← The SaaS Podcast - Growing Profitable AI SaaS & AI Agents
The SaaS Podcast - Growing Profitable AI SaaS & AI Agents
Bootstrapped SaaS Growth When AI Took Over the Market
00:43:07
Sylvestre Dupont (Parseur) on growing a bootstrapped SaaS to 7-figure ARR while AI competitors raised hundreds of millions
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- [00:03]
A
Welcome to the SaaS podcast. I'm your host, Omer Khan. AI has changed the playbook for building and growing SaaS. Every week I talk to founders who are writing the new one. My guest today is Sylvester Dupont who bootstrapped the SaaS to seven figures in ARR with a team of just six people and zero outside funding. But he spent an entire year building without talking to a single customer. Launch day came and went, nobody signed up. He even reduced the price of his product to $9 a month just so people would try it. Then well funded competitors started pouring hundreds of millions into AI doing exactly what his product does. In this interview, Sylvester breaks down how he rebuilt his entire product around AI funded entirely through his customers revenue and how an unconventional channel that most founders overlook became his primary source of customers. One of the hardest things about building a SaaS product or an AI agent is not having a technical co founder or CTO to guide the decisions. That's where Gearhart comes in. They can act as your fractional CTO and technical team. They bring AI expertise from projects for Meta and Google and they have strong Silicon Valley connections with founders and VCs. And since they're a Ukrainian born company with offices in San Francisco and London, you get senior level talent at an offshore pricing model. Right now they're giving our listeners the first 20 hours of development for free. Go to Gearhart IO to book a call. That's Gearhart IO. If you're building or investing in a SaaS company, you already know security isn't optional. One breach and everything you've built can be at risk. That's where ThreatLocker comes in. Imagine having the power to decide exactly what's allowed to run in your environment and and blocking everything else by default. No guessing, no hoping your existing solutions catch it. Real enforceable control. ThreatLocker is a zero trust platform that locks down your environment without disrupting operations, gives you total visibility and stops unauthorized applications before they become a problem. If you want stronger security and tighter control, visit threatlocker.com that's threatlocker.com the playbook that got you to six figures in ARR won't get you to seven figures. And at this stage you don't need another course. You don't need more content, you need clarity. And you need people who get it. Because right now you're probably second guessing every decision, wondering if you're focused on the wrong things, working harder but watching revenue flatline. SaaS club mastermind is how you get there. A small group of founders all Scaling to seven figures with Mastermind calls and direct access to me. Think of it as your board of directors without the drama. Apply at sasclub IO Mastermind or that's sasclub IO Mastermind. Sylvester, welcome to the show.
- [02:54]
B
Hi Omer, thanks for inviting me.
- [02:56]
A
My pleasure. So for people who don't know Parser, what does the product do, who's it for and what's the main problem you're helping to solve?
- [03:04]
B
So parser is a B2B SaaS and what we do is quite simple. We help automate data extractions from documents. So if you receive too many documents, too many PDFs, too many emails, too many spreadsheets, and you want that data on the documents to be somewhere else in your accounting software, in your CRM, in your just spreadsheet. You send the document, you tell us what you need and we extract it for you. It's a very generic product. We are not vertical, we are not tied to an industry or particular use case. You can do it for many, many things. And what we like about it is that every company has documents. I don't know any single company that says, oh no, I don't need to copy and paste some data from documents I received, I have invoices, I have delivery notes, I have contracts. So the pool is gigantic, the use cases are infinite and that's quite fun to work with.
- [04:06]
A
So give us a sense of the size of the business. Where are you in terms of revenue, customers, size of team?
- [04:11]
B
We are quite an old company, so we started 10 years ago, so we had the time to grow. Today we do seven figures. We remain quite small. Today we are only six people. We kept very small for very long. For the first five years we were just the two of us, my co founder and I. And then slowly we increased the team, starting with marketing and later development and support. But yeah, we keep very small. One particular thing about our team is that we are remote. Everybody remote and very far spread apart. We are six people, we live in six countries across five time zones. That spreads 12 hours. So the latest recruit is from Singapore, so it's the most eastern one and the furthest west is the support in Miami in the us.
