Before a board meeting early in the history of Descartes Labs, I sat looking at my deck, realizing that it lacked a narrative. I sat down and penned my first board memo and produced one every quarter thereafter. I named it “Meditations” after Descartes’ most famous book, in which he secured reason in the eyes of God, providing the philosophical foundation for the scientific revolution.
Today calls for a different kind of Meditation, a song of lamentation.
Descartes Labs was on a mission to better understand our planet through satellite imagery. To enable such a lofty mission, we built a data refinery, a petabyte scale repository of satellite and other geospatial data combined with petaflop scale supercomputing power. Because of our platform, we attracted some of the best scientists from around the world, often fleeing universities and government institutions, looking for an intellectual island to do impactful science. Our Cartesians built some of the most remarkable demonstrations of technology I’ve ever seen in my career.
Even with almost $100m of invested capital (strangely, Crunchbase doesn’t list the last two rounds), >$200m in total going into the company (revenue+investment), ending 2021 with over $17m in revenue, and multiple 8-figure government contracts, the company was sold in a fire sale.
Writing that sentence is absolutely shocking to me. How is it possible that a company with an incredible team, so many successes, so much revenue, and so much invested into the underlying technology could possibly be worth close to nothing?
Given the wild ride of Covid and the economic rollercoaster ride we’re currently on, it’s easy to dismiss Descartes Labs as a victim of macroeconomic circumstances. I don’t believe that to be the case and will make the argument that there were two main reasons for the mismatch in the actual value of the company versus the price that was paid:
- The company was burning too much cash.
- The sales process was run poorly. (i.e., the process of selling the company)
At fault is the management team, who executed poorly, and especially the board, who knew these facts and chose to do nothing.
I’ll first dive into a bit of history about the company, since for the first five years — through a series of successes and failures — I was at the helm. After I was fired in January 2020, I have much less visibility into the day-to-day of the company, but will do my best to assess what happened.
Of course, I’m telling the story from my vantage point. I’ll do my best to be objective and honest, but any story written by a passionate founder ought to be read with a skeptical lens. I do hope we hear other perspectives and perhaps an objective third party can take on the challenge of synthesizing into an approximation of the truth.
I’ve been warned about writing this post, “You’ll never raise money from the Valley again…” The power dynamic between founders and VCs is asymmetrical. VCs have no problem firing a founder and being vocal about it, but when founders observe bad behavior from VCs, the advice is to shut up and find better investors next time.
The SAFE Note changed seed funding by preventing bad early-stage investors from injecting punitive terms into convertible notes. I believe there ought to be something similar for founders: a set of standards around compensation, severance, stock, and board structure. I’m going to make it my mission to collaborate with other founders and the VC community to build some kind of Bill of Rights for Founders.
Until then, here’s the story of Descartes Labs, how a remarkable geospatial startup went from flying high in orbit to end in a fiery crash back to Earth.
Anni Mirabiles: The Early History of Descartes Labs (2014–2016)
Descartes Labs defied common wisdom in our early days. We spun out of a National Laboratory, we focused on science instead of engineering, we chose to headquarter in New Mexico before it was popular to flee California, and we were able to attract coastal money to a state that had never produced a successful software startup.
After I helped sell Zite from CNN to Flipboard in March of 2014, I had a fantasy about going on sabbatical. After some travel, my plan was to move to NYC to do part-time consulting while I figured out my next startup. As fate would have it, I got a call from a friend who said that one of his friends (a semi-retired VC living in New Mexico) had been working with a group of scientists at Los Alamos National Labs (LANL) who were building a search engine for the video archives of large media companies. Imagine typing in “iraq bomb explosion” or “George W. Bush blooper” and getting hundreds (or, in the latter case, thousands) of results. Given my background in search, my 3 years at the helm of Zite within CNN, and my penchant for spinouts, it seemed like a perfect fit.
The market wasn’t responding well to their pitch. The scientists had been trying to raise money from VCs with fits and starts for at least a year before I met them. There was a term sheet from a prominent VC for a $15m series A, but those conversations and many others fizzled out.
Though I, too, was extremely skeptical of their business plan, I hopped on a plane to New Mexico on Bastille Day 2014 because I had been obsessed with The Manhattan Project since I was a little kid. When I met the cofounders, I was blown away by their brilliance and humility. Immediately after that first meeting, I knew we needed to start a company.
