Jul 24, 2026 · 30m · y-combinator
How Two French Engineers In New York Built The Company That Monitors The Entire Cloud · Y Combinator
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In this Y Combinator Startup School Paris fireside chat, Datadog Co-Founder and CEO Olivier Pomel shares lessons on scaling a multi-billion-dollar enterprise cloud platform, overcoming early VC rejections, adapting to AI disruption, and maintaining hands-on leadership.
How this conversation actually went
Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. How this is scored →
The partners as informed peer 3.3 Guest teaching 3.6 Guest disagreement 3.0 The partners pushing back 2.0
speaking balance: gold is the partners, purple is the guest (3 minute bins)
Sharpest disagreement ▶ 10:55 Dismissing 'strategic' as corporate BS
Pomel forcefully dismisses standard corporate jargon, stating that whenever someone uses the word 'strategic' he mentally translates it directly to 'bullshit.'
Hardest push from the partners ▶ 12:00 Challenging CEO involvement as an organizational bottleneckThe host directly questions Pomel's hands-on involvement in minor product decisions, pressing him on whether that intervention turns the CEO into a bottleneck.
Biggest teaching moment ▶ 5:18 Correcting the history of monitoring versus observabilityPomel firmly corrects the host's premise that observability existed at the time, educating him on how siloed and reactive 2000s monitoring tools were.
The partners hold their own ▶ 27:15 Host validates US expansion with personal founder experienceThe host brings in his own track record of starting in Europe in 2012 and moving to San Francisco to directly reinforce and contextualize Pomel's cross-border expansion advice.
the scores for every segment, with the reasoning behind each
| Chapter | Topic | The partners as informed peer | Guest teaching | Guest disagreement | The partners pushing back | Why |
|---|---|---|---|---|---|---|
| Title Sequence: Y Combinator Presents Startup School Paris | 2 | 2 | 2 | 1 | The conversation opens with playful banter about Datadog being rejected by Y Combinator. The host acts as an amicable facilitator asking broad biographical questions about Pomel's background and move to New York. | |
| Founding Datadog and Unifying Dev and Ops | 3 | 4 | 3 | 2 | Pomel details the initial dev-versus-ops friction that inspired Datadog. When the host asks about observability companies back then, Pomel corrects him, noting the industry was called monitoring and was far more siloed. | |
| Category Creation and Product Market Fit | 3 | 4 | 4 | 2 | Pomel recounts early fundraising friction with Bay Area VCs and explains Datadog's refusal to write down corporate values. When the host summarizes this as 'your culture is you,' Pomel reframes it to emphasize practical actions over personal identity. | |
| Hands-On CEO Leadership and Ground-Level Feedback | 3 | 4 | 4 | 3 | Pomel candidly rejects corporate strategy speak, bluntly equating the word 'strategic' with nonsense. The host raises the risk of leadership becoming a product bottleneck, prompting Pomel to explain how sampling frontline data guides the organization without blocking it. | |
| Expanding the Product Portfolio and AI Agility | 4 | 4 | 3 | 2 | Pomel explains how Datadog expanded into 25 products and managed the volatility of public markets. When the host probes stock price worries, Pomel educates on how public market swings actually impact operational talent retention and RSU compensation rather than company survival. | |
| AI Revolutionizing Software Engineering and Internal Workflows | 4 | 4 | 3 | 2 | Pomel outlines Datadog's AI strategy, highlighting how bleeding-edge AI labs differ sharply from enterprise clients with finite compute. He explains their internal mandate moving toward no-code development workflows driven by AI tooling. | |
| Co-Founder Relationships, Geographic Expansion, and Velocity | 4 | 3 | 2 | 2 | The discussion covers long-term co-founder dynamics, geographic expansion from Europe to the US, and velocity in personnel decisions. The host relates his own experience moving to SF while Pomel advocates for moving rapidly on hiring and firing. |
Statements from this episode (18)
Pomel: Datadog Interviewed for Y Combinator and Was Rejected by Paul Graham
“Yes, we applied. We got an interview. I've got I've got a rejection email from Paul Graham still, you know.”