- [05:03]
A
And how many customers do you currently have?
- [05:05]
B
Close to 1,000 now paying customers. We have many more, we have a free plan. So we have many more non paying.
- [05:11]
A
And the business is totally bootstrapped.
- [05:14]
B
Yes, we started fully bootstrapped, 50% shares to each share through its co founder and we kept it like this.
- [05:22]
A
Great. So let's start with like let's go Back to like 2016, 2015, like where did the idea for this product come from?
- [05:32]
B
My co founder and I, we know each other for very long, like 25 years now, and we are both technical minded people. He's a senior Python developer. I used to be in consulting at the time when we started, but I have a technical background and we started to want to create some things on our own. So trying to start a business thinking about different ideas and at the same time, we were both traveling quite a lot at the time. And so I started to work on some travels as I did work on a map to map out my travels to show them nicely. And I got bored by having to enter all the trips one by one on this map because we were traveling a lot that way. I made it trips. And so an idea came that, oh, maybe we could have a tool. You just send the booking confirmations and you get your map updated. So we started to research the space and we saw that there were already some tools doing that, but none that were doing it the way we wanted. And we said, oh, maybe that's an idea. That was 2015. Okay. We said, let's go. I think we did all the mistakes that everybody does when they start a new business. So we spent a full year hunkered down, coding, zero marketing. We did just a little experiment at first to have a quickly done homepage and put some Google Ads to see if people would click sign up and then see if we would collect emails. And we collected 50 emails. So we said, okay, we are product market fit, we're good.
- [07:03]
A
That's right.
- [07:05]
B
And then one year later, we did everything. We even had the payment ready on day one. We did everything. So one full year, full development, no marketing, no nothing but full. And then we launched in December 2016 and we launched on Product Hunt. We launched on hacker news like everybody does. And nothing happened, of course, because we didn't do any marketing, we didn't talk to any potential customers. We did send the 50ish emails we had collected one year before. We did send them, hey look, we are ready. But it was one year later. So I think two people signed up and quit immediately. So it was a huge failure.
- [07:50]
A
This isn't the first time I've heard something like that. And a lot of new founders get into this situation. They're excited about the product or an idea, they start building it. It's more fun building the product than it is to go and talk to potential customers and think about marketing or sales. So you keep Doubling down on that. And ultimately you get to a point where you've invested so much time and money into the product that you're just looking for confirmation that you're doing the right thing. So it sounds like you did a very sort of similar thing where you were excited about the solution and then you're looking for a market that might want this. What would you say when you sort of look back at that? I mean, there's obviously a whole bunch of things that you could have done differently. But what was the biggest mistake that you made in that first year?
- [08:48]
B
Well, we should have found potential customers that wanted to talk to us that were excited by such a product and could have built it with. We could have built it together. I would have loved to have somebody that would have said, hey guys, I'm happy to pay X amount per month. And we would have been built a version that works for them together and we would have been much faster, much more straight to the point. And that would have been good. But yeah, and in general, just start marketing is not an afterthought. It's not only just having a homepage and a sign up button. You need to have a strategy. You need to see how you're going to attract your customers, where you are going to find them, what is going to be your elevator pitch, what, what IU is the idea you have in mind, the way you explain it, something that speaks to them. So there's a lot of work there. I think as a technical founder, you just focus on the technical because that's what you know, that's what you are comfortable with. But you have to learn marketing. If you are launching a new product without somebody that is more product and marketing oriented, this is something you have to learn on your own and you better do it sooner than later.
- [09:57]
A
And you didn't know who your customer was either at that point, which makes things really hard to figure out. And it's very easy just to say, oh, our customers are people who need data extraction from documents. But as you know, that's probably not the best way to figure out who your ICP is. So once you got to that point where you launched and it was kind of crickets, how did you then figure out who you were going to serve, who you were going to solve this problem for?