By the end of 2014, we had settled on satellite imagery instead of media search, we created a company, gave it a “temporary” name of Descartes Labs, raised $275k in angel capital by October, signed a deal with LANL, and closed a $3m seed funding with Crosslink Capital in December of 2014.
When VC is at its best, it deploys its capital against world changing bets, even in the face of uncertainty. Our deck basically said “We have some science! We have some smart people! Satellites are going to generate a lot of data that we think will be useful! Here are some verticals who might care!” The fact that we were able to circle over $3m of capital on such a risky proto-company gave me hope for a better future through technology.
Armed with a small warchest, I hopped in my car with a friend and drove to New Mexico to begin a new adventure.
For the first few months of 2015, the first order of business was setting up our digital laboratory. We got $100k in startup credits from Google Cloud Platform (GCP) and started collecting satellite data to run experiments. In March, my cofounders came up with what I thought was a wacky idea: they wanted to process a petabyte of data in under 24 hours, which would burn at least a quarter of our credits. For context, a petabyte is a million megabytes; an average photo on your phone is around 2.5MB. To me, it just seemed like a distraction, since there was no clear customer value out the other end; on the other hand, when you’re building a Lab, sometimes you just need to let the scientists play.
In mid-April, despite all odds, our team commanded 30,000 processors for 16 hours to complete what became known internally as “The Big Run.” I was absolutely astounded. So was Google. We got a call early on in the run because they thought something was very, very wrong, like a denial-of-service attack. After we begged Google not to shut down our calculation, we became friends. They sent out some folks later that summer to chat with us, beginning a long and fruitful partnership with their team, culminating in a visit by legend Vint Cerf in 2019. Not only were we the first startup in history to burn through our startup credits, we became the Southwest’s largest GCP customer. Of course, this isn’t necessarily a good thing because, as you’ll see, our cash burn contributed to our demise.
Now that we had done great science, it was time to take that computing power and data and build customer value. Hedge funds were a target in the early days of a company and we learned that they were hungry for alternative data sources to give them an edge, something still unique in 2015. Predicting global agricultural yields seemed like a reasonable use case given our core dataset, so we began Project Iowa, an attempt to build a corn-yield forecast for the US.
And did we ever! After releasing our predictions ahead of a very important US Department of Agriculture (USDA) forecast, we singlehandedly moved the market 3%, thanks to a well-timed Bloomberg article. Even though we moved the price in the wrong direction (2015 wasn’t our most accurate prediction), it didn’t matter. Big agricultural companies who weren’t returning our phone calls started answering and we were able to raise another $5m from AgTech VC Cultivian-Sandbox.
In 2016, we focused on selling our global agricultural yield forecasts. Cargill, the largest agricultural company in the world and largest privately-held company in the US by revenue (~$130b), approached us with a challenge: could we combine our data with their proprietary data to create better models for their agricultural supply chain business. After many months of hard work, Cargill decided to partner with us, becoming both a customer and an investor.
It’s hard to understate the importance of Cargill to Descartes Labs. Not only did the relationship provide revenue to the company, allowing us to raise a Series B and hire a lot more people, but the thought partnership between Cargill and our team helped us to figure out who we were. They realized before we did that the magic of Descartes Labs wasn’t in a SaaS product to democratize satellite imagery. No, we were a modern AI consulting company (cf., Palantir) who had assembled brilliant minds, built an internal set of tools that gave our scientists access to huge amounts of data, and created a collaborative internal environment to solve complex problems. You can see me and James Weed of Cargill speaking at Fortune Brainstorm Reinvent in 2018.
Another important relationship that began in 2016 was DARPA. We were awarded a multi-year $1.5m contract to investigate how geospatial data might be used to forecast famine in the Middle East & North Africa. Not only were we helping Cargill to feed the world, we started working on important social impact work.
By the end of 2016, we were feeling pretty good about defying the odds of being a New Mexico spinout of a National Lab. We were even profitable in Q4 2016, unheard of for a science startup.
Descartes Labs had become the Miracle on the Mesa.
The Descartes Labs Dialectic: Palantir or Salesforce? (2017–2019)
All the while, a debate was brewing within the company, known as the Descartes Labs Dialectic: are we building a product or a services company?
Descartes Labs crossed $10m of revenue in 2017, typically a massive milestone for software startups. The problem was that 90% of our revenue was in just a handful of accounts. Thanks to a brilliant cofounder in sales and a technical team to back up whatever custom deal was sold, we scored some really big wins for ourselves and for our customers.
