Lessons from Olivier Pomel

Olivier Pomel, the co-founder and CEO of Datadog, has quietly built a multi-billion dollar enterprise by focusing on solving real-world engineering problems. While not one for gratuitous self-aggrandizement, his interviews and talks reveal a wealth of knowledge for entrepreneurs, leaders, and builders. [1] From the critical early days of customer discovery to scaling a global public company, Pomel's insights emphasize a customer-centric, no-drama approach to business.

On Founding and Early-Stage Strategy

Don't start by coding. "For the first six months of the company, we didn't write a line of code, which took some restraint... we actually spent all that time talking to potential customers and potentials users." [2]
Your biggest fear should be building the wrong thing. "Our biggest fear was not to... manage to build software. It was to build the wrong thing... solve a problem that didn't exist." [3][4]
When you have no product, everyone wants to talk. "When you don't have anything to sell, everybody is super happy to talk to you." [2][5] Use this pre-product phase to genuinely understand customer problems. [4]
Early fundraising failure can be a blessing. "Failure to raise initially was what made us... all those constraints are how we built the culture of the company, how we found certainty about what it is we're building and for whom. We owe our success to that in a larger amount." [5]
Hardship builds a better business. "Anything that is a constraint or a hardship actually is good for the future if you survive it... you're more likely to make it later." [6]
The founding problem: bridging the developer-ops divide. The idea for Datadog came from direct experience with the friction between development and operations teams who "hated each other." [1] The goal was to create a shared source of truth to foster collaboration. [7]
A co-founder helps you persevere. "It's good to have a co-founder, because your lows are not completely aligned. So there's always someone to pull the other up." [5]
Solve the right problem, and solve it well. To build a lasting company, start by creating the best solution to a painful problem that larger competitors are overlooking. [8]

On Customer Centricity

Run towards the bad news. "My piece of advice is really, look for the bad news. You run towards the bad news... the first thing you do is you talk about it, you bring it up and then you actually hear directly from the customer what they have to say about it." [2]
Customer-focused is not sales-driven or engineering-driven. "Everybody wants to be customer-focused. The problem is that most companies end up being either sales-driven or engineering-driven and, if you want to be customer-focused, you can't be either of those." [2]
Stay subscribed to support emails. Pomel famously stays subscribed to all of Datadog's support emails to keep a direct pulse on customer issues. [9]
Month-to-month contracts keep you honest. "For a very long time we didn't sell yearly deals. We only sold month to month, meaning that customers had the opportunity to churn all the time... if something is wrong with a product... we know right away." [2]
Friction with customers is a learning opportunity. "There's still going to be some friction. But that friction is also how you're going to learn about the value of your product and about what would you need to do and where you need to go next." [2]
Customers want you to succeed. "They want your company to be in business two years from now. They want you to ship new features. So they really want you to be successful." [2]
Build with customers from day one. Datadog starts new product development with a small team that involves customers from the very beginning to figure out the real problem that needs solving. [3]

On Product and Engineering

Every product must be best-of-breed. "The goal with every single product we ship is in the end, on its own, even separate from everything else we do, it should be best of breed." [3][6]
Start new products small. "It's very hard to start new products... you need to go from being mostly successful to being mostly unsuccessful... the way it works is we're going to start with a team of 10 or seven or five." [3]
Success is broad adoption, not a feature checklist. "We're not actually in it to have the largest amount of features... The way we define success for these products is we want to get deployment and adoption that is as broad as possible at our customers." [1]
The platform is the real competitive edge. While each product aims to be the best, the true advantage lies in a broad, fully integrated platform that makes it "irrational for customers to mix and match tools." [4]
Infrastructure monitoring is the perfect landing spot. "That first product, that infrastructure monitoring, is the perfect place to land because it gives you a very large surface of contact with your customers environment." [5]
Product managers don't invent products. At Datadog, product managers are not tasked with inventing products but with ensuring the company builds the right things for customers. [2]
Show value on day one. "It's critically important to have low friction for products to be adopted and to show value... it's very important for whatever you have to work well on day one." [10][11]
Better data makes better AI. "Having better and more specialized data actually yields better results... when you think of where AI is going to go in the next few years, you have thousands of companies that have very good very specialized data and all that data is going to be put to good use." [12]
The shift to AI is a shift from writing code to building trust. "With applications that are mostly nondeterministic... you actually shift the problem from writing the code... to actually building trust in it and understanding how it's going to behave." [13]

