'm interested in. Like, the vision and the strategy you saw and how you brought 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 down 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?”

I've got 20 minutes, I was back to back to like, interview someone, demo something, get their feedback, rinse and repeat. And it's kind of those things where like, you know, if you run into a problem one today, 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 know, I need to fix this, right? And so, you know, I remember just kind of, to kind of think of how kind of crazy it is the way we kind of share an all-in chat of like meetings and stuff, right? It was like, oh, I meet with someone at this great experience to tell

me some really interesting quotes, facts, or whatnot. And I heard we scribbled down notes and then tried to like, clean them up with meeting and remember exactly what they said. It's a very stressful situation, right? It's like being a courts photographer, right?

And also being the lawyer, could I interview you in the personal and 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.

And it's also like that we're like a really poor artifact. I share them my team and a lot got lost.

You know, I'd have this amazing conversation, I'd share the note

“with my team and they kind of struggled with shoulders, okay?”

Right? So I just want to look at this, because there's something, don't we have the technology to fix this at this point, right? And 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 right in the sales space,

I could be like, "Gog" and stuff like that. And they're really expensive and they're kind of mediocre, right? It's like a, it took you of 30 minutes an hour to get the recording afterwards. It was mostly just a transcript and all sorts of transcripts. When I wanted it, it was just like, I got off the meeting.

There's instantly some notes great. 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? And we kind of took our hypotheses that really got us excited.

It got me excited about what turned in the bottom. And that was transcription in five years ago,

Um, some three to four dollars an hour to transcribe content. Which doesn't sound like a lot, but if you imagine, if you build a product and transcription, don't product and meetings, people are easy going to do 10, 20, 30 hours a month on it.

“Gosh, you're hard costs for that product are already like $50 a month, right?”

So, the fact that Gog and Fuchsia got were charging at $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 this is kind of commodity."

Like when we try a bunch of vendors, like kind of made all a prototype, and try a bunch of vendors like Amazon and Google, and I think we're just called Rav. That's like, these are all pretty good.

They're not great, but pretty good. So, at the time, Popsis, like transcription costs will go to zero.

Because they're all good enough, and it costs always turning down.

We think they'll go to zero. And more than 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 way of quote-unquote AI companies, like 2015 to 2020, that were terrible, right?

“Yeah, promised you the world, and delivered almost nothing, right?”

And so, but we're, 'cause I was like, no one wants a transfer. I don't want to get off a medium-grade transfer. I don't want to read anything to do with a transfer. But the AI will need a transfer to do all the fun stuff

I think it could do in the future, right? Your notes, write your actions, fill in your CRM, find trends, find themes, or work me with certain things happening. All that stuff needs it really good, high quality censorship. So, we started on the company with those two ideas and said,

gosh, if those two things are true, transfer to Costco Zero, and AI gets really good, could we be the first people to give away this part for free? Right, in those space where people are sure you're hiring $3 a month, what would you give away for free?

Because we actually don't think the values in the meeting itself. It's in building up the state-of-based, then you build which AI features on top of.

And so, we always have to see so we're going to give away

this part for free to individuals with the hope that gets us into a bunch of companies where we can then tell 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 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 a deadline that's hooked three times. But I don't have time to sit and listen to every meeting. Right? And so, I got really excited about spaces

because one kind of fit the hypothesis of where I thought the world was going. But two, I had this really awesome kind of two-sidedness to it. One part where you can give away a lot of value for free. If you're okay about that, you don't have to like charge people later, because there's just a nice kind of complementary business

built on top of that for their managers. That's kind of how we got started, right? And it's kind of funny to mention that we were kind of ahead of the curve,

“and I think that's probably true, because we had a third corollary to this hypothesis,”

which was, if you wait till when transcripts cost is zero and AI is really good, you'll be two to three years to start this business, right? You have the kind of obvious to everyone, and everyone jump in, but like any technological revolution, the best companies like build towards the hypothesis, companies out, and they do all the other stuff, right?

