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In Otter Words: Sam Lessin | Otter.ai

In Otter Words: Sam Lessin

Otter Marketing14min

Ross Rubin

00:01

Hello, and welcome to In other words, a podcast that looks at the way people are making use of real time transcription. I'm Ross Rubin, Principal Analyst at reticle research and I've been tracking and writing about the tech industry for more than 20 years, continuing our focus on investors. Today, we're going to speak with Sam lesson of slow ventures, Sam first became known for developing a file transfer product called Drop IO, that was sold to Facebook. And more recently, he's been looking at ways to improve the performance of knowledge workers, which we're going to get into in a little bit. But for now, Sam, thanks so much for joining us today. Why don't we start out if you could please share some of the ways that you personally use otter

Sam Lessin

00:50

remembering to dues and remembering things get Donner's ideas or strategy ideas you have, or thoughts that come up, you know, I frequently will like just speak rather than type, and then share that with, you know, with a few friends or partners or colleagues, depending on what we're working on. And the nice part is, it used to be that speaking is faster than writing for most people. But listening is much slower rate than then reading. And so the nice thing about otter is it does great freedom of excellent translation of speech to text, but then also kind of with a hybrid approach of having the text plus the audio to refer to you basically make sure that it actually is faster for the person generating content and faster for the person receiving the content, to get to the key ideas and go and kind of get things done when it's kind of a memo style use of honor. And then you know, or like, you know, interview like you know, who's using that the ability to like so much faster, to to to, to kind of both speak and get a full full concepts out and then also be able to like parse out as tax jumps, the right points review was sad and use that as data. And then I think for the team use cases is like record over the your company meetings, etc. I mean, like, look, we've gotten to a world where what percentage of meetings are on Zoom, it's like so high among like tech companies, right? And that's because people are remote. That's because you know, people are dialing in, etc. And that's good. But the context is still lost, you still have to like, be there, and then everyone forgets what was sad. And so I think the vision is saying, Look, we're gonna get to a world where meetings happen, we don't have to have the same meeting 15 times, you know, context isn't lost, like, this is an incredible goal and dream, I think that, you know, kind of relies upon having great, both recording and then great speech.

Ross Rubin

02:40

Yeah, I love that dichotomy about optimizing both for the capture of the information through voice and the consumption of it through reading to really an interesting point,

Sam Lessin

02:52

if you personally, were just optimizing for your own experience, and no one else's, you'd probably always want to speak and read, right? Like, that's what you'd want, I don't want to like people are slow to listen to it. Like if you could just read, if I just had already said everything I was gonna say and you could read it, you get much faster through this and cut to the heart, we're much faster readers, usually his do more. So the problem is, obviously, we live as humans in a society where you can't just do what you want, right? You have to kind of also model to what other people want. And so you know, but we can have that.

Ross Rubin

03:23

I suppose one of the advantages of the reading is that sort of semi consciously, you're always kind of like looking ahead a little bit of where you are. And that's impossible to do with voice. So Correct. Yeah. Cool. You touched on some of the sharing and collaboration you do with with your teams, as well as some of the collaboration that other teams did forward, forward, forward, looking at companies as you refer to them or doing you talked about some of the benefits. But could you maybe talk a little bit about maybe more of the different kinds of scenarios. So for example, one of the different kinds of tasks we've seen, honor used in is kind of sales review meetings. So it's easy for the team to capture the kinds of current issues that may be happening with a prospect pipeline, I imagine. CRM kinds of applications are another one. Any other kinds of tasks that that you're seeing in that vein? Yeah, I