On Scaling and Leadership

Go from being good at coding to good at not coding. "You have to go from being really good at coding to really good at not coding." [1]
To scale, you have to give up control. "I'm a bit of a control freak, but to scale a company you have to trust a lot of people and put them in control and give them enough room otherwise you're never going to get all these owners that build a company on your behalf." [1]
Hire executives who are peers, not subordinates. "People that report directly to me, I should be able to think of them as peers, they're not people I manage. If I have to manage them or their career, it's probably not the right fit." [3][6]
An IPO is a starting line, not a finish line. "The biggest misconception about an IPO is that it's an exit it's actually not it's a starting line not a finish line." [5][6]
Don't sell along the way. "To grow to a large company one of the hardest things to do is not to sell along the way." [1]
Build a business that is efficient from day one. "We were always super scared that we would not actually manage to raise more money. So we wanted to to build a business from the day from day one that was very efficient." [6]
Hire a sales team only after you know what you're selling. "When you hire a sales team, you need to have all that in place otherwise the sales team is not going to figure things out for you, you still need to do that yourself." [1]
Focus on the long term. When dealing with public market pressures, Pomel prioritizes long-term company growth, believing that if the company is built correctly, other aspects will follow. [5]
Parenthood improves time management. "Parenthood has made Olivier Pomel more disciplined with time management." [5]
Look for leaders who get in the details. "We're looking for people who can say, 'hey, let's go and look at what's actually happening on the field, talk to the customer, look at the details of the processes... and let's design the next version of it.'" [5]

On Company Culture

Maintain a "no jerk" policy. From the beginning, the founding team had a strict "no jerk" policy for hiring. [1]
Keep a low-drama culture. "Our culture is to be low on drama. We are here to learn. We want to help people build good products for customers." [8][14]
Don't have written-down principles. "We've never written it down. So we don't have like, you know, to have principles or, you know, seven values or any of that stuff." [3] The culture is embedded in the actions and priorities of the company.
Encourage people to keep growing. Datadog aims to keep smart people from plateauing by maintaining high standards and encouraging continuous learning. [8]
Accept feedback and be willing to do it again. "If someone tells you that something isn't right, it's important to accept that feedback and do it again." [8]
Efficiency is a core tenet. Born from early financial constraints, a focus on discipline and efficiency remains a core part of Datadog's culture, even after raising significant capital. [6]

On Building in New York

Building in NYC is an advantage. "It's actually probably easier to understand how to build the right product in New York than it is in the Bay Area." [12]
New York is more in touch with the real world. "New York is more of a normal city with normal companies... we actually credited the fact that we were more in touch with the the real world as one of the reasons of our success." [12]
The Bay Area can be an echo chamber. "In the [Bay] area... you hear something that you agree with it might very well be something that you said... three days ago and it just found its way back to you." [12]
Overcoming the "mental deficiency" of being in New York. "Whenever we pitched West Coast investors it was sort of seen as a form of mental deficiency to be based in New York and doing infrastructure." [1] This early skepticism ultimately didn't hinder their success.

On the Future

Every company will want automation. "The dream is you never have to wake up in the middle of the night ever again to fix an issue. The issue has been fixed for you." [11]
It takes time to find the right application form factors. "It took many years after the iPhone came out for all of the applications we're using today to emerge... that's because it took some time to zero in on the right form factors." [12] The same will be true for AI.
AI adoption may take longer than we think. "My worry is that it might actually take a little bit longer than we thought it might... because of the lag from humans. Customers have to understand what they're going to use and how they're going to use it." [12]
Security is paramount for AI adoption. Drawing a parallel to the cloud, Pomel believes that for AI to be widely adopted, the main fears around security need to be taken off the table so everyone can "build with confidence." [11]
There is an arms race in security. "We do see is really an arms race... especially with the progresses made in AI. Because if we can do more to automate the fixing of issues with AI, bad actors can do even more in terms of finding all these issues and exploiting them." [13]
The future is a mix of open source and proprietary models. "The market is a pretty healthy split between all of that because there's good use cases for all of those to exist. Any given company is going to use a mix of those." [12]

Learn more: