Every Lesson From Scaling Datadog to $40B
EP 108 of The Logan Bartlett Show: Untold stories from tech's inner circle
Olivier Pomel built Datadog into a $40B company while burning only $25M in capital along the way. In our conversation, he shares the fundraising lessons, operating principles, and core insights that made this possible. We also talked about:…
the pros and cons of building a tech company in NYC
how early-career professionals should approach learning AI tools
how Datadog is building a trusted relationship with their users around AI features
& much more
Click here to view the episode transcript | Watch on Youtube | Listen on Spotify or Apple Podcasts
✉️ Episode Memo
→ The team didn’t write a single line of code for 6 months
Olivier’s biggest fear when starting Datadog was about building the wrong products and solving problems that didn't exist. Before Datadog had a product, potential customers were eager to discuss their problems openly. However, once they had a product, the interactions felt more salesy, making people less open and willing to engage. People (especially engineers) are more receptive to conversations that genuinely focus on their issues rather than being pitched a solution, so take advantage of that dynamic as much as possible.
→ Working with peers > managing
Olivier Pomel believes that direct reports should be treated as peers, not as subordinates. If you have to manage their career, they might not be the right fit. Instead, you should trust them to do their jobs and focus on discussing what’s best for the business. This approach can also be liberating and help set high standards when hiring.
→ Olivier’s mindset toward shipping new products
The goal for every Datadog product is to be the best in its category and outperform all established competitors, even standing on its own. Olivier understands that achieving this for each product takes time, but beyond building top-tier products, Datadog's true competitive edge lies in its broad platform approach. With fully integrated products, Datadog made it irrational for customers to mix and match tools instead of adopting the entire Datadog suite.
⭐ Trailer
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