If we spend two to three years building all the foundational work, and the product experience that you talked about, the good user experience, the good usability, the reliability, the 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 a tooth there. Then, so when you guys were doing the hypothesis, like this was like in back in 2021, COVID days, I don't even like to use that word, I have to say I feel like we just don't use that word anymore. I don't know, I don't use, I hate using it.

I mean, it's funny because sometimes my brain, I keep thinking, oh, it's only a couple years ago, but I know, it's almost six and a half years ago now, like, you know. So today, there's a lot of players in the marketplace, but you've had the market share.

So are you seeing competitors coming in and taking over? Are you guys adapting your product now more with AI? How are you staying in the trends, 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?

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 do so talk, I show my revenue graph. You could see the point where AI actually shows up. And for us, that was kind of like GPT-4 level of AI.

That was a point where the AI could write better notes to the 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 your 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

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 with this prospect. And we can surface like risks, we can surface trends, so to speak.

And now the state of the art is moving to, oh no, now we can actually look across every meeting you've had for four to 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 column because we just assume that it's a 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.”

Now we're at this point where that actually works. So we can be like, hey, we got a new engineer and they're wondering about why we built this system in 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, yeah,

10 minutes. So I think it's pretty cool where 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 we think meetings actually fun? One, we remove all the work, right? So like, you don't have to be a starter for, but also, you don't have to get off in meeting and then have more work than when you start it, right? I think that's where this is going, it's like, everybody hates meetings today.

Even if a great meeting, I still have done the meeting. I'm like, crap, now I gotta go do all this stuff we talked about. We're not too far away. You get off that meeting in two terms of it's already done. The emails drafted, the fall of the schedule, you know, the, the, you know,

the presentation we went to build out is already stubbed out. Maybe it's even 80% built, right? So like, one is this kind of magic I've just speak things into existence on meetings.

“And then the other thing that I think we're going in where the space is going”

is kind of like information finds you. So the other thing people have made about meetings is they're in a building of them, right? They're in their sort of their inability. They're in a building of meetings, right? Oh, and the building, yeah, yeah.

Yeah, we're all in tons of meetings, and it's because it's a good primary way we disseminate information at 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, as you go on sit through a 30 minute recording and read the transcript,

it's just done, right? And so, if one time you're in need on a meeting, well, shit, now you're going to be on that meeting all the time, right? I actually think there's 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 it's we talk about a project, they're related to, or we reference a customer that they're, they're a 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 was in every morning that's basically curated from everything's been happened there, or yesterday we'll happen today.

And it's telling you, hey, here's what this is 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 world.

“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, get back to building stuff again, right, and doing work. Is that what your work, is that what you're working on? Is that the, is that like, so is that a different company?

Or is that what fathoms? No, that's, that's our state of mission, right? Our mission is to like make meetings amazing by kind of continuing down. They are 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 will do it for you, right? So, we have API and CPL itself, so we can do some of those action for you. It's interesting because I was just thinking,

so basically, all these people, I just say all the different,

all the different departments, all the different rules, 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, 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, but 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 don't want to know any time or pricing discussion doesn't go well, or I want to know any time, there was a heated debate, you know, like an engineering stand-up, or it understands tone, understand semantics,

and it will compile all those clips together, and in a daily or weekly, it'd be like, okay, here's every competitor mentioned, and here's every pricing discussion that goes well, here's the themes of what these topics were,

that it can go fine to you, but you have to kind of declare what things you care about, right? Well, opt you into a standard set, but like, but I imagine where we're going to keep going beyond that, to like, not only do you just kind of explicitly say, here's the type of moments I'm interested in,

but yeah, I mentioned you just, you know, looks at the job title on your badge and kind of says like, ah, given you, and I know the project sure we're going to like, I'll go set up a bunch of these myself, right? Like, and I'll listen to all these trackers, and then all of some to the size

that we can put to you. So kind of like, kind of like, meeting notes themselves, I was like,

“I think we've got the V1 today, but I think where it's going”

is going to be kind of my boy. Yeah, I was just as you're thinking, as you were saying, and 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 are, you know, are people happy in the company? Are people's 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, you're engineering team. There's a, there's an issue here, like, right? And this thing's about to explode. Yeah, there's not a lot of folks speaking up that's, you know, very contagious meetings. There's a lot of stuff. And I,

