What happens to Observability If Code is AI-Generated? The Potential for AI in DevOps, with Datadog Co-founder/CEO Olivier Pomel

**Conviction** (0:05)
Welcome to No Priors. Today we're speaking with Olivier Pomel, the co-founder and CEO of Datadog, the company at the forefront of the DevOps revolution. Datadog is a leading observability and security platform for cloud applications. Its execution and ambition has impressed me for years, especially since learning more about the company after it acquired Screen in 2021, a security startup I was the board member for.
I'm excited to be talking about the potential for AI in DevOps. Olivier, welcome to No Priors.

**Olivier Pomel** (0:32)
Thanks for having me.

**Conviction** (0:34)
Let's start with a little bit of personal background.
You're French, you've been in the US, working on startups since 99 How did you start to think about starting a company and Datadog in particular?

**Olivier Pomel** (0:46)
Yes. I'm from France, and I guess nobody's perfect. I'm an engineer. Also, I got into computers, largely through computer graphics. When I was a kid, I used to follow the demo scene in Europe, which was all about 3D and doing interesting things in real time. This led me later on to be one of the first authors of VLC, the media player, who I think is mostly used for viewing illegally downloaded videos.
I should say, most of the people who made that successful came in after me, picked up the project and did something fantastic with it after I left for the US.
Then moved to the US to work out of all places for IBM research in upstate New York.
I thought I would stay six months and I've been here since 1999 So it's been a while. I worked for a number of startups. Through the, I would say, the tail end of the.com boom, I arrived right in time for the bust. After that, I worked for, I think, eight years for an education software company, Education Startup that was doing SaaS for schools based in New York.
And that's when I was at this company that I spent quite a bit of time with a person who was my co-founder, Datadog. And that's where we had the idea to start Datadog, basically, which was, I used to run the dev team there, and he used to run the ops team, and we had a different team. We tried hard not to hire jerks. We were very good friends. We've known each other since the IBM days, basically. And we still ended up with dev and ops setting each other, people pointing fingers at each other all day long, big fights. So the starting point for Datadog was not monitoring. It was not even the cloud, initially. It was let's get dev and ops on the same page. Let's give them a platform, some place you can work together, see the world the same way.

**Conviction** (2:34)
Yeah, that's actually quite different than thinking of it as like a ticketing relationship, right? A quite siloed relationship between the two areas. I think most people assume that Datadog comes from a place that was more like metrics or like we knew the cloud was coming. And I'm sure both these things are true, but it's interesting that the core starting point is really around like DevOps collaboration.
You are, I think, pretty long NYC and have been challenged on like building in front of NYC as I think to even attempt before. Like, tell me about your original thinking on that or if it even crossed your mind.

**Olivier Pomel** (3:08)
Well, I mean, so I stayed in the US because I loved NYC. That's why I ended up staying here. I love the energy. I love the diversity of the city. I also met my wife in NYC and she's also not French, so she's also not American. So it also made sense for us to stay in the city. So when we started, my co-founder, it made total sense to start a company in New York. We also knew fantastic engineers. We would hire in New York. So it was very obvious from that standpoint.
I would say it was less obvious when we started fundraising because we didn't come from systems management or observability or anything like that.
And we were based in New York, which was not seen as a great place to start an infrastructure company at the time.
So I would say for most investors, especially Bay Area investors, I think it was considered as some form of mental impairment to stay in New York at the time. It made it harder to fundraise. And I think as a result, it made us more successful because we were so scared of getting it wrong and so scared of not being able to fund the company any further that we really doubled down on building the right product for one thing, but also we built a company that was fairly efficient from day one. And hovered around profitability throughout its whole existence pretty much. And I think in the long run, it's been an advantage. Like everything else, if everything has a long run or long-term advantage, it turns out to be very difficult in the short term, typically.