Why Entrepreneurs Must Trust Their IntuitionㅣRewind AI, Optimizely, Dan Siroker

Dan Siroker 0:00 So this April, we did

Dan Siroker 0:01 something kind of crazy. This was not a consensus good idea when we discussed it internally, which was we raised our Series A in public. I recorded, like, a seven-minute version of it, and I only, I think I only did, like, my third take and just unedited, put it up there, and it took off. It really resonated. We got two million views on social media, thousands of offers to invest, hundreds of really qualified meetings that came out of that, and ultimately an amazing lead investor in NEA who led our Series A at a $350 million valuation. So it all started actually with two really pragmatic concerns. One was... I'm Dan Siroker. I'm the co-founder and CEO of Rewind. At the beginning of my career, I studied computer science at Stanford, left Stanford to go started a career at Google as an associate product manager, and in November 2007, joined the Obama campaign. That inspired me to start my first company, Optimizely, which we grew from zero to $120 million annual recurring revenue, 450 employees. We sold that company, and that's when I started Rewind. Rewind is a personalized AI powered by everything you've seen, said, or heard. Our vision is to give humans superpowers, and we wanna do that by using technology to augment our biological limitations and using tools like Rewind to give you perfect memory. Uh, we're growing fifteen percent month over month in terms of ARR today. Yeah, so we've raised $33 million from great investors. Our very first investor was Sam Altman, and I pitched him on the vision for Rewind, and within the first meeting, he committed a million dollars of his own funding. The next round was our seed round, led by First Round Capital. Another round by Andreessen Horowitz. And more recently, our Series A we, was led by NEA.

Dan Siroker 1:40 Ultimately, what seems like successes were overnight successes, but it required a lot of pain, uh, to get there. The first idea and first company I actually started was after I graduated from Stanford. My research at Stanford was on predicting the stock market, looking at financial news. So I actually started a company. I mean, I don't know if I even incorporated it, but it was basically for a year after I graduated. By myself, I toiled away kinda building cool tech, and this is where I learned firsthand, like, the importance of distribution. It was also really lonely. Working on your own without a co-founder is very challenging, just the psychological ups and downs. So I actually spent a year toiling away kind of on my own, and then the drive to do that came from impact. You know, that's always been the driver about entrepreneurship for me, is how do I have the biggest impact? Made me realize, wow, I really should learn the skills necessary to be a successful entrepreneur. So I had this kinda misguided idea I'd get that from Google, so that's why I went to Google, 'cause I thought that would help me learn the skills necessary to be successful as an entrepreneur. And it was misguided because most of what I learned at Google was how to navigate Google. You know, eighty percent of the things I learned was how to be successful at Google. Twenty percent was applicable, you know, how to work with great engineers, how to cut scope, how to define and build great products. But I actually think the best thing I could have done back then is join an early-stage startup. You know, had I joined Facebook at the time, which was an early-stage startup, or even Dropbox, which, you know, I would've learned so much more what it takes to be successful as an entrepreneur because that's what your challenges are every day. In November of 2007, I was working at Google, and Barack Obama came to campus. At the time, he was third in the polls behind Hillary Clinton and John Edwards, and he had this vision for how to use what we were doing at Google, using evidence and data and feedback, and bring that to the government. And I remember feeling really inspired in that talk. The last thing he said when he came to Google was, "I want you to be involved," which is kind of a euphemism that politicians say to encourage you to donate to their campaign. I took him literally. I actually flew on a p- plane two weeks later, uh, to Chicago, where the campaign headquarters were, and I just said, "I'm, I'm here as a volunteer. What can I do to help?" And that's what led to this opportunity to do A/B testing and experimentation. It's things I had seen at Google, but bringing it to the campaign. And ultimately, that became a job. I quit my day job at Google, moved to Chicago, and, um, uh, was the Director of Analytics for his campaign. The role of analytics in the campaign was entirely new in 2008, and the reason why that was possible was because Barack Obama was third in the polls. The campaign manager, David Plouffe, had this mentality. He described it as the risk-reward mentality. He basically says, "If we just did everything like every other campaign, we would end up just like everyone expected, third." And so he had this mindset of, let's take some risks. Let's do things differently than every other campaign. A good example in, in 2007 when I joined that really made this mentality something the campaign embraced was we did an A/B test, and the A/B test was if you go to barackobama.com, at the time, the first thing you'd see was this very presidential-looking photo of Barack Obama asking you to sign up on the email list. And we ran an experiment comparing that in real time to a really compelling video, a video we were excited about. You know, it had snippets of his 2004 Democratic National Convention