Scribe makes it easy to share how you do your work by creating automated documentation. Scribe raised a Series B recently and has grown to millions of users with enterprise customers like Gong, LinkedIn, and Shopify.In this episode, Scribe’s co-founder and CEO, Jennifer Smith chats with Sandhya Hegde about Scribe’s early days.

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‍Be sure to check out more Startup Field Guide Podcast episodes on Spotify, Apple, and Youtube. Hosted by Unusual Ventures General Partner Sandhya Hegde (former EVP at Amplitude), the SFG podcast uncovers how the top unicorn founders of today really found product-market fit.

TL;DR
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Years before starting Scribe, while she was at McKinsey, Jennifer observed how top performers at companies worked differently from the processes laid out in detailed binders and onboarding manuals. Documenting these and retraining the entire org was a common consulting project.

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Scribe's original vision included automation but early customers told Scribe that the most valuable part for them was the workflow documentation itself, not necessarily automation. Scribe decided to focus - shipping updates faster and getting rapid feedback and adoption from a broad set of users.
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Noticing viral adoption and sharing, Scribe pivoted from founder selling to a bottoms-up, PLG motion to get the product in as many hands as possible quickly.

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Sandhya Hegde

Welcome to the Startup Field Guide where we learn from successful founders of high growth startups how their companies truly found product market fit. I'm your host, Sandhya Hegde, and today we'll be diving into the story of Scribe. So Scribe makes it really easy to share how you do your work by automatically creating the documentation around it. They recently raised a series B round and have grown to millions of users with enterprise customers like Gong, LinkedIn, and Shopify. Joining us today is Jennifer Smith, the CEO and cofounder of Scribe. 

So you started Scribe 5 years ago now. I would love to go back to that moment and really‌ dig int, how did you and Aaron end up starting this company? What were your experiences that kind of gave you the motivation and maybe even the insight that eventually led to Scribe?

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Jennifer Smith

So I'm gonna tell you the story, but I'm gonna caveat it with one of my favorite Steve Jobs quotes, which is you can connect the dots, but only when you look backwards. So I'm gonna make it sound like it was this wonderful predestined thing that we were gonna find each other and solve this problem. That is not how it felt at all as I was living my life. I think if you were to go back and tell me at the start of my career that I would be doing this today, I probably would have laughed at you. I started my career at McKinsey.I spent 7 years in the ops practice there, working mostly with financial services firms and tech companies. So that's a long fancy way of saying  200 days a year on a plane, going to places like Salt Lake City and Tampa into these really big operation centers, and trying to figure out how to make them more efficient. Not the most glamorous work, but it actually drives a lot of impact for clients. And you learn as a consultant, the name of the game is you find the best person in the ops center, you befriend them, and you just ask them, why are you better than everybody else? And they would pull out a really thick binder. This was 15 years ago. Okay? I'm dating myself. They'd pull out a really thick binder with laminated pages of step-by-step guides. And they would say, I was told to do this, to memorize this. That's not what I actually do. I found these 50 better ways instead. And so we would pull up a chair behind them, we would look over their shoulder, and we would write down what we saw them do, and we'd basically generate a new binder.And we'd give it to the leader of that ops center. We'd say, here, if you can just get everybody in this center to do this set of processes instead of those, you'll raise the performance of everybody. That was kinda the state-of-the-art best practice. And I sort of filed it away in my head and said, like, gosh, what a shame. Someone will obviously do something, some day. And I kinda moved on with my life. And then I found myself in venture, and we obviously talk a lot now about how to sell software, but I got really curious about why people buy software. Maybe it was the former consulting entity. I've kinda just always loved enterprise customers, understanding their psyche. And so I interviewed over 1200 CIO, CTO type folks, and I would just ask them, like, what problems are keeping you up at night? Like, what do you wish VCs were investing in? What do you have budget for? What are you seeing today? And I kept hearing the same theme come up over and over again, which is I have all these people who show up to work every day and their fingers on keyboards, 9 to 5, like typing, doing work. I have no idea what they're actually doing. All I can observe is the input and the outputs. And that kinda institutional knowledge walks out the door every day at 5 PM, and I gotta hope it comes back, and I have no way of solving this. And so I kinda flipped from saying like, gosh, someone should solve this someday to, like, why is nobody solving this right now? And I just became really obsessed with this problem. I had a professor in business school who said once, find the thing that you're always apologizing for about yourself and find a way to make money off of it. And for me, I'm just obsessed with efficiency. Like, it just, it like upsets my core to see waste and something happening in an inefficient way. And so this is a problem that I've just been‌ mulling over for a while. And I looked around and was like, okay, great. Let me go find somebody who's solving this problem in the right way, and let me go join them. And the kinda quick TLDR is I I didn't see anybody doing it the way that that I wanted it to be done, or I didn't think they were solving it in the right way. And so we ended up starting a company.