- [10:29]
B
So we did two things. The first thing was to start and publish some content on our website. Some blogs about what is document parsing, what is data extraction, how does that work? Some things a bit more technical, some things a bit more general of what we thought people would be interested in. But that was SEO play, basically. But that takes lots of time. It's. You don't overnight have some traffic. But we did start at the time and then in parallel we started to contribute to some forums. The one at the time that had the most conversation was Quora, that I think now is totally disappeared and replaced by Reddit. But yeah, and Quora is where we found our first customers. We started to. There were already some people asking about document automation, data extraction, et cetera. We started to answer that, we started to be active, we started to be helpful, not only just to blast our products, but just to honestly answer what could be the best solution. And this is where we started to see some signup and finally we could start and talk with people because we had the little chat widget already at the time and it was priceless to just interact with people that were trying the product.
- [11:42]
A
So what were you posting on Quora? There's a principle here. You weren't just posting a link to your website, right?
- [11:51]
B
No, we were making elaborate answers, answering exactly the customer's problem, mentioning our brand in passing along with other competitors, just to be fair, just not to be too pushy. And that worked, at least at the time. I don't know anymore.
- [12:06]
A
Yeah, now I'm sure, Even back in 2016, it seems like a long time ago, but I'm guessing Parcel wasn't the only game in town. So what was it about your product that you think got people interested compared to other potential solutions that were already out there?
- [12:30]
B
So we are talking about pre AI, boom and everything. So at the time, products were quite complex to use. Basically what you had to do in all of the competing products was, was to have to create some rules. So you say, oh, this is my document. Look for a line that starts with invoice and then remove everything that is before the colon and then go up to the end of the line. And you had to specify those rules manually, one by one. It was super tedious. And if your document had another layout, we would have to do that all over again and decide some rules to choose with this rule set or that rule set. It was complex to set up and to use. We decided to keep it simple and stupid. So we decided to be visual. So we would show you your document, you would highlight the data you wanted and we would do the heavy lifting behind the scene to figure out where this bit was and how to make it work. And we make it so that you could have as many layouts as you wanted and we would automatically pick the right one. So for us, simplicity was what was our first setting point you could basically get set up in maybe 10, 15 minutes rather than two hours.
- [13:42]
A
And how did you figure that out? Did you look at the products that were out there and say, these are complicated to use. How can we make this simpler? Or were you getting feedback from people complaining how hard it was? What was the process that got you to the point where you said, a visual type solution is going to be one of the best ways that we can differentiate our product right now?
- [14:08]
B
Well, that was quite early because I'm quite analytic as a person. I love Excel spreadsheets and going deep into the data. So I needed to have a bit of an approach on how we would do that business. So I did look at all the competitors, I tried them all. I look into the pricing, I do look at everything. And for me, what came out of it was the complexity of the product. And my co founder, Sylvain, is also somebody that is very good at making simple solutions, at finding elegant answers to complex problems. And it appealed him as well to try to find the best way to have something visual and easy to present for our users.
- [14:50]
A
You mentioned you got your first customers through Quora. Did the first 10 customers come through there and how much were you charging those early customers?
- [15:02]
B
So when we launched, the very, very first day we launched, we had our first pricing, I think was $49. But when we saw that nothing was happening, we slashed our pricing down to $9, just, you know, just to try. We just wanted feedback. And so that's how I think that contributed to having our first paying customers. And yeah, I think, I wouldn't say the first 10 were from Quora, but I think a large share of the first 50 were from Quora. And by that time we kept publishing some articles and by that time the SEO play started to work for us. It was a bit easier back then and we started to attract most of our users from SEO.
- [15:43]
A
So aside from posting on Quora, having these sort of answers and doing the creating content and trying to make the SEO play, was there anything else you were doing to find customers?
- [15:55]
B
Well, we tried a bunch of things like posting on some communities we would find or even at this time, I think we already started do some ads, but nothing really worked. The first thing that after SEO, the first thing that worked for us was when we created a connector for Zapier. Zapier is an automation platform, if you know about it. And then because R2 is a bit useless on its own, when it shines is that when you can send the data to your applications. And because it takes a lot of efforts to build integrations for each and every application, we decided to integrate with Zapier, that already integrated with thousands of applications. And these guys, they, well, you could create a connector for them. So we did that. And then they would advertise about you, they would send a newsletter and say, oh, we have this new connector that arrived and. And they did a blog post at some point about mentioning us. And that was great because the guys that were on Zapier were super qualified. There was not that much traffic compared to SEO. But the conversion rate from the traffic we got from Zapier was incredible. We had like maybe 20 or 30% conversion rate. So that was very nice.
