The Ledger
Every statement that passed quotation and attribution checks. Mix any filter with any other: certainty 1/5, debate potential 5/5, or both at once.
why aren't all 47 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 0 checkable ones are still open, waiting for their date. predictions held up or didn't; assertions are supported or contradicted. on every card: ▮▮▮▮▮ certainty · ▮▮▮▮▮ debate potential. speakers are clickable
Pomel: Paul Graham's 'Founder Mode' essay will do more harm than good
“My worry about the founder mode, and everything that gets pulled down to a very short piece like that, is that I think it's going to be used and abused in all sorts of different ways, because there's so much context that goes into every single word in there, l…”
Pomel: Within five years, security will inevitably attach to observability
“We have a thesis that security, like, five years from now will be will be, or rather, let me rephrase it will be a no-brainer that you have to attach your security to your observability, because that is what gets deployed everywhere in your application, in you…”
Pomel: Cybersecurity software will consolidate into large platforms
“We think that it's too complex. Like, it's impossible for the customers to actually understand how to piece that together, and to integrate everything into a consistent whole that really protects them, and so we think that security is going to go through the s…”
Pomel: Month-to-month contracts beat multi-year deals for validating new products
“So for new products and new companies, I would argue, month to month is great. Because your customers can try at any time which means you'll get the hard reality to hit you in the face and you can't ignore it, you know, which is a problem when you have, so you…”
Pomel: AI will boost developer productivity by 10x to 100x
“And I think AI on top of that is going to give us maybe another order of magnitude or two in terms of, you know, what a human can produce functionally.”
Pomel: Datadog historically avoided 'AI' terminology, viewing it as 'bullshit words'
“For the longest time in the history of the company, we've been careful about using the words AI. We thought they were, you know, bullshit words mostly.”
Pomel: AI solves only 2% to 5% of systems management cases
“Right now we'd be lucky to solve, you know, two percent, three percent, five percent of the cases with AI.”
Pomel: Datadog's Toto model beats other models on observability and weather benchmarks
“This model from day one was state of the art, like, it's it beats all the other models, of course, on the, on observability data, we have special benchmarks from that, but also for other things like weather data which was very surprising to us.”
Pomel: Product AI chatbots require handholding as users struggle with prompts
“It works great for some use cases, but you need to handhold the users a lot more. Like, users don't necessarily know exactly what to ask for and how to ask for it, or what to go next, you know, once they've asked a question.”
Pomel: Many big tech AI assistants risk being too much like Clippy
“The risk right now is that a lot of the assistants we're seeing from the big companies are too close to Clippy.”
Pomel: Leading with AI in IT monitoring will inevitably disappoint
“It's very hard for what we do to lead with, you know, AI because you, you're bound to disappoint, because the generic case is very, very hard to solve”
Pomel: Customers say they want false positives but hate noisy software
“When you ask, when we first visited customers to figure out what they wanted from our product. When you ask them to pick between a false positive and a false negative they'll say, oh, give me the false positive, I'll decide if it's right, but I want to know. I…”
Pomel: European tech ecosystem remains fragile without large-scale companies
“I think we still have to see them scale to large companies in, in France, in Europe more broadly. It hasn't happened yet. So the ecosystem is still young, and I would say still fragile from that perspective.”
Olivier Pomel: Y Combinator rejected Datadog over lack of initial product
“We applied to all sorts of incubators, we got to a Y Combinator interview, and then we didn't get into Y Combinator. I have an email from Paul Graham that says You know, a platform is only as good as its first product, and you don't have a first product, blah,…”
Half of Datadog design partners drop off after pricing is introduced
“When the product is ready, when it's great, about half of the design partners just disappear.”
Datadog keeps struggling product teams small rather than killing products
“We did not kill products, but we, the way we do it is we start small, and we've waited a long time to scale up.”
Pomel: Negative customer feedback is the only feedback worth listening to
“The people who are used to scaling the products that work ignore the negative part, whereas it's the only part that's worth listening to.”
Pomel: AI shifts software value from writing code to understanding behavior
“Every time you add productivity, you add complexity, meaning that you have less and less of an understanding of what it is you're doing... So a lot of the value shifts from just creating that thing to understanding how it's going to behave, how it's changing o…”
Pomel: OpenAI's latest models remain early stage for reasoning capabilities
“There's more we can do maybe on the reasoning side, though I would say even with the latest releases from OpenAI, it's still fairly early in terms of the quality of the models and what can be done there.”
Pomel: Anomaly detection systems must prioritize avoiding false positives over false negatives
“The most important, when you do things like that, is to not generate false positives. So these systems tend to generate more false negatives than false positives. Basically, if the system is not sure it's probably not going to tell you anything, because if it …”
Pomel: West Coast VCs dismissed NYC-based infrastructure startups
“Whenever we pitched West Coast investors, like, it was sort of seen as a form of mental deficiency to be to be based in New York and, you know, doing it, doing infrastructure.”
Pomel: Effective technical content requires hiring engineers reporting to engineering
“In the end we ended up hiring full-time engineers who are also interested in journalism, and those people exist and have them basically focus on research and writing and we have a team basically that's built that way. It reports into engineering, it doesn't re…”
Pomel: Resisting acquisition offers is key to building a large company
“To grow to a large independent company, you, one of the hardest thing to do is to not sell on the way.”