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Sandhya Hegde

 How did you meet Aaron? How did you know it was the right time, right place to, start something, or were both of you excited about the idea? Like, how were you thinking about evaluating who are the right people to start the company with?

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Jennifer Smith

I feel like so many stars have to align for a company to get started that I sometimes look back at the the founding of Scribe, and I'm still just incredibly grateful and amazed that the stars aligned for us for this to happen. It kinda felt like sort of a snowball at the time where I looked at it and said, this is what I wanna be doing. This is what I would wanna build. We got some very early technical resources from a few engineers who said, like, hey, we'll kinda help you out with this. I had an early customer who was, like, if you build this thing, I'll actually use it.

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And so in many ways, I almost started a company without realizing that was happening at the time. I was just like, ah, okay, great. Like, you want this thing, and you're willing to help me build it. And so, like, let's kinda connect this together and make this happen. I call meeting Aaron, one of the greatest fortunes of my life. Aaron's my cofounder, and he is an incredibly talented engineer and product builder, probably ‌the fastest that I've ever seen. But he's also just a a gem of a human. And I think that's incredibly important, because I spend more time with him and now our broader team than anybody in my personal life. And it's a huge source of joy to me. So I'm just gonna put that plug in there for anybody who's thinking about cofounders and early teams.

Like, it really matters. And a huge source of motivation for me ‌in building this company has been, you know, doing it with him too, and and just, you know, wanting to see him and our team win. But that's just, a side note. I had gotten introduced to him through the former talent partner at Greylock, who I'd worked with before. And, I had been kinda thinking about this problem and starting to build, and Aaron was just starting to pop his head up.

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He had sold his last company to Google, and I think had lasted 18 months there, and he was getting the very serious itch to get back to building. And so when I met him, I think he got excited about problem space. I I got really excited about him. I met him. I ‌think I interviewed over 80 people, to join. It was kind of early engineers. I stopped counting at 80. Let's put it that way. There there probably were more than that. And when I met Aaron, I sort of instantly was like, it’d be fun if we did this thing together! 

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Sandhya Hegde

What was your articulation of the early product you set out to build with Scribe? I'm curious, you know, how closely that matches what you‌ ended up getting early customer adoption for.

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Jennifer Smith

 The quick answer is that it's about 50% of what we have today, but very aligned in that 50%, and the other 50% no longer here. So we originally set up with saying, gosh, all of these people are spending this time using software at their computers, and they're doing it pretty inefficiently because they don't automatically capture what they know how to do, And then what if we could also build an automation that replicated what we saw them do? And so we built that, and we had early customers, and we had some success with it. But we had two things happen. One, we had customers say to us, pretty clearly, like, hey, actually, the most valuable part of this 2-thing that you're building for me is that early part. Like, ‌automation is great and good, and, and I'll take it if you've got it. But like, you helping me understand how my people are spending their time, like, that's really valuable to me. And the second part was they voted with their feet which is they would use the first half of that software and, like, not the second. They were  like, can I just keep the documentation piece? And I don't really care about that automation thing. And so that was, I think a really‌ humbling, but clear realization for us that it wasn't the whole shebang together necessarily that was adding the most value. It was really even, you know, just that first piece. And so we said, gosh, we've gotta get a lot more signal pretty quickly on what people are ‌ gonna use this for, what this looks like. We have a whole bunch of ideas, but we could be very wrong.