- [17:11]
A
So today you have over 1,000 customers. Are they still coming from SEO?
- [17:18]
B
Yeah, mostly it's maybe, I don't know, 95% today with SEO. So what we did is that our first recruit was a marketing lady person that would dedicate it to publishing content. So that was in 2020. And we kept growing and growing and growing our or Surface because our use case are unfeeled. So we just have to understand what our customers do. Write articles, try to find the long tail keywords and publish and publish and publish. That works great. And very recently, like last year, we doubled down on it and we translated all those articles in at first three languages, but now we have I think close to 10 languages to widen the net, basically.
- [18:08]
A
But Sylvester, all the LinkedIn experts tell us that SEO is dead. So how is it working for you?
- [18:15]
B
It's still working today, but indeed there's been a drop in traffic because of the AI overviews. AI traffic. So now our place to try to do AI SEO Geo, I think, as they call it nowadays. And so we monitor how good we appear in the AI search results, we try to increase that. But at the end of the day it also depends on the type of traffic. When your answer that gets replaced by an AI overview from Google. Most of the time the people were looking for an informative answers, they were looking for definition, they were not looking for a product. If they look for products, they will not stay on the explanation from Google, they will visit the website. So even if our traffic has dropped, our numbers of sign up has not dropped that much at all. It's increasing. So you have to look at the end of the day of the result of your conversions, are you getting traffic
- [19:18]
A
from ChatGPT as well?
- [19:20]
B
Yes, yes, and growing and perplexity as well and more and more anthropic.
- [19:26]
A
So are you doing anything different when it comes to SEO versus aeo, geo, whatever the term is these days. But is there anything you're doing different?
- [19:38]
B
We try a few things. The first thing we tried is that on our blog post now you have some buttons to summarize the blog post with AI in the hope that then we will end up in some training data from those AIs later on down the line to get our brand mentions. I have no idea whether that works or not, but the buttons are clicked so some people enjoy having the ability to have a quick summary and then we try to keep up to date with whatever we read or the people that research about AI do. And so a lot of them is about, for instance, putting some FAQs, lots of FAQs, structured data FAQ in your article so that the AI has no trouble reading them. Putting some bullet points at the top if possible. In a lot of ways, at least from what I see today, the recommendation that we read for being good at AI looks like the recommendation you would read 10 years ago for Google. So a bit of a dumber AI, but just trying to provide the easiest, simple solution to whatever the customers are looking for.
- [20:43]
A
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- [22:46]
B
So a few things. The most important one was we actually made the product simpler. I'm coming back again at this, I'm sorry, but that's my thing. For instance, at first we would ask the customers that would sign up, they would ask them to create a mailbox where they could send documents to and they would have to name the mailbox. Then we would ask them to create a template where they could visually highlight the data. Then they would have to name the fields, name the templates and et cetera. And there was a lot of, we would request from a lot of inputs from the user. Progressively we started to remove all of that and then AI came. So with AI, it's much easier to have AI do things for you. And now we don't ask anything from the user. They sign up, they upload a document, we create a mailbox automatically, we find a name for it, we look at the documents. We use AI to try to identify what is the most likely data points that the user want to extract. We do it, we show it and we say, hey, that's what we think you want. Not you can change it, but at least we removed all the friction that we saw over time. But that took months and years of maybe watching recordings or finding bugs or looking for some niche corners. And that's. And we have not done, we are still working on it today to remove friction.
- [24:13]
A
So you started out as this rule based parser which you explained earlier and today you are this AI powered parser, data extraction tool. But you guys didn't just put like a wrapper onto like GPT4, right? You decided to take a different approach. Can you just explain what you did?
