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

The Vault Unlocked

Fathom CEO Richard White shares how he foresaw AI's potential years before the hype, betting that transcription costs would plummet and AI would become powerful enough to transform meeting notes. His vision led to buildi

Key takeaways

• Fathom was founded in 2020 with two contrarian bets: transcription costs would drop to zero and AI would improve enough to generate meaningful meeting insights.

Transcript preview

Speaker 1 (0:00) 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 show. I'm excited to have you. I just, 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. I'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 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 white combinator. 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, and spent working on Fathom, which is the number one kind of rated on G2 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 note takers. And I've used Fathom before and then, you know, we switch and now I'm back to Fathom. And 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. interface, it just usability of it. 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 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 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 to 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. It's great experience. It told me some really interesting quotes or facts or whatnot. And then I heard away 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. And also being the lawyer interviewing the person on the stand at the same time. 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 that 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 just remember looking at this, me like, 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 two. that were doing call recording. Nothing with AI yet, obviously. Most of the products are in the sales space, 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 in the fathom. That was transcription costs would fall to zero, right? it's like three to four dollars an hour to transcribe content, which doesn't sound like a lot, but if you imagine building a product that uses transcription for meetings, people are easily going to do 10, 20, 30 hours a month on it. Gosh, your hard cost for that product are already like $50 a month, right? So the fact that Gong and folks like 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 very expensive. And so we kind of looked at 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, that was a very contrarian take, because it's hard to remember, but there was a wave of so-called AI companies from 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 to transfer. I don't want to get off a meeting and read 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 trends, find themes, alert 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 goes zero and AI gets really good, could we be the first people to give away this product for free? Right. And in a space where people are showing you $105 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. 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 was 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? Yeah. It's kind of obvious to everyone and everyone jump in, but like any technological revolution, the best companies like build towards a hypothesis a 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 of good usability the reliability the obviously the 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 in back in 2021 uh you know COVID days I don't like to use that word I think I even I hesitate to say I feel like we just don't use that one day more. I don't I don't use. I hate using it. I mean, it's funny because like, and 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