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How do we get the tightest, quickest, highest signal feedback loop? That was the thing we solved for. And so we said, gosh, we gotta get this thing out in the world, and we're just gonna release it for free and see what happens. And so we releaseda very early version of Scribe, on Product Hunt. They say if you're not embarrassed by your first product, you spent too much time on it. Especially looking back now, we are hilariously embarrassed by it. Like, it wasn't connected to the Internet. It was designed entirely by engineers. I mean, it was a very kinda clunky MVP at most version, especially when you compare it to what we have today. We just put it out there.

And it was pretty cool and interesting to see. I think in the first couple of months, we had, like, articles written about it in, 15 different languages. We would see kinda just the downloads come in every day of users but then also sending us notes, with lots of feedback. I mean, some people pages of notes, and I mean, rightfully so. It was a very clunky product to say the least. Wasn't even really a product at at that time. But it gave us enough conviction to be able to say, gosh, we're gonna drop the preconceived notion we had coming in, and what we thought this business was gonna be. We're gonna really listen to what people are telling us and what the users are saying. And even though these numbers are really small right now, in terms of number of users and things like that, like, we just felt like there was signal here. Like, you can feel market pull. And the thing that I continue to say today to our team is finding product market fit, it should not feel like you're pushing a boulder up the hill. If it's really effortful, like, then you're not on a steep slope. You know? And what you wanna be doing is finding a steep slope where it feels like it's being pulled out of you and the market is pulling it out of you. And so we oriented very much around how do we test the slope of this hill that we're on right now and do that as fast and quick and most efficiently as possible. And then once you feel like the boulder's starting to go down the hill and pick up momentum and freaking run after it as fast as you can.

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Sandhya Hegde:

And walk me through the timing. So, you know, once you started the company, how long did it take you toget that first Product Hunt launch out there, and when you started looking at the early adopters after that first launch, what were any surprises or learnings, for you from it of who you thought would be using it versus who was actually using it? But, yeah, very curious about ‌ the timing of your first product launch or, you know, maybe the first Product Hunt launch and then the more mature GA product. Like, how long did it take you to get there in your early days?

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Jennifer Smith

 It took us about a year maybe from formal founding to the first launch of the MVP of Scribe and what it is today. And then, you know, from there, it was a constant iteration. And so there's no clear milestone I can point to after that. But I would say after we did ‌the basic GA of Scribe, it took us a few months still to start to get signal from people using it because it's not like we had a marketing team or a way to get ‌the word out there. Right? And so it was really just organic word-of-mouth. And what we were looking for was not the absolute size, because it was small. Right? We're talking about, like, dozens of people a day, at most in the early days. And so we weren't looking for size. We were looking for momentum and what the trend looked like over time. And so we‌ watched it for a period of a couple months. We set a date for ourselves‌ and we were like, by this date, here's the trend we would have wanted to see. Here are the signals we would wanna see in usage, in feedback, ‌in buzz, in momentum, and excitement. And we said if we hit‌ this milestone, then this becomes the crux of the company. And what we're gonna be doing, we're gonna drop this whole automation thing. We're gonna completely reorient. Right? And it really was ‌kind of a ‌defining moment for us. We didn't hit the milestones that we said we wanted to hit and be able to see. But when that date came, we looked at each other, and we were like, you know, we still believe in this thing. Like, we may not see the numbers on paper, but, gosh, like, I just feel it. Like, I'm feeling the pull. I'm feeling the excitement from customers.

I'm feeling their frustration with how limited our product is today, and that's a good thing. If they're calling you up to tell you how bad you're, that means they care. That means you're barking up the right tree of a problem ‌that touches people. And so we said, well, we didn't actually hit the numbers, but we're gonna go ahead and do this anyways. And so we made‌ a just a pretty hard-line in the sand decision of this is what the company is gonna be going forward. And people always say we never looked back, But truly, we never looked back. It was that line in the sand. Like, I remember it. It was August 31st. That was our drop dead date, and that was it. August 31st, starting September 1st, never looked back.

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Sandhya Hegde 

What were some examples of the feedback you got around your product that was surprising and memorable for you?