- [24:37]
B
Yeah. So today AI is very good at extracting the data. I mean you can send one PDF to ChatGPT and most of the time it would get you some data and you can extract it. But if you really want to automate your whole workflow, it's not just about sending a document to ChatGPT, it's having the full end to end automatically fetching the documents, looking at them, routing them to the right mailbox, they need to be. There is a lot of work in pre processing the documents so that the AI can have the most chances of finding the right data. So for instance, if there are images or scans, we try to make them straight. We play with contrast if we have to, we resize the documents. Some PDFs are awful. I don't know if you ever entered the wonderful world of PDFs, but some of them are so complex and so different than usual that we have to have some codes that fix all the issues that can happen so that we present the best possible version to an AI and then the AI does it. And what the AI does, even if we have years of practice about finding the right flow and prompts and tweaks and many things, at the end of the day it's an LLM. So we keep up to date with what happens. And then you have to export the data. And then there again here you have a lot of. You have to transform the data, make sure the data all the same, the numbers, the locations. We have a lot of downstream post processing that happen before we can send it. So what we do today, basically, if you have three documents on a folder, you don't need us. But one unit is if you have 100,000 of the documents that you have to pass every year and you want an end to end flow.
- [26:32]
A
What's like your token usage or costs of processing this volume of documents. You're a bootstrapped business. We know that using AI to do anything like this can very easily get seriously out of control. So what's the situation for you? How are you managing those costs?
- [26:59]
B
To be honest, it's not that crazy. Our costs today are. Our server costs are more important than our AI costs. Maybe this year is going to change because we keep adding AI a bit everywhere. But it's under control, it's not a large part of our costs. And why is that? Is that again, we try to keep the most simple approach as possible, cache everything we can so that we don't have to ask twice. We don't use the smartest, best AI, most expensive ones as we see today. Not because we don't want to spend the money, but because they are slow and they get limited. And the people that users, they cannot wait for half an hour to get their 100 page document processed. So we try to find the balance of the best quality AI for the fastest response times. And that's not too much delay.
- [27:57]
A
Well, I think you're in an interesting space because I sort of see you in the middle. On the one hand you have other players in this space in sort of document processing, which as far as I know, I'm not an expert on this, but it's a pretty big opportunity and there's a lot of spend in that space and some of these companies are spending hundreds of millions of dollars while you're having to sort of be in this bootstrapped business with the constraints that come of running being bootstrapped. At the same time, you've got these developments happening with ChatGPT and Claude Code and all of this stuff. So what would you. I want to talk about both of those in terms of how you think about your positioning and kind of competing against some of these bigger players with a lot more money. But let's start with the other scenario where people are looking at something like Parser or other products and saying, I don't need that anymore, I can do whatever I want. With ChatGPT and Claude.
- [29:03]
B
Well, again, for some use case it might be perfectly reasonable and I would actually encourage some users to do it. Especially again if the volume is low. Sorry, you may not need us. If you are happy with downloading an Excel and keeping it on your folder, you may not need us. But if you start doing your own rollout, your own solution based on those AI, so you try to ask them to write some codes and host the codes, I can guarantee you that it's going to work no problem. But you're going to have to maintain it quite often because the models change, the package got out of date and it may not end up being as cost effective as it is using a third party solutions. We had quite a few customers still today that come to us and say, okay, we tried our own solutions. It was a nightmare to maintain. As the volume grew, it kept exploding. We went back to looking for a SaaS or cloud solution and you guys are doing it and it's great. Even us now we have to keep on the latest and greatest AI development because they change so fast that it's almost a full time job to make sure we have the best engine we can offer to our customers. So basically we do the R and D for our customers.
- [30:25]
A
Yeah, I think the whole idea of Vibe coding is, is so fundamentally it's just a completely different change to what we've been used to when it comes to software and this sort of the space. But I think there's a lot of realities of Vibe coding your own solution that a lot of people or businesses haven't fully thought through or understood the consequences of maintenance being one of them. Right.