Olivier Pomel: Startups must frame products within existing categories and spend
“You actually have to take your customers where they are and talk to them in terms that they understand in terms of their existing categories, their existing spend, existing solutions.”
Datadog rejects Apple-style secret product development
“We don't do it like Apple, like we don't disappear in a basement for three years and then, you know, ship a fully formed product that takes the world by storm. Instead, from the earliest days, like we work with design partners, we work with customers, and we t…”
Pomel: AI model observability will take years to fully flesh out
“So I think it's going to take maybe a few years for that category of observing the models themselves to fully flesh out in terms of what the use cases are, the needs and where they go.”
Pomel: IT teams won't manage AI separately from existing cloud infrastructure
“You are not going to manage your AI separately from your databases separately, from your network separately, from your security separately. Everything makes more sense when it is managed together and when we can assemble the full picture for you.”
Pomel: AI might resolve 20% of IT issues in a year
“Maybe in a year it's going to be 20%, maybe, but it's going to be gradual.”
Pomel: Observability log volumes grow much faster than customer revenue
“The biggest challenge with observability is that any application can generate any arbitrary large amount of logs. And so the data volumes grow much faster then our customers revenue”
Pomel: Datadog avoids dedicated AI labs because they set wrong expectations
“We, so we don't have a lab. In general, we're a little bit careful with labs. I think it's sets the wrong expectation.”
People quote 'Founder Mode' to disagree with Pomel's decisions
“I've already been on the receiving end of a few people quoting, quoting Founder Mode to disagree with things that we're doing, I was doing, so.”
Pomel: Datadog was founded to unify metrics, traces, and logs
“And one of the main reasons why we started a company was to bridge the gap between the different teams and break down the silos. It didn't make sense for us to have those things being separate and, you know, it turns out the problems actually don't stop at the…”
Pomel: Datadog starts with off-the-shelf software before building proprietary systems
“Well, we usually, when we build a new system or add a new data type, we usually start with something off the shelf and something open source. And at a small scale it's going to work. And then as we grow, as we get more and more data into it, as we see the many…”
Pomel: Datadog processes about 10 trillion records per day
“So we're talking about, like, 10 trillion records a day, something like that?”
Pomel: Commoditized monitoring tools succeed when bundled into broader platforms
“It's a category that is not necessarily super interesting on its own, you know, because it tends to be a bit commoditized and, you know, it's a little bit high churn but it actually makes a lot of sense as part of a broader platform, which is what we offer. So…”
Pomel: Datadog defines success by broad team adoption, not buyer purchase
“The way we define success for those products is we want to get deployment and adoption that is as broad as possible at our customers. You know, so again, going back to what we're trying to solve here, we want to bridge the gap between the teams and bring every…”
Pomel: Sales teams cannot figure out product positioning for startups
“When you hire a sales team, you need to have all that sort of in place. Otherwise the sales team is not going to figure it out for you. You still need to do that yourself.”
Pomel: Datadog raised launch price to $15 then $18 without metric impact
“When we launched a product we priced the product initially, we were going to price it at 12 dollars per, you know, instance, per month and then the night before we said, let's put 15. And. It was, I cannot disclose that. It, We put 15, it worked fine and, you …”
Pomel: IPO preparation is mostly about the following 18 months
“Most of the work you do there is really to prepare for the 18 months that, that follow the IPO.”
Pomel: Real competition comes from novel approaches, not late copycats
“If their plan is to do whatever you're doing, or a fraction of whatever you're doing, ah, four years later, ah, that's not where your competition is going to come from. Your competition is going to come from people who are trying to do it differently, and Are …”
Olivier Pomel: Datadog's largest enterprise customers pay tens of millions annually
“Our smallest customers, you know don't pay us anything, and they're individuals or students. And our largest customers are the largest companies in the world, you know, paying us tens of millions of dollars a year, and we'll have pretty much everything in betw…”
Pomel: Datadog splits engineering equally between core platform and specific products
“So yes, the breakdown is roughly half of our engineering team is on the platform, and half is on the is assigned to specific products.”
Pomel: Datadog was created to unify development and operations around shared data
“The starting point for Datadog was, no, there must be a better way. Maybe those people can talk to each other. And we wanted to build a system basically that brought the two sides of the house together. All of the data was relevant to both. Make sure they spea…”
Pomel: Datadog retains the last 24 hours of incoming data in memory
“The way we run it under the hood is that we're going to keep all of the data that's from the, let's call it the last 24 hours in memory so it can be accessed very, very quickly, and over time we age this data to various forms of, you know, colder and cheaper s…”
Datadog hired its first salesperson at under 30 employees
“We were, I think, a bit less than 30 when we hired the first salesperson.”
Pomel personally monitors customer tickets, closed deals, and employee feedback
“I see a large volume of the tickets our customers are filing, so I want to stay in touch with what's happening with the product. And I'm going to see all the deals we close, and I'm also going to read all the comments we get from employees in employee service.”
Pomel: Datadog never pivoted and built its original vision
“No, so we didn't pivot. So we were, it's a great question because when we didn't manage to fundraise initially we sort of gobbled the pitch quite a bit. We tried to turn it in different ways, and we thought maybe we'd, we'd do something a bit different, and we…”