Infra Play #67: On Palantir and high conviction bets
In an industry full of largely anonymous and bland companies, led by “professional managers”, Palantir stands out in many ways.
[Source Photos: Palantir and Getty Images]
By popular demand, this week I’ll do a deep dive into Palantir. In an industry full of largely anonymous and bland companies, led by “professional managers”, Palantir stands out in many ways.
Largely hated by the media and professional investors, the company has embraced it’s role as the contrarian, going as far as even playing along with the retail investor community.
Today we will try to answer several questions:
What does Palantir actually sell?
How does their product tie into the future of Enterprise adoption of AI?
Is this a good opportunity for tech sales?
The key takeaway
For tech sales: Palantir has an exceptional product and deep domain expertise in driving LLM and Enterprise-grade ML adoption within customers with large scale projects. It’s also a company that deeply despises sales reps. Avoid at all costs until a structural change at leadership level.
For investors: I’ll not speculate on where the price of the stock will go because all bets are off when we are talking about a “darling” of the retail community. From a purely product and customer integration perspective, the company is one of the 3 strongest players in AI adoption today. The continued mismanagement of the GTM team raises significant questions around how sustainable growth is on a long enough time scale.
So is there an actual product here?
Some say there are three major unsolved mysteries in this world, namely: who really built the Great Pyramid of Giza, what is the meaning of life, and does Palantir even have a real product?
I highly recommend to go trough the insider view of Palantir by Nabeel S. Qureshi. This is how he experienced their approach to customers:
When I joined, Palantir was divided up into two types of engineers:
1. Engineers who work with customers, sometimes known as FDEs, forward deployed engineers.
2. Engineers who work on the core product team (product development - PD), and rarely go visit customers.
FDEs were typically expected to ‘go onsite’ to the customer’s offices and work from there 3-4 days per week, which meant a ton of travel. This is, and was, highly unusual for a Silicon Valley company.
There’s a lot to unpack about this model, but the key idea is that you gain intricate knowledge of business processes in difficult industries (manufacturing, healthcare, intel, aerospace, etc.) and then use that knowledge to design software that actually solves the problem. The PD engineers then ‘productize’ what the FDEs build, and – more generally – build software that provides leverage for the FDEs to do their work better and faster.
This is how much of the Foundry product took initial shape: FDEs went to customer sites, had to do a bunch of cruft work manually, and PD engineers built tools that automated the cruft work. Need to bring in data from SAP or AWS? Here’s Magritte (a data ingestion tool). Need to visualize data? Here’s Contour (a point and click visualization tool). Need to spin up a quick web app? Here’s Workshop (a Retool-like UI for making webapps). Eventually, you had a damn good set of tools clustered around the loose theme of ‘integrate data and make it useful somehow’.
At the time, it was seen as a radical step to give customers access to these tools — they weren’t in a state for that — but now this drives 50%+ of the company’s revenue, and it’s called Foundry. Viewed this way, Palantir pulled off a rare services company → product company pivot: in 2016, descriptions of it as a Silicon Valley services company were not totally off the mark, but in 2024 they are deeply off the mark, because the company successfully built an enterprise data platform using the lessons from those early years, and it shows in the gross margins - 80% gross margins in 2023. These are software margins. Compare to Accenture: 32%.
Tyler Cowen has a wonderful saying, ‘context is that which is scarce’, and you could say it’s the foundational insight of this model. Going onsite to your customers – the startup guru Steve Blank calls this “getting out of the building” – means you capture the tacit knowledge of how they work, not just the flattened ‘list of requirements’ model that enterprise software typically relies on. The company believed this to a hilarious degree: it was routine to get a call from someone and have to book a first-thing-next-morning flight to somewhere extremely random; “get on a plane first, ask questions later” was the cultural bias. This resulted in out of control travel spend for a long time — many of us ended up getting United 1K or similar — but it also meant an intense decade-long learning cycle which eventually paid off.
There are two main themes to unpack here, one is about strategy and the other one is about execution.
From a strategy perspective, the goal of the company was to gain access to customers with complex challenges trough it’s consultancy approach, then build custom applications that solved quantifiable problems. These became the foundation of their current platform.
While unusual for a Silicon Valley company, it’s also not a shocking idea in the context of the industries they targeted. I used to work for a niche tech company focused on planning and optimisation software that had a similar approach, except that it started with the “base” software and then developed custom implementations on top of this stack that became industry-specific products. The reality was that even when utilising those “products”, there was still a heavy element of writing new code for the individual implementation. Unlike Palantir, the company ended up being acquired because it struggled to scale above the $200M revenue and it’s heavy reliance on consultants was seen as a negative for growth.
The second theme is about execution. Unlike the company that I worked for, Palantir focused on hiring exceptional talent and then pushing them to the limits in order to solve big problems quickly at their customers.