- [31:02]
B
It's just as a developer, it's a lot of fun to vibe code because you can go so fast, so quickly. But then if you start looking under the hood and see what the AI is actually producing, you can see some quite horrendous stuff. And I do that in a weekend because that's what I enjoy doing. So I have some side projects and I, I like to wipe code them. But it's fun for a TDT project. It doesn't scale at some points it gets too much, too complex and the AI is lost and maybe it's going to improve, but today it's not ready.
- [31:39]
A
I saw a tweet somewhere, maybe it was a meme or something. It said something like, software is dead. Vite coding is the way to go. And I've canceled my $10 a month calendly subscription and I now have my own solution which is 5% accurate with the scheduling and only costs me 150 bucks a month to maintain. So let's talk about the other side. So you're also in a space where there's some very well funded competitors who are probably investing a lot more into the product innovation, AI and so on. So where do you see yourself fitting in the market? If you're talking to a potential customer and they're saying, you know, why should I use you? Why is your product better or different than these other things? What's your answer to those people?
- [32:35]
B
So we try to mix three constraints that usually are hard to mix together. We want to be simple to use, we want to be scalable in terms of activity. You could go as much volume as you need and we want to be compliant or trustworthy because our customers are sending us personal data and we know that we have to do everything we can for ensuring that. We treat that data as privately as we can for I think it's quite hard to combine all of them. So if I look at the bigger players, the VC funded players, they are compliant because that's a given for them and they can scale, they have the money for that. But usually their processes at their tool is very complex because they are serving very large companies. So they are used at making very complex custom built solutions. I think that deserves the purpose of automation. For me, automation should be simple as possible, self service. You shouldn't have to talk to sales to get access to the product. For me, if you understand business automation, you shouldn't have a human in the process. So for me the big VC funded customers that have as their first step talked to us is a bit of a red flag. But even the ones that have some free service for what I can see, they could do better in having something that is actually simple to use. And this is where we hope we try to keep our focus and have something that can be set up in a few minutes.
- [34:34]
A
Keep it simple, always. Let's talk a little bit about your target market. The conventional wisdom for any founder, especially bootstrapped, would be to pick a very specific problem, very specific niche market, very clear ICP and go and solve the problem for them first before you try to expand from that. And you didn't do that. You went horizontal, I think from day one with the product. And then when we look at the landscape today, with everything that's happening and AI and the changes, we often hear horizontal products are toast. It's all about if you're going to succeed, it's going to be more about vertical SaaS and those kind of plays. So first, maybe tell me why you decided to go horizontal from the start.
- [35:34]
B
It was not a decision we make consciously at first. We just said, oh, let's build a parsing tool that sounds fun and it's generic and we are developers so we're going to abstract everything. So yes, maybe we should have niched at first and then expand it. But that didn't happen. But that worked for us, so why not? And there is the. It's so thrilling when that works. It's so thrilling. We had some guys that in one day they got to pass a 10,000 utility bills and you talk to them and they're very happy, they get all the utility bills. And then you jump to the next conversation and it's the guy that is a pigeon race, a breeder and he has a genealogy of pigeons, raised pigeons. And he has PDF with papa pigeon, mama pigeon and baby pigeon and he wants to extract that from a PDF and that works too. And the exact same tool with the exact same config because we created it in such a generic and simple way, it works the same. And there is a beauty in that, right? To build a product that is so lean and hopefully so well thought out that we don't care about whichever data we receive, we just care about what you need to extract from it and then we give it back to you.
- [36:57]
A
But does that make it harder to market the product and reach potential customers?
- [37:01]
B
Yeah, I think. I mean, I've never built a vertical SaaS so I cannot have firsthand experience on how the Difference is really. But yes, I definitely. It's not like on our homepage we can say the solution number one to extract the data from your pigeon genealogy tree. No. So we have to find some wide language. But again, most of our traffic is SEO and SEO Pay is great for that because you can write about how many, use cases as you want and deep dive on it and talk to your customers and make sure you use their vocabulary. So there is a bit of work there, but you can go very wide with SEO, there is no limit.
- [37:43]
A
So that makes sense. And it sounds like what you've set up with SEO and this funnel and how you acquire customers is working for you. Do you worry that maybe now with the way that we're talking about AI tools, that you can have new players come in who are more vertical, focused and doing a much better job at finding a solution for the pigeon guy, or do you think that that isn't necessarily a concern because of just the nature of what this document parsing and extraction is about?