Pomel: Legacy monitoring was siloed for Ops, leaving developers blind to production
“It was not called observability. It was called monitoring. And it was very job specific and very reactive. So, you know, for network monitoring, you'd have a product for, you know you'd have something that the ops team would use, but the developers would never…”
Pomel: Established companies initially dismissed Amazon's cloud as an unusable toy
“The premise for the company, which was let's bring Dev and Ops together into one platform was actually completely central to the explosion of the cloud. And we also completely underestimated the explosion of the cloud with, oh, that's interesting. There's this…”
Pomel: Framing products in established categories makes enterprise purchasing easier
“People love the idea of a new thing, but they have no idea what they should pay for it, and their boss has no idea what they should pay for it, whereas you say, oh, this is financial monitoring and then everybody, everybody and their boss understands, yes, act…”
Pomel: Culture flows from leadership actions, not written value lists
“What we said instead is culture flows from the top. So we exemplify the culture, we hire, we promote, we hire based on the culture, and today, that still works.”
Pomel: Scaling founders must sample raw customer feedback over executive summaries
“Another thing I think I encourage everyone to do as soon as you start scaling a little bit in your company is to keep in touch with what's actually happening on the ground. And by that I mean the actual support requests, the actual sales transcripts from the s…”
Pomel: Inquiring on random support messages forces managers to stop managing up
“Well, what I do is I just pick up those random emails or, you know, Slack or whatever, and I just reply with a question, you know. I was like, I don't understand what's going on. And then, you know, and then, you know, the, what happens is that, there's two th…”
Pomel: A manager's job is knowing their domain, not pleasing their boss
“Your job is not to understand what I want, As a boss, your job is to understand what's happening within your span of control, and understand it very, very precisely. What's, what's working and not working?”
Pomel: Companies must build ahead of AI demand and will fail more often
“With AI in particular, things are changing so fast that you just can't wait to see the demand materialize from the customer base. So you need to get ahead of it, which I think us and many others I think are going to get wrong more often, and we need to be at e…”
Pomel: Major Datadog Investor Dumped All Shares When COVID Lockdowns Began
“Our lockup expired the day of the COVID lockdowns. So I don't know if you remember, there was a big market crash that day. It was also a lockup expiring. One of our biggest investors got scared and he dumped everything that day. So I think, I don't know, we're…”
Pomel: Public Stock Crashes Harm Tech Companies via RSUs, Not Operations
“Does it impact the company in the short term? No, but it creates a comp issue because people are paid in RSUs. So the main things you have to worry about is, okay, so what does it change to comp and how can we manage that?”
Pomel: VCs Spend Far More Time Understanding Companies Than Public Investors
“The VCs you have as a private company, they spend so much more time on your company There's so much more concentrated than the public investors. Like public investors have, they're looking at, you know, 20, 30 different names. They come in and out of these nam…”
Pomel: Datadog counts the top 10 AI companies globally as customers
“We have the top 10 AI companies in the world as customers.”
Pomel: Software engineering is inverting from mostly writing code to mostly automating
“The point here is it's an inversion. Like, you used to mostly write, sometimes automate, and now you're going to mostly automate
Sometimes, right.”
Pomel: Solo engineers using AI do six months of work in days
“We saw like literally, I mean, absolutely excellent developers, like not beginners, but people rebuild whole systems in a couple of days alone that were absolutely amazing. Things that would have been possible, but, you know, done by a team of six, over six mo…”
Pomel: European startups must enter the US market immediately after PMF
“On the other hand, I think it's absolutely critical
to go after the US market as soon as you can.
So as soon as you have a product with some form of market fit go after the US market.”
Pomel: Startups expanding to the US must relocate at least one founder
“I think the, you know, typically if there are two founders one of the founders moves to the U.S., and you cannot start in the U.S. Without, without having a founder there and you should absolutely go to the U.S. But I don't think you need to move the whole com…”