I've got you mentioned to an outing, because, you know, we first got in this business,

everyone wanted to do just like, send them an analysis on transcripts. And I'm like, so much as well as when you don't have to. Right? Like, especially in business, right? And business is all about to, right? But back at an intelligence engineering, but I ran our sales team for a minute,

like I started up and, you know, tone is everything in sales. How, yeah. Yeah, they said they're going to buy, you play me that clip of them saying that,

“right? Like, you'll know from that clip, like, well, then 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 mentioned, yes, facial recognition, like, you know, how engaged are people and stuff like that, and 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?

Um, by employees, about a hundred. Okay. Wow. Okay. But we're also kind of, you know,

one of my internal goals is, I would like us to get 200 million revenue with less than 150 people.

Yeah. I actually have a lot. I think actually like, we're now in this era where you used to be that, you know, no one will stop by the revenue, no one's like going to be like, oh, here's where revenue added, here's where 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 percent sales team now to get

200 million dollars in revenue, sort of. 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 incorporating, 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 how many people say, it's still not there. Like, if you ever

had it, like, if you ever had it, actually ask whether it's clawed or clawed or gpd to actually do something, and it doesn't get a 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 in it. 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 can look at this, 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 place where, anyone can open the command line that's a clawed or gpd, 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, might be really intentional about which models you use in which order or whatnot, right? And so I think, like, or seeing as kind of the, you know, the clawed one in our great general proportions, 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? In this regard, there's

a general brain, it's good and 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 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 on the clawed, and I'm going to ask it some trying new questions. I'm like, you could do that, it will not succeed.

Here's your transcripts. For us, we'll get to the things that's talking about earlier, like, there's tracker concepts and be able to basically get 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, yeah, where 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, like, say, clawed and they give me the, you know, the feedback, but it's, but it breaks. And there's a nuance at misses, and, uh, and hallucinates.

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. And that was the one big challenges, you know, just even us kind of processing things like this was, you know, when you're asking questions like, hey, tell me every time there's a price discussion in this and go, well, well, how many of your meetings have that? Maybe 1%. Hopefully, hopefully, hopefully it's not like 20%. Right? Well, let's 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, uh, GPT-5 last year, um, was kind of viewed, I think commercially is like not a very impactful major release. But it was actually really important to us because the one thing they fixed in that release was hallucinations. They dropped hallucinations by 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 meal on the

“haystack type problems. And that's why the dropping your all your transcripts and card doesn't work”

is because one, the only really context window gets the less quality it gets, but two sometimes ten thousand means just not get 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 the process is enjoyable, right? Right? Yeah. Yeah. So it's funny to talk 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. Like, it was sauna. It's the speed at

which AI is being produced and building. I've never seen it before. No, maybe other. And I think

and I feel like people are like not like seen it. I try to explain to people like, 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. We don't 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 roles, 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, ten years? I mean, I think I need a couple shifts.”

I mean, one of my, my buddy Emmett, who's run twitch and that runs this AI, I can be called softmax. Talks about, I think this is a really good analogy where describes models as kind of like you know, sort of level of education where it's like GPT-3 was like a eighth grader, right? Yeah, GPT-4 was like a high school student. GPT-5, you know, like, you know, it kind of says like, yeah, 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. 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 this kind of

“world where we kind of think, you know, youth walls inherent the world sort of thing, but I think”

for a lot of us that have been in business for a while, just kind of 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, you need context, they need autonomy, they need like, you know, guard rails, but also not micro management. It's kind of this interesting doubt. 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? 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 dollar company with maybe two people, three people working in it. I thought of a lot of things to, yeah, yeah, so my my my goal of my goal was, okay, that's to be true and I do believe it to be true. Well, how many million dollar companies will have four, five, and whatnot? But I also see a lot of the big companies are still hesitant

on really fully adopting AI still in the 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?