- [38:27]
B
I think in general, it's a very crowded space. There are players in and out all the time. So maybe with AI we have a few more players. But I don't think it has tremendously changed the game because again, it's not just about the AI. It's also about everything around privacy, data compliance and scaling and these things, they are a whole different game. But at the same time, it's true that with everything that happens in AI and things moving so fast, we are trying to think about where we should go in five years and in 10 years. And I think we start now to have some ideas or some directions that we would not have picked a few years ago before AI, because. Yeah, because it is definitely shifting our direction. So now the way we want to go is very early. So I won't be able to share about it here. But yes, it's to be able to provide more values to the users beyond just data extraction, just in case it gets too commoditized.
- [39:36]
A
Yeah. And do you think that how much of a risk you think there is that it does get commoditized?
- [39:44]
B
I don't know. It depends on the timeline. Maybe 20 years. Of course, we are gone. I hope in five to 10 years we're still around.
- [39:52]
A
I mean, there's no shortage of these PDFs out there, is there?
- [39:56]
B
No. And I think we also live a bit in a bubble. If you ask some small business owners, many of them don't use AI today. They don't even know what maybe ChatGPT yes, they would know. They heard of it, but many have never used it. You should start to talk about Claude or Anthropic or Codex or whatever. No. So there is also a lot of inertia that maybe we Things will take a long time to change and I've
- [40:22]
A
tried extracting data from PDFs with ChatGPT and a lot of the times only to realize a day later that it didn't actually extract the right data.
- [40:34]
B
Yes, yes, data quality and controls are something fun with AI.
- [40:39]
A
All right, we should wrap up, so let's get onto the lightning round. I've got seven quickfire questions for you. You ready?
- [40:46]
B
Yep. Let's go.
- [40:47]
A
What's common startup advice that founders often get that you think is wrong for
- [40:54]
B
the ones like us that are spoiled and bootstrapped? I would say to say no often, to keep your focus, know what's important for you for your growth, and say no to everything else.
- [41:04]
A
What book would you recommend to our audience and why?
- [41:07]
B
The one I've read most recently that left a lasting impression on me was Plax 1 by Nassim Nicholas Taleb. About the biggest risk in your life are the ones you don't know about.
- [41:20]
A
What's something you're good at now as a founder that you were terrible at in sort of the first year of building your business?
- [41:29]
B
Just be driven by customer concerns. Just don't do what I think is right, but listen and do what they want.
- [41:37]
A
What's your favorite personal productivity tool or habit?
- [41:40]
B
Now that we are growing as a team, I try to prioritize everything that my team depends on me, so I try to unblock them first before I do the things I have to do later so that I don't think they are on productivity.
- [41:55]
A
What's a new or crazy business idea you'd love to pursue if you had the time and money?
- [41:59]
B
Well, if I have all the time, I would retire today. I would try to create a vibe coding tool that can keep things simple and not create ugly codes of thousands of line.
- [42:10]
A
What's an interesting or fun fact about you that most people don't know?
- [42:14]
B
Well, I like to travel. I travel quite a bit and I like to take a picture of me jumping when I travel. So I have a website called Jumping Traveler and every time I travel somewhere, I post a picture of me on there.
- [42:27]
A
What's one of your most important passions outside of your work?
- [42:31]
B
Well, travel is one of them and everything related to it. Slow travel, preferably ferries, crews, trains. Love him.
- [42:40]
A
All right, great. So Sylvester, thank you so much for joining me. It's been a pleasure. If people want to check out Parser they can go to parser.com so it's p a r s e u r.com and if folks want to get in touch with you, what's the best way for them to do that?
- [43:00]
B
Twitter is fine. Slybigs is my handle.
- [43:03]
A
Okay. We'll include a link in the show notes. Thank you. It's been a pleasure and I wish you and the team the best of success.
- [43:09]
B
Thank you very much. Omer. Thanks for inviting me.
- [43:11]
A
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