The problem was that we hadn’t built any products yet.
Our corn (and eventually soy) forecast was a product of sorts, but we had trouble selling it. Proving that it had “alpha” (i.e., an edge that gives a trader an information advantage) was difficult and the value of a straight forecast was limited. I came to believe that selling data products was the wrong business model for AI startups. (A post from a16z penned by two of their partners in early 2020 is an even better statement of the sentiment.)
Another potential product was the underlying data refinery. Perhaps we were building a platform? We used it to great effect with our customers in building custom models for them. But, the companies that could derive the most value out of our platform were typically in commodities like agriculture, shipping, metals & mining, and forestry. They didn’t have the technical expertise to extract the full value out of the data or computing power within our platform.
We, like many AI companies like Palantir, were a hybrid consulting company: we built a robust platform that we were the best in the world at using and charged our clients lots of money for building unique, extremely valuable, proprietary (read: cannot be sold to others) models. Even if we structured the revenue cleverly by selling our customers a platform subscription and subscriptions to the models we built for them, we still weren’t a SaaS company.
If I could go back and change just one thing, it would be the resolution of the Descartes Labs Dialectic. I would have shut down internal debate in the company from the crowd that thought we should be building a software company. I would have been much clearer in our fundraising decks about what strategy we were pursuing: AI companies can build an enormous amount of enterprise value though specialized consulting contracts.
I succumbed to the market narrative, pushing startup founders to pursue a Software-as-a-Service (SaaS) business model.
To “solve” the Dialectic and package Descartes Labs as a software company, we separated the team into the Platform Team and the Applied Science team. The Platform Team built the tools and the Applied Science team built the models. Our typical customer engagement started off with a pilot project, usually around $100k, and our theory was “land-and-expand” (another popular SaaS trope): grow the small account into a much larger account, paying >$1m / year. Even though we were taking consulting contracts in the short term, in the long term, a product would emerge from the engineering team.
Or, at least that’s the theory on which we raised our $30m series B from March Capital in the Summer of 2017. Series B was another pre-emptive round, raised without me having to go through a full process and shake the money trees on Sand Hill Road. This new capital was intended to grow our sales & marketing team, build out our “product,” and move into a growth stage so we could raise a healthy series C.
Looking back on Series B, I’m conflicted. On one hand, I absolutely believe in taking money when it’s available. In 2017, we were 8 years into a bull run and we wondered how long the gravy train would keep running. On the other hand, when you take a big round, it’s important to be prudent with the cash and expand only when you believe that there is a viable business model. This requires investors and the company to be aligned around what constitutes product-market fit and what signals indicate that the business model is ready to be scaled.
In 2018, we scored a few minor wins, which kept our revenue up and to the right, close to $20m. Thanks to superior performance against our original DARPA contract, we were able to translate that contract into a much larger deal to build a geospatial data refinery for the government, in a contract worth up to $7.2m. We also made a considerable amount of progress booking pilot contracts from $50-$150k, not bad for initial projects. For 2019, our plan was to continue that pipeline of pilots and translate some of those pilots into large, multi-year 7-figure contracts and we’d be flying high.
However, by the end of 2018, we realized that our land-and-expand thesis was encountering roadblocks. We were losing money on pilots (read: negative gross margins) and translating those pilots into larger deals was difficult. Predicting revenue was nearly impossible (read: not a repeatable business model), driven by long lead times and uncertainty around how much value our pilot projects would deliver to the customer.
Things got dicey around our Q4 2018 board meeting, where we presented our 2019 plan. We projected that 2019 would be a 50% increase in revenue year-over-year, given that we hadn’t quite figured out our sales process or product . The board was not pleased, they wanted to see a much steeper growth curve.
Now the Descartes Labs Dialectic reared its head. Our investors wanted us to be a SaaS company with SaaS metrics and SaaS growth. We simply were not. We should have structured our entire business around being a high-end consulting company. Perhaps we wouldn’t have gotten SaaS multiples. Perhaps. Or perhaps we would have focused our energy on what we did best. I’d rather have $100m / year of long-term consulting contracts than burning expensive venture capital on a fantasy SaaS product.
Ultimately we capitulated to the board’s desire for an unrealistic revenue expectation because, in my mind, isn’t that what I signed up for when I raised the money? Unfortunately, it caused the company to focus on improbable but high-value deals instead of getting our product philosophy and sales strategy in order. By pushing us into unreasonable growth expectations, the board drove us to hit our numbers in the short term, not build a long-term engine for growth.