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Jennifer Smith

A lot of it was, pretty obvious, in terms of, like, the content of the feedback. The thing that was‌ surprising to me was, ‌in a pleasant way, just how passionately people felt about it and how detailed the feedback was. I mean, we'd literally get pages from some random person I'd never met, you know, who lives halfway around the world, who, just happened to stumble upon our thing from Product Hunt or, like, some friend had told them about it or something. Right? And just kinda seeing, like, the level of‌ pain that they were describing.We had assumed it was there, but I think seeing it on somebody's face or reading it between the lines and, like, the very long detailed email that they send you is really, like, the signal to be looking for. I think when you're trying to find product market fit is, like, have you really hit something‌ deep? And so the things they were asking for were incredibly reasonable and typically pretty obvious. Like, I wanna be able to edit this thing. I wanna be able to share it as a link on the web. I mean, these are really fundamental stuff because our product was so basic when we originally released it.

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Sandhya Hegde

 Got it. And, you know, how did you‌ start analyzing who was using the product? Like, once you had some critical mass, how did you think about, like, okay, who is our customer profile? What can we take away from the early adopters who are using this? So I'm curious kind of what your learnings were at that time and then how they have evolved over the next 4 years.

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Jennifer Smith

One of the really interesting things about Scribe and and the problem that we're solving is it's a very human problem. It's an incredibly universal problem. Like, anybody who's at work and has to use software and work with another person is a potential user. And so, at the beginning, we were like, again, we've got thoughts on who might use this, but we don't really know. And so our attitude was let a thousand flowers bloom and see where our users will direct us. I think what we assumed we would see were really strong pockets of particular functions or industries or something. And what was interesting to us is we didn't. I mean, we really saw that it was incredibly horizontal and this is still true today. Everyone from‌ your, single local accountant to fast growing startups to Fortune 100 companies. And the advice that we kinda got in the early days, and even a bit beyond the early days was, well, maybe that's a great thing for TAM. That's a really bad thing for you in terms of trying to find product market fit, becaus, directing your efforts against an IC, because you can't be everything to everybody. To pick one. And we thought about it, and we‌ tried. We sometimes would sit down and be like, okay, well, so many smart people have told us we should just pick a few ICPs, and really go hard at it. And there are a bunch of, you know,‌ early lore stories about other horizontal products that picked a few in the early days and really focused on them. So we tried to study those and understand what they had‌ got out of it. And so we sort of forced ourself to the table to say, like, let's pick a few. And we could never really pull the trigger with any degree of conviction because it just wasn't what we were seeing and feeling from our customers. And so we‌ avoided doing any concentrated ICP push, and instead said, we're really gonna build for the problem set. We're gonna be very opinionated about the problem we're solving. And we're very opinionated about the way to solve that problem, because we've now talked to enough customers and understand what their workflow looks like.

But we're not as opinionated about who you are because we‌ think this can show up in many different ways. And so it it's very contrary to the advice. And I think the way that I hear almost every other company has gone to market. And it was so extreme that I had investors and just kinda people who I think wished the company well and had been around Silicon Valley for a while who would tell me, like, you can't do this. This is not gonna work. And I kinda said to them, like, watch me. I think it will.

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Sandhya Hegde

Right. I think, you know, it's really fascinating especially given it's also a collaboration problem you're solving. There's a vitality to it as well. Feels like there's a lot you could potentially be learning from consumer go-to market, which is by definition, more horizontal, less vertical. I'm curious, like, how would you articulate go-to-market strategy, especially given that you are choosing to not go an ICP route. You're going for the horizontal, and  there have been other companies that have succeeded with that as well. How would you articulate your go-to-market strategy over the past few years?

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Jennifer Smith

Yeah. Since we're talking about the early days, this is another kind of important difference. We had originally started off selling top-down, enterprise sales. I love a good enterprise sale. I just I love that motion.I love talking to enterprise buyers. We got a lot of pull and interest pretty early. Like, it just it made‌ a ton of sense. But remember my point earlier, I was like, we need to get fast In enterprise sales, you know, those can be some pretty long sales cycles. And when you've only been around for a few months as a company, waiting 9 months for a deal to close is like an eternity. And then you gotta wait for people to use it and activate all these sorts of things. And I think at the same time, we realized too that this kind of very much lends itself to a bottoms-up product. But we really came at it from just how do we get this in the hands of as many people as possible and learn as quickly as we can and validate a bunch of the hypotheses that we have.