speech. We all thought that was gonna win, and we wanted to prove how smart we were by using an A/B test. And just kind of on a whim, we also included a few other pictures. One picture we included was a black-and-white photo of Barack Obama with Michelle, their two kids, very informal, sitting kind of on grass in, in this black-and-white photo. And it turned out that last photo dramatically overperformed compared to the rest. This photo actually did surprisingly well. It's the last photo that some, you know, white hair, grizzled political veteran would have picked. But, you know, in hindsight, you look at it, wow, that kinda normalized him as a, as a likable guy. It, it sort of showed a different angle to him as a candidate. And we did an analysis, and actually, that one change alone led to an incremental $40 million in donations from the email addresses that we got from that page. So that's just one example of how using data and A/B testing really helped inform the decisions we were making. One big lesson I learned from the Obama campaign is the power of A/B testing. You know, it's, it's not a new idea. It's really just the scientific method, but it's applied to the real world. What ultimately inspired me to start Optimizely, which was trying to build a product I wish we had in the Obama campaign to make it easy for anybody to do A/B testing. At that time, the tools we used on the campaign and those were, that were available online were very expensive. They required a developer to be part of the process. And so the insight we had from the campaign is like A/B testing is a good idea, it's just hard. So let's take a good idea and make it easy. And in some ways, that's been kind of the journey I've had on any product I've tried to build, is take something that's a good idea at its, at its foundation and democratize it, make it possible for anybody to do. So Optimizely at its start was really trying to build a product I wish we had in the Obama campaign to make it easy for anyone to do A/B testing. The way it worked was you took a snippet of JavaScript that we would give you, you put it on your website, uh, that URL never changes, and then you could run A/B tests directly in our visual editor. This was a breakthrough at the time because the alternative was every time you wanted to run a new A/B test, you needed a developer to be part of the process. The early hypothesis for Optimizely was that most valuable thing we could build was the lowest friction way for non-technical people to run a series of A/B tests. That the hypothesis was if we did that, we lower the friction, it would increase the chance that somebody does an A/B test, and then if they inc- they do an A/B test, end up having an impact. And so it came from this very basic idea that if the friction was high and the cost to implement was high, people just wouldn't do it. And if you don't do an A/B test, you're not gonna get the value. And it seems simple now in hindsight, but in the moment, the alternatives from companies like Adobe required huge professional service contracts, really sophisticated experiments. You needed lots of multivariate tests to justify the upfront cost of doing these experiments. And with Optimizely, we flipped it on its head. Like we didn't even actually support multivariate testing because we realized it's so much easier for a marketer to run a series of A/B tests and maybe some parallel A/B tests to learn, incorporate the winner, and move on than sort of upfront create this huge sophisticated experiment that's impossible to get statistical significance. So that was the thesis that we started with, and it w- it really worked well. I mean, that was the reason why building a product you wish you had is so powerful is that you have an intuition. Your intuition is the product you wish you had. This is exactly the product I wish I had in the Obama campaign to be able to very quickly run these A/B tests. So the distinct phases in Optimizely's growth I would describe as the 2010 to 2013 was really rapid growth. We were lucky to get product market fit very early, three years, seven million in ARR or something like that. And we raised our Series A, uh, led by Benchmark. Then that was a $28 million Series A. Then we raised a Series B not long after, a $57 million Series B and then a Series C. Just, and so we were just like growing, growing, growing. The next phase, I would say from probably 2013 to 2016, uncontrolled growth in the, in the team. I made the mistake of... It's one thing to, to h- raise more money than you need. You can... You should do that. If you couple that with the mistake of spending more money than you need to, that's really bad. And I think we got... I, I didn't do a good enough job as CEO in saying no. Hired these great, you know, head of marketing who says, "Oh, I need a demand gen person. I need a field marketing. I need, uh, events." And I'm like, "Oh, great. Like I hired you to be the CMO, so like go, go for it." I didn't have the constraint of lack of capital, and then I didn't have the discipline when we did have the capital to really make sure we were growing efficiently. So I think we grew far too quickly in terms of the team. Uh, we didn't need hundreds of people to do what we're doing, and that was a mistake. So I think we got too big too quickly in terms of the team. And then what happened was when you get to hundreds of people spending all of your time with sort of getting people aligned and just getting people to like march in the right direction, and I think that was also a mi- big missed opportunity. We kind of squandered the, the lead we had. We weren't moving as quickly as we could. I personally was pretty burnt out. I had been doing