2019 admittedly was not my best year as CEO. We had grown very quickly and our leadership at the time didn’t have enough experience to manage that growth. Further, hiring in New Mexico was extremely difficult. We got really lucky in hiring two experienced Silicon Valley executives who both came to New Mexico thinking they would retire, but were seduced by our mission. Each influenced me greatly and I’m thankful to this day for their wise counsel. That being said, I badly needed an operational CFO to help me understand the numbers. My comparative advantages are building a vision, imagining what products emerge from a set of technologies, and raising money for a company. How that money is spent is not my forte and I needed the right kind of experienced help. With a requirement that this individual had to live in Santa Fe, I missed out on a number of opportunities to build up my leadership team and didn’t find anyone until September 2019.
About halfway through 2019, the board and the company knew that hitting our sales numbers was unlikely, since the number was dependent on either closing some highly-speculative commercial deals and a single government contract. The commercial deals didn’t close and we lost the government contract, despite signals that we were going to win it continuing up until the 11th hour. Despite all of this, we were able to close another $20m investment in late 2019 to extend our runway at $200m valuation.
The board decided that it wanted to be “helpful” and deployed someone to be part-time embedded within the company. Despite limited operational experience, the “help” built a separate financial model that utilized SaaS metrics and expected us to abide by that model.
The board had chosen the wrong path in the Descartes Labs Dialectic. By golly, they valued us at SaaS multiples and we were going to be a SaaS company!
I got the call in November 2019 that the board had decided to fire me. The stated reasons were: our burn was too high (~$1m/month), we missed our sales projections for 2019, and I was slow to hire experienced executives. All of that was true. However, firing the founding CEO is a huge disruption to a company and needs to be thought out carefully. Not only does the founding CEO know the company better than anyone else in the world, but they have the incentive structure to fight like hell to make sure a company survives.
Many CEOs have issues when they cross 8-figures in revenue, balloon to over 100 employees, and are figuring out how to manage a company. To this day, I feel that the punishment simply doesn’t fit the crime and I’ve never gotten an explanation. The reality was that we have over $20m in revenue and when we needed to extend runway, I was able to raise more money. Descartes Labs was still, by any measure, an incredible success.
Their exit “plan” for me was rushed: they wanted me out within a few weeks, akin to walking me out the door. They were going to put the CFO, who had only been there two months, in charge of the company until they could find a new CEO, though they weren’t planning on telling the CFO that he was going to be temporary.
I was feeling burned out at the end of 2019 and would have accepted a transition plan where we agreed that I’d cut costs and aggressively search for a replacement CEO. That plan would have saved the company $10m over the course of 2020: I could have surgically removed both cloud and people costs from the company to reduce burn while we found new leadership.
Another option, completely rejected by the board, was to take a step back and decide whether we were even in the right business. Maybe we shouldn’t have gone down the SaaS route, reduced our headcount, and focused on high-margin consulting deals. Maybe the satellite data business wasn’t as robust as we had originally thought. Maybe our assumption about growing to $100m in ARR was wrong in the first place.
An option never considered was to sell the company right then and there. Given that we had just raised at a $200m valuation and that the market was still hot, I could have initiated an acquisition process and likely sold the company for greater than $200m, given our incredible team, client list, and demonstrations of scientific prowess.
The board resisted a dialog and I capitulated. Seeing that I had lost, I tried to play the game. I prepped an exit, hopped on a plane to Davos (we were a 2019 WEF Technology Pioneer) and passed the baton.
The Post-Founder Era (2020–2022)
My visibility into the company was limited for the next few years. Though I sat on the board, I did my best not to talk to current company employees, to give the new CEOs enough freedom to operate without a shadow CEO poking in from the outside. I joined the committee to select a new CEO, though I knew that I was only there ceremonially (make no mistake: the investors will choose your replacement) and to convince the incoming CEO that a large common shareholder wasn’t going to be a thorn in his side. We hired and installed a(nother) new CEO in July of 2020.
An irony of 2020 was that a major reason for firing me was having a high burn, slightly north of $1m/month when I left. Our burn continued uninterrupted in 2020. Indeed, the burn during the last quarter during which I was CEO was the lowest burn for the remainder of the life of the company.