Sam Lessin

04:32

think there's what I call what you're describing as coaching. So if you think about it, there's a lot of people who have interactions externally, you know, that can be salespeople, or BB conversations or whatever. And, you know, especially in fast paced environments where things are changing and there isn't a one set script, but there are goals and people are trying to improve. You know, it's it's one of those things where like, I actually spend a lot of time within the company I'm building called sin but like, the upshot is is like knowledge workers in general it gets the worst coaching You're on a sports team, or you're, you know, doing a job that is in a more, you know, manual like or you know, manufacturing, whatever. It's like, there's data, that data lets you be coached, right? If you think about how most knowledge workers are coached, what happens if you're, if you're lucky, you have a one on one and once every once in a while, and your manager or boss, ask you, how's it going, and maybe review some outcome metrics, but that doesn't really help you, if you're a salesperson, you're not closing deals, right? You're boasting like, close more deals, like hit the number doesn't really do much for you, you need help on the process. And the problem is, is that you can't have someone shadowing you all the time, right? It's just impossible. And so, you know, it's too inefficient. And but like, if all you do is say, hey, I can record everything, and then get feedback on my process. Right? That is like, hugely valuable. And I think that's definitely part of the future.

Ross Rubin

05:47

So you mentioned thin, I was actually a customer fan when it was more of a consumer facing offering. And I've had some discussions about the potential for tools like otter in this sort of personal assistant space, it really seems to be a very good kind of match. Yeah,

Sam Lessin

06:14

yeah, I use it with my assistants for exactly that is like, you know, as a part of what Finn, you know, did me know, Finn is a business, we started out with this thesis, which is the future of work of human plus computer for sure. And we built an assistant product because it forces you to figure out the broadest set of how do you create the, you know, the rigging and the routing acoustic work on what and and helps you understand and think about the workflows and how you build them customize the workflow. And then it also thinks about you the holistic systems, how do you create basically, like, industrialized is where I would think, right, like knowledge work, which is, you know, I would argue Ellenbrook is largely pre industrial right now. You know, we've moved that business up to the point of our coaching very much towards the biggest insight we had, which is, man, we have all these assistants, and they're doing good work. But unless we understand exactly what they're doing in their process, right, moment, by moment, click by click, you know, interaction by interaction, we can't possibly help them do a better job and optimize the overall system. And so we basically ended up building this very deep analytics, and like QA toolkit that other teams can use, right, to basically optimize any sort of knowledge worker, which could be, you know, sales and some kind of support, etc. I think, you know, otter is like a key input to that, right, in terms of like, that feature ecosystem where like, if you want knowledge workers in general to have coaching and improvement their jobs, and also you want great interfaces, where like, as someone who's asking for an impersonal assistant, I just want to ask for it, right? And I want to potentially give you a lot of context, as I'm thinking about it. But I don't want to have to, like, type it out, right? I just wanted to go, like otter was great for that. I have somebody to help me out in the nesting on the inside investing side of what I do. And, you know, I frequently just send him orders, you know, if it's anything done or to, you know, type up a note on a company or share something with someone or do something.

Ross Rubin

08:02

Cool. Cool. So, I'd like to switch gears a bit and talk about possible ways that technology could help coach people, even before they enter the workforce, because it seems like as a number of applications for students, for example.

Sam Lessin

08:17

I mean, I wish I'd had it right. Right. You know, it's so slow to like rewatch lectures, right? And even when you're rewatching, you know, it's interesting. So I'm quite dyslexic. I didn't learn how to read until like, third grade I had to do about flashcards because I couldn't sound things out because like, you know, that's part of what it was. And I think to myself, Man, if I had a tool that could have basically hybridize, spoken word, right, what I'm hearing with actual reading, that I think would have helped me a lot, both, you know, learning to read, probably, but more importantly, then when I was in class or doing an activity, it, you know, the reinforcement on two channels is super helpful for like, efficiency of, of knowledge acquisition, you know, watching a movie and putting subtitles on it. Sometimes people do that for when there's tough accents. You know what I mean? Like you listen to some of these shows, like BBC shows, and I know a lot of people would turn on the subtitles. And they're like, look, I mostly understand it. But if I really want to attend the show, it's good to have both streams of understanding. Like, that's clearly a better way to consume information you really care about.

Ross Rubin

09:21

That's, that's a great point. And one of the interesting things there is that even if the accent is so extreme are so pronounced that otter may not be able to do the dead on transcription out of the box. It's just one of those side benefits that I think you get by committing to the tool. So if you're in the habit of using the tool, then you're in the habit of recording and you'll you'll still be capturing that and can review it and send it to humans or whatever.