Optimizely, uh, for well over a decade, and in some ways after three or four years, I kind of fell out of love with the business. You know, we had actually solved the problem we had set out to solve, which is building a product that made it easy for anyone to do A/B testing. And I made the mistake in my mindset at that point to think that my job was to hire people better than me, empower them, delegate to them, and ultimately, that meant I'd spent a lot more of my time on parts of the business I didn't love. And I ended up spending so much more of my time in those parts of the business, a- and that just didn't give me as much energy as the product side. So most of my day was things that drained my energy. That was something that I wish I had done differently. You know, I looked at the time, I s- I saw folks like Lou Cerny at New Relic, who was famous for being this, you know, public company CEO who still codes. And I should have done that. I should have modeled myself after him, knowing that that's not selfish. You know, at the time, I thought that'd be selfish. But what I realized, the bigger selfish thing would be to fall out of love with the company. 'Cause when you do that, it's so much harder to attract great people, to retain them, to inspire them, and had I just been more focused on problems I was actually passionate about, I think we ultimately could have achieved much, much greater success. I'm proud of the outcome. I'm proud that we sold it, but it's only a glimmer of what we could have done had I still fall... Ha- had still had the same passion for the company 13 years in than I did three years in. The most salient lesson I learned from Optimizely is, is a pattern, and this is the pattern of things I regret most, and this is what the pattern looks like. My gut says we should do A. Somebody else says we should do B. We end up doing B for all the good reasons. It's a board member who suggested or an executive who we've hired, and then B doesn't turn out well. Uh, and those are the things I regret most, not because when I went with my gut things didn't turn out well. That's happened plenty of times. I just don't remember any of it. The things I remember most are when I went against my intuition, I didn't have the confidence in my conviction to argue for my intuition, and we ended up going down a different path that ultimately failed, and that's where the biggest lesson I learned was confidence in my conviction. I didn't realize that as a founder you have so many data points coming in through you from the engineering to customer voice to sales to just the, the market, the in- investors, and that helps you form this intuition that sometimes is really even hard to articulate. But when your gut says you should do A And you really feel like you should do A, you're, you're gonna regret doing B if it doesn't turn out well. So that's the lesson I've learned. And now with Rewind, I have much more confidence in my conviction. There are plenty of times we do A and it doesn't turn out well, but most of those are two-way doors. Most of those we can go back and change after. So I, um, I think that's the lesson I learned more than anything.

Dan Siroker 11:51 Yeah, so the first idea, the very first seed of what turned into Rewind was losing my hearing. And when I tried a hearing aid, there are two things that happened. One, I could hear again, which was amazing, but an equally amazing thing I realized in that exact moment was how I didn't realize how bad my hearing had gotten. It's this simultaneous realization of how great hearing is to these examples, like I remember I first had it in my ear and I would like rub my shoulder and be like, "That makes a sound." I would turn a faucet on and be like amazed, like, "That's a sound. There's a sound that's coming from that." And what that told me was clarity around what I think is a secret, which is that we all live our lives limited by our own biology. We all live kind of like a horse with blinders on, like we don't even realize what we don't have until you can feel it. That moment put me on this hunt. Now, it took 10 years to, to bring it to life, which is what are other ways that technology can augment human capabilities, transcend these limits that we have by our own biology, and give us superpowers? So the hypothesis when we started Rewind was that there are so many things in our lives that we forget, and that if we could give the f- users the feeling of perfect memory, that that would kind of change their mindset, and they'd be willing to, you know, record things, capture things for the benefit of having the feeling of perfect memory. We actually started very narrowly. We started on meetings. The first product and the first MVP we launched was actually called Scribe. It was a bot that joins meetings, it transcribes the meeting, lets you actually go back and see a recording of it. We did that, uh, launched that, and learned a ton. We were being asked all the time to go beyond just meetings. "Boy, I would love to be able to remember other things, not just the meetings I'm in." And that technology had finally caught up to the vision. So that's when we pivoted from what was Scribe to what is now Rewind, um, was this, uh, sort of this simultaneous confluence of hardware got good enough, Apple silicon in particular. We had learned that people wanted this product. We knew that being able to capture everything was far better than just meetings. 