Daniel Dines, UiPath CEO & Founder: Why Agents Do Not Mean RPA is F*** | E1240

This is a story that, uh, I never told anyone. (screen whooshes) I've wasted my, uh, late 20s, big part of my 30s and 40s thinking in this way. It's a totally waste of cycles (laughs) and energy, man. (screen whooshes) I am a lonely wolf. I find life pretty lonely, man. That's not only about this job, but I live mostly in my head, thinking, analyzing, reflecting. This is how I spend my life.

Ready to go? (upbeat music) Daniel, dude, I am so excited for this. Thank you so much for joining me in the studio again.

Well, I invited you basically (laughs) for this podcast.

(laughs) Now, uh-

So thank you for having me.

Dude, honestly, our first show did so well. I got so many emails from young entrepreneurs so inspired by your journey. And so I thought I would capitalize on the success of the first show. And I wanted to start with something that you said to me before, which is, at this stage of kind of the AI cycle, product matters more than innovation. Can you unpack that for me?

Yeah. Actually, I was thinking a lot lately, what's, you know, our story in, you know, in within the AI narrative we've... where we can really bring a lot of value. So over the last two years, we, um, we've spent a lot of time really trying to fine-tune LLMs, build around them, and to a certain degree of success. But I've got really inspired by stories like Cursor.ai, and my development team loves that product. It's a beautiful product built on the top of multiple LLMs, but it just, it just works. And I, uh, I recall actually how we started UiPath. There, maybe there is a... This is a story that, uh, I never told anyone. And, uh, so in the beginning, we, uh... So we were always based on AI in a way, but we were using a library called OpenCV, which among many other things provided a really cool feature to find a, a smaller image within a bigger image. So, and we repurposed that library for the sake of automation. So we can take a screenshot of an application, and if you want to click on a button, we can take an image of that button and then, uh, find it, you know, during, uh, during replay, just call, you know, a function, find this image of the button, I will get the coordinates, and I will click on the button. But that was not the only thing that we did. We created, I think, a magical experience. So we let someone to basically record the flow on the screen, just show I need to click this button, indicate on the screen the button, and then we'll generate, like, a very simple statement, like click that button with the image. Everything was stored. So you could have recorded an entire flow based only on, you know, working with images, even typing in a, typing in an edit box. So we will capture the edit box image and then, like, a label, and we can, we will find them during run time. But from the perspective of the user, it was really simple. So I remember it was, like, 2013 when I showed, I demoed this product to some guys that were really Blue Prism experts. And in order to do the same thing in Blue Prism, it would have taken, like, two days, and, uh, the outcome would be not as reliable as in our case. I did in front of them this flow, like, in three, five minutes, press run, and it worked. And I asked them, "What do you think, guys?" Total silence. They couldn't believe their eyes. And this is how actually we found our first niche to fight what was a giant for us, like Blue Prism at that point, and it was that niche where people would have to automate processes without having access to the applications other than by remote desktop via, like, Citrix, kind of. And this image-based recognition was the only way to, to do it properly. And that was our first niche where people would deploy and would prefer us versus Blue Prism. And from that one, we have basically expanded, you know, into what we are today.