to do an interesting these things because there really has to about their data being elsewhere

now that they can see the value, 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 and people thought. I mean, the thing you were just mentioning about, hey, there's a new model already 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 define an amount of compute in the world is sloshing back over the 4.8. And even though they have a technically EOL 4.6, it doesn't, you know, when you ask it a question doesn't work cuters in the time, right? And so there's this other interesting thing that we're doing is like, we're moving a lot off this front-tier models and onto open source models, not to save money, that's nice. But because like the basically upgrade life cycle on these things insane, right,

and they're not for a compatible thing you build for 4.6, we'll work for 4.8, but like you want to start from scratch. If you want to be happy about it, so you're just constantly to be 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 ready in 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 front-tier labs, some open source, increasingly more open source. But like it is not the building cycle has gotten

way easier. The maintenance cycle's gotten way worse. And so like, it's never easier to stand

up a prototype as well. I want this works. And yet that thing, you'll have to rebuild every six months as long as 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,”

to ask whatever it might be has never been easier before, but the ability to now maintain them is actually harder. And that's because 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 as I go, okay, I get why I need

an engineer team now. Like I might at that point where I can get it from like 0 to 5, but like you want to get it to the point where it's efficient, effective, stabilize, you need the AI engineer experts. Yep. And 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, if you like, oh, I want this thing to exist and you can kind of almost root for it. Like we've had a few

features where we spend 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 or it's like, oh, no, not only do we want to, you know,

it's never been easier build, but we want to focus on the things that are just speaking easy to build,

“thanks to new early sex or why. And so, you know, I think our AI team spends half their time”

just reading white papers and keeping 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 we want to be building. That's that's the thing that I'm scared. How do you keep up? Like, you know, if you're a business owner sitting in your listening, right? Business podcasts, and you've got to, you know, a small medium sized 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 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 feel like they're not following behind, but still incorporate as much AI in their business without it being something now a full-time job? Yeah, I would, I think those 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, 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 be 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 or the average business user, user, actually 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 and it will be as good, you know, 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 like a quad-co-worker, quad-co-code or something and just start building something, you just gotta get started. Like, there's no, do not let the maintenance costs, yes, it's there,

be it at all an impediment to getting started because you will be blown away if I'm not some of you could do. I thought just to me friends who are not technical, who are now automating whole parts of your businesses. Like, I've got friends that are salespeople that are building

and her yet like, "Hey, I had a small operating system for my marketing team." It's my book, right? So 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 like AI developer. I would have 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 kind of, it's like four months ago,

if you said you're gonna be doing this, I would never have believed you. 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 and AI? That's what I did. 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, you know, this was kind of like shut up." He's like, "Listen, you're other all in, or you're not. You make a decision." And I went home that night, and it was one of those things where you're just sitting,

sitting, burns, and burns. 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. What does all in mean and AI? And the next thing you know, I'm seeing how it's working, you don't need to be like, you need patience, 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 run. A lot of these companies are going to be coming out, and it's going to

be a race to get in 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 F1, you know, race team that are working on Sundays every day, you know, like you said, throwing out the end? Right. Well, and then, hey, okay, just we're going to build a platform stuff that other people will have to build on on. I think 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

software is going 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 are 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've got to go race $6 billion, go build it. Well, that market's not worth more than a couple of million dollars. Now, you go build that in a weekend,

and that's a very profitable business. So, it's now going to democratize creating software. It's like, you actually, you do need folks like myself and my AIT, if you're going to go build the F1 car for a good company, one is foundation platform, so everyone 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 a few of the

experts here is expertise or yourself, you've got those connections, you know the problems people have, you don't need to hire a 20% team and raise $5 million dollars 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'm saying it to people, like with AIT today, the only limitation is the mind is what you can or cannot see at

this point. There's nothing you can do or can't build or can't visualize or can't even bring

“to fruition that AIT 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, you know, you help podcasts, there's 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 ask me to do this.

I just want to make sure you understand. If you are using meetings of you are 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 for any last notes or any last thoughts. No, and it's mostly free. So, no, it's not checking out. Yeah, 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. Again, rich, thank so much for being here. Appreciate it for having this stuff. (dramatic music)