'Cause often the... what happens is you, you try to remember something, and you might remember a detail, but you get the source wrong. That ability to be comprehensive was kind of a thesis from the beginning. If we could be comprehensive, then we finally could deliver better on this promise of perfect memory. So often people think about starting a startup by looking at different categories and different markets, and they think, "Oh, how do I build a better mousetrap in an existing market?" And I think that's for some people. There are people for whom optimizing, incrementally making something better, is just how they're wired. Personally, I'm much more excited about creating new categories because I think there are so many things in our lives today that technology can ma- make better, and the ways to actually really have a 10X or 100X improvement is to build something new, not to build something slightly better than before. Rewind is an example of that. It is a fundamentally different way of approaching the same problem. And if you think about what is, like, the most common way today that people use to try to remember, the most common thing people do to try to remember, if you describe it, it will seem so anachronistic. The entire idea of note-taking is all rooted in this idea of trying to remember something better. And if you think about it that way, that you need foresight, you need to know what you might wanna remember later, you need to be able to search it, you need to be able to actually put effort into it. Our approach is entirely different. It's passive. It's capturing everything. It does it without being perceptible. It does it in the background. That's a way to think about it. It's like an entirely new category of note-taking, although note-taking is all trying to solve the problem of remembering better. We wouldn't take notes if we all had perfect memory. If you all had perfect memory, you wouldn't use Rewind, and so that way, that's the new category we're building, is the category of giving you perfect memory. The best advice I'd have for entrepreneurs who wanna start a new category is to focus on the problem, not the solution. It's very easy to fall in love with some sophisticated new technology, like, "GPT-4 came out. Okay, cool, now what problem do I solve with it?" It's instead, if you start with a problem, if you believe that there's a problem of people don't have perfect memory, then that problem is something you can solve by building entirely new categories. So I think you need to really obsess with a problem, really deeply understand the problem, try to look at the substitutes, like what do people do that's kind of, like, weird and broken today? Like I said, note-taking is kind of weird and broken. It's a, it's an inkling that there is a problem to be solved. It's just the status quo is so inept. Like, if nobody actually is piecing together products that exist today to try to solve your problem, then it may not be a real problem. Usually, the signs of a new market or a new category are people sort of gluing together things that aren't meant to be put together to try to solve the problem. There's this hodgepodge sort of duct tape and bailing wire to try to solve something, and the core of what they're trying to solve is a job. It's a job to be done. It's something they want in the world to exist 'cause they have a problem. And so that's, I think, my best advice. If you want us to create a new category, really think about the problem, and then let that lead the technology, not the other way around.

Dan Siroker 16:25 So this April, we did something kind of crazy. Uh, this was not a consensus good idea when we discussed it internally, which was we raised our Series A in public. Took our pitch deck, uh, I recorded, like, a seven-minute ver- version of it, and I only... I think I only did, like, my third take, and it was unedited, put it up there, and it took off. You know, it, it really resonated. We got two million views on social media, thousands of offers to invest, hundreds of really qualified meetings that came out of that, and ultimately an amazing lead investor in NEA who led our Series A at a $350 million valuation. And so it all started actually with two really pragmatic concerns. One was we had such an opportunity to build trust with users by being more transparent. You know, our product is different. It's new. It's a new category. At first blush, you sort of ask, "Okay, well, what happens to this data?" And, and people are concerned about privacy. "Well, what about this company? What if Google comes by and buys this company, and then all of a sudden I'm gonna get targeted with better ads?" And so we really wanted to start with, like, how do we build trust with users, that we are a going concern, we're a business that's gonna be around for a while. And then simultaneously, I was getting hundreds of investors reaching out to wanna meet, some of them very important luminaries. I just didn't wanna, like, blow them all off. Said, "Okay, let me just create a video that I can send to all of them, and while I'm at it, why don't I just put it up on Twitter and see if that actually gets trust from users?" And that was kind of the two data points that led us to actually publishing it. In hindsight, like, why did we even do that? We had three years of runway. We didn't really need the funding. But we got from three years of runway to six years of runway, which is even better. Right now we're growing 15% month over month, uh, in, in annual recurring revenue, and the primary source of that growth is word of mouth. I think building trust with users, especially as a startup, is critical. Users, especially early adopters, they wanna love your product. They wanna love your business. You probably are solving a problem that's so m- that matters so much to them, but they also don't wanna get screwed. They don't want their data to be sold. Uh, they know that startups might get desperate and do things that ultimately are not