And so we shifted to go to market as kind of a classic PLG company, like, very bottoms-up and then creating on-ramps for people to self-select into a self-serve funnel or into sales. And that was another really big unlock for us as a company very early on because it meant we now had, exponentially more people who had their hands on the product every day and who were using it and not just writing us the really long emails with the feedback. But, now we could see product telemetry and see where they were voting with their time and their feet, and what features were being used, and what the funnel looked like, and all the kinds of things. I mean, you've come from Amplitude. Like, you're familiar with this. All the kinds of things that you would then start to analyze. And so our learning just exploded, with that decision, following users and value from the product and all those other things.

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Sandhya Hegde

Got it. Makes sense. Well, you know, maybe switching gears a little bit to, like, the ecosystem. Now you're building an automation startup, even just automating the documentation process and not, you know, the actual steps. That was the second half of your original vision.

You are building an automation startup at a time where, like, the state of the art in AI tech just shifts beneath our feet every month or so. How do you and Aaron think about product strategy in the context of, new breakthroughs, model improvements, AI agents? Like, how do you as a, leadership team stay sane and keep your strategy aligned to what's happening outside?

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Jennifer Smith

It's like an incredibly exciting time to be building. I think when Aaron and I set out 5 years ago to do this, we just we never imagined that we would have the tools that are available to us today to be able to solve this problem. And, it's changing seemingly, it feels like every week, sometimes even every day. Last couple of days, there's been some really exciting announcements that have come out. And so we think about it as like, gosh, our vision and mission is unchanged. But now we have way more powerful tools at our disposal. And I think there's some interesting things we can do to contribute to kinda the state of the art of that as well. And so we invested in that from an engineering perspective also. But, like, does this mean we can be more ambitious? Or realize our original, kinda goal and aspiration sooner? And so it's, incredibly exciting. And I think it's such a privilege to be building in this particular era, just given everything what’s going on. And I think we'll look back on this time in the way that we do the birth of the Internet or cloud or mobile. I think anybody who claims to have a crystal ball right now to understand how the world's gonna look in 5 or 10 years and exactly how we're gonna use this is maybe a far smarter person than I am. So I think there's a ton of uncertainty, but you know what startups thrive in? Uncertainty. And uncertain times and ambiguity and moving targets. That'swhat startups ‌are built for, and that's in many ways their competitive advantage. And so, you know, if you're a technologist building in this time, I think you kinda just have to be excited. I don't know how you could feel anything else.

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Sandhya Hegde

And how do you think about that second half of your original vision today with, all the new superpowers that tech infrastructure is giving you?

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Jennifer Smith

 Yeah. I mean, certainly, the promise of having a high-fidelity automation is much closer now than it was back when we were building. You know, RPA was‌ the state of the art at the time. And there's a lot there's great things that has done. There's a heck of a lot of limitations to it as well. And I think there are many things that are interesting about what's going on right now. But I think one of them is thinking more about what does a human interaction component of it look like? If you think about RPA, for example, a lot of it was just sort of under the hood. You know, it's mostly unattended automation. Like, you're doing this thing, not a good use of your time. We're gonna have somebody code up a bot and just take it away from you, and then you never have to see it or think about it. And those end up being, pretty low-value tasks. Now, maybe they're done at incredible volumes, particularly in really big companies. And so the cumulative value is quite high. But the value to kinda any individual worker, maybe it just means you didn't have to do that annoying thing. You know, now, we look at our users, and and even, was it 9 months ago, we surveyed them and asked them, how are you using AI tools like ChatTPT? And, a very good percentage of them were using it daily. And this was a while ago before we even had some of the advances that we've got now. And so I think it's radically changed in how much it's present and at the forefront of what it means to be a knowledge worker, sitting down at your computer to do work and the tools that are available to you. And so that's a very different paradigm. And I get quite excited about that because the crux of Scribe has always been about how do we make it so humans spend their time on human tasks, on high value tasks. And how do we help humans be better at the things they do, at the things that are uniquely human? And that's really what, AI and a lot of the assistants that we're seeing now are geared towards. And again, I didn't think that I would see that this soon in my life. And so it's just, like, incredibly exciting for me to be, like, at the helm of a technology company that's trying to think about how to make the lives knowledge workers better and to have these wonderful gifts dropped from the sky that we can now build upon and improve upon based on what we see.

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