Sam Lessin

09:55

Yeah, I love that kind of call out about the company I really liked about their approach is There are a lot of companies out there that are working on obviously, you know, just speech to text and odor is more accurate by every test I've done, which is great, right? Like their technology is better than any other technology out there. But but here's the other thing that I really liked about the company. And the approach is it's honest. So if you go and talk to kind of people who are working on speech translation to the Microsoft and others on one of the bots, so you think like Microsoft or Google or whatever, they'll tell you that like, Oh, they're speech to text translation is 99.8%. I'll give you ridiculous statistics about how there's future haters like better than humans, right? And the reality is, I don't question the science, I'm sure that like, there's some slice of the universe where they're technically correct. But from a practical perspective, right, if you just had a transcript and nothing else, they're pretty hard to read, right? And so I like to honor like, Look, our technology is better. But also, we're hybridizing the consumption experience in a way that like we acknowledge the fact that like, if not perfect, right, and that means that like, you can still pick up and understand what's going on. Right, as opposed to companies that things that are overly technically there's like some hubris to it, but it's not accurate. But if you ask them, if it's accurate, they'll tell you it's accurate. You know, it's not like, okay,

Ross Rubin

11:13

academically, academically accurate, right. But I love the point you're making about readability. Because, you know, having looked at a number of these transcripts, I would agree that the tool does a great job on kind of a word for word basis, or phrases or what have you. But there's still maybe some work to be done in kind of understanding what a sentence is, and punctuation, those other things that we kind of take for granted when we're reading, right?

Sam Lessin

11:41

Getting is like actually humans, if you listen to them, sometimes, if you like, just wrote down everything I said, it would make no sense. It seriously, it's like this, the thing is, like, so much of language is like in context. And we don't fully understand that, like, literally, there's a huge difference between structured with written language, which is meant for legibility and conceivability, and spoken word, which again, like if you just wrote just purely what I said, and the pauses I put in, it would be very confusing to read,

Ross Rubin

12:08

I wanted to maybe hear your thoughts on some complementary technologies that that you're seeing, we talked about zoom, when you mentioned the idea of someone coming back into a conversation that was recorded and viewing that transcript, I thought about kind of a Slack or, you know, Microsoft Teams kind of scenario where someone could jump in on the transcript. Obviously, a lot happening right now with language, real time language, translation, anything you're kind of seeing that you view as particularly compliment complementary in terms of evolving technologies.

Sam Lessin

12:48

I mean, I'm trying to, you know, come at, not directly. It's not that those things aren't important. I just think what's happening is that people are all sorts of teams are developing their own tool chains. You know, what I always like to say is, you know, people who think that the future of work software is in Microsoft Office Suite, you know, is sorely missing the point. Today, what we've done is we've taken technology, and we basically recreated a bunch of tools that we had that were paper tools that Hurray, ask yourself this question, which is in the future, will all of your work interactions be recorded, so that you can increase sharing, like, which increases productivity by getting people on the same page? And it gives you the ability to get coaching, like on the interactions and how to improve them more rapidly, rather than just spending your whole career doing it as it's done without any feedback? Or good coaching? Like, will you end up in a world? The answer is, in my mind, definitely, like, There's no way that's not the future? Right. And the question is, if that's the future, what are gonna be the key collaboration tools and products that bring you there? Right. And, you know, to me, otter is on the right path, for sure, which says, look, it is designed, you know, uh, you know, wooden voice and the national conversation at the center, but you know, fundamentally is building a collaboration platform. And that's exciting.

Ross Rubin

14:03

Definitely a lot to get excited about there. Very cool. All right. Well, that's gonna wrap up our episode for today. Sam, thanks so much for joining us. If you'd like more information about fin please check out fin.com. For more about Sam or slow ventures, please check out slow.co You can find more about my company reticle research at reticle research.com. You can also follow me on Twitter at Ross Rubin. Or if you'd like to check out my Podcasts to get our take on what's happening in tech. You can do that at Tech spensive.com. And of course, check out otter on the web@otter.ai Follow the team at otter underscore AI on Twitter. And be sure to download the app from the Apple App Store Google Play if you haven't already for an auto words. I'm Ross Rubin thanks so much for listening

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