in their best interest or their users' best interest. So if you can assuage those concerns by being transparent, that goes a long way. And every time I've done it, every time I've paid off, uh, every time I've made a bet on transparency, it's paid off. So, uh, you know, we'll see. Maybe one day I'll regret being so transparent, but so far it's, it's worked really well. So that was sort of the recipe, and there's so many ways to build trust, and there's so much status quo. Like, you know, no, I doubt a s- you know, CEO of a Fortune 500 company would put their candid 360 feedback out there. If Tim Cook did that, then great. But if Tim Cook can't do that and won't do that, then one way I can beat him is by doing it, and by being a startup that's willing to take those kinds of risks. I think that sets us apart from the big tech incumbents. I, I am a big fan of flywheels. What I would recommend, especially early stage startup CEOs, is don't get obsessed with the greatest flywheel and frameworks and make something people want. At the end of the day, your job is to build a product that people want. It solves a real problem for them. And if you're lucky enough to do that, then you can start thinking about over time, how do you build sustainable competitive advantage? How do you build differentiation so that even if a competitor knew exactly what your playbook is, you could ultimately beat them 'cause you're building and investing into a flywheel that gets better. Of looking at companies like Amazon and say, "Wow, how did Amazon get so big?" And you look at, you know, Jeff Bezos famously talks about investing in things that don't change, looking at how the world's gonna be the same in five years or 10 years. Uh, will people want more selection or less selection? More selection. Will they want lower prices or higher prices? Lower prices. Will they want faster delivery or slower delivery? And, and so, okay, let's build a flywheel around faster delivery, more selection, lower prices. That sounds great. You know, they have this napkin, this famous flywheel that Amazon has. But at the end of the day, it started with building a product people wanted, getting them books over the mail, uh, and getting them the selection that they couldn't get elsewhere. And you need to start there before you have the luxury of thinking about flywheels and sustainable competitive advantage. And I know I'm the only... I, I've definitely made this mistake before of, like, getting ahead of yourself, but you gotta start with build a product people want. Yeah, so the advice I'd give to founders trying to find a problem that they can build a business around, uh, starts from a couple of dimensions. First, really be honest with yourself. Is it a problem? Is it a painkiller or a vitamin? You know, there's a lot of things in our life that are just small, be solved better with a pro- product. But you also have to accept that, like, change is hard. People are stuck in their habits. They're used to doing the things they're doing. So anything you build needs to solve a problem that's not just, like, a slightly better version of something that exists, but needs to be ma- you know, painful enough problem that they're gonna change their behavior to use your product. So that's first is, like, really be honest with yourself. Is this a problem? And is it a problem that you have? You might think it's a problem you have, but, like, be honest. Would you actually change your behavior to use the product that you're thinking about building? The second is if you focus on a problem, you think about the future of your focus on that problem, either what you're doing is a good idea or a bad idea. If it's a bad idea, it'll probably fail and you'll change ideas. If it's a good idea, you might have to live with this problem for 10 years, for 15 years, or 20 years. So make it a problem you care about. Make it a problem you might be obsessed with. The way I looked at it with Rewind is the problem of giving humans perfect memory is a problem that I would want to spend the rest of my life pursuing, even if it failed. Even if it wasn't successful, I'd rather be on my deathbed saying, "Well, at least I tried to give humans perfect memory and failed," than not try to solve that problem. And I think if that lens is something you use, you end up actually solving a real problem. And if you're successful, which you should hope you are, you're still gonna wanna be around in three or five or 10 years to make that problem and that product and that company as big as it possibly could be. So the one thing that AI can't replace, and in fact, the one thing that AI should all help us pursue is purpose. That's one thing that AI can't do. AI can't give us purpose. And as humans, that what's make us uniquely human is our purpose. Why are we here? It may be to spend more time with family. It may be to create something out of nothing. And if AI can be in service of your purpose, that is an accelerant. That's a superpower. It's not a replacement. It makes you better at what you do to pursue your purpose. And if anything you do in your day that doesn't help us pursue our own purpose can be taken away and augmented with AI, then I think that's a good thing for humanity. So our vision is to give humans superpowers. But if we're successful, I see Rewind as being as ubiquitous as glasses are for vision or hearing aids are for hearing. It's a tool that people will try, they'll use, and then they think to themselves, "How could I live life without this?" Uh, and that's my dream, our hope is if we're successful, people will look back today kind of in shock at how we lived our lives when there's so much more technology could do for them. [outro music]