A condition of the new CEO joining was that the existing investors would invest another $20m (somehow, neither this nor the $20m I raised at the end of 2019 are on Crunchbase), which made sense given the need for more runway, but also added significantly to the preference stack. Also, it tapped out our investors–they had no more money they were willing to commit to the company. For example, Descartes Labs was the single biggest cash investment in the history of Crosslink Capital and they couldn’t write another check.
I was asked to leave the board at the end of 2020, which worried me terribly since there would be no common shareholder or founder representation on the board. Since I had a chunk of stock options that would expire within 90-days without a relationship with the company, I brokered a deal to leave quietly in exchange for maintaining those options until the sale of the company. Plus, it really didn’t matter because, if the investors don’t want the founder on the board anymore, they will find a way to eject you.
As I was leaving the board, the stated plan was to try to become cash-flow positive within a year. The new CEO was going to manage to cash and, if we weren’t able to hit our numbers, he would cut costs every quarter. In my opinion, his operational plan to grow the businesses was a rehash of ideas we had already tried, but I gave him and his new leadership team the benefit of the doubt. Perhaps with better leadership, they could achieve the meteoric growth that I was unable to execute.
The new CEO had quarterly meetings with me so I could keep abreast of what was happening with the company. It seemed like we were going to win an extremely large government contract by the end of 2021, which did occur, even though it was a few months late. Sometime in the Summer of 2021, it was decided that the company would sell. The bankers began pitching the street with a ridiculously high valuation of $800m.
What was I up to during this period? In another aborted sabbatical, I took a month or two off to ski, but as Covid started descending on the world, I decided to move to Omaha to lead GrainBridge, a joint-venture between ADM and Cargill. The vision was to use data from the two companies to help farmers become more profitable, an agricultural data refinery. Over the next 18 months, I’m really proud of what the team built. We immediately cut burn, released a product, built a product development machine, and decided that the best way to pursue our mission was to sell the company to Bushel.
While I was celebrating in Omaha, Descartes Labs was in a downward spiral.
An Unnecessary Implosion: Burn, baby, burn
I only got a trickle of information from October 2021 until April 1, 2022, when I received a phone call from an angry board member. The company was about to run out of cash, hadn’t billed a single penny against a massive government contract we had won, had missed numbers every quarter, and was burning an astonishing $2.3m each month. Even worse, I was informed that the acquisition process had been botched and it seemed like the company didn’t have any options.
I was flabbergasted. How could a company that ended 2021 last year with over $17m in revenue be close to folding? I started calling around: investors, current & former employees, and customers that I knew. I went from being flabbergasted to horrified. Everyone–including board members–agreed that the company and the sales process had been grossly mismanaged. Though the details I uncovered are shocking, they aren’t important to this narrative.
The number one job of a CEO is not to let a company run out of money. Burn had been steadily increasing quarter-over-quarter. Cloud costs had ballooned to ~$800k/month. Hiring had continued, despite an inability to deliver revenue. Why did they not cut costs? The reasoning from the CEO to the board was that a RIF during an acquisition process would be bad optics. That calculation was irresponsible and incorrect: acquirers had to consider not only the acquisition price, but the cost of running the company over the coming years. If an acquirer thinks that the cost of servicing the revenue is greater than the actual revenue, that’s a turnoff.
I quickly wrote a plan for the board to reduce costs and reboot the acquisition process. I didn’t relish this idea, since it would be a lot of work, and I was otherwise occupied. However, it was my duty to the company, our investors, and to our common shareholders, that is, all of the Cartesians who were either working at the company or had worked for the company in the past.
The board rejected the plan because they felt like they had bet on the current management team. Even though I believe I could have run a sales process ending in a price that reflected the true value of Descartes Labs, I do understand their logic. In reality, the board should have seen in Q4 of last year that we were going to run off a cliff in 2022 and, if the CEO refused to cut costs, they should have fired him then. Letting the company run towards a cliff of insolvency was a massive breach of the board’s duty.
I continued to watch from the sidelines. With Descartes Labs running out of money and few sales options, Descartes Labs, despite all of its value, was sold to Antarctica Capital for basically nothing. Existing shareholders got only a small percentage of the new company.
In the end, I’m still proud of Descartes Labs, a New Mexico-based science spinout with a broad and important mission to better understand our planet through data. We attracted some of the best scientists in the world. We performed remarkable technical feats, many of which translated into enormous value for our customers. Very, very few startups get as far as Descartes Labs did.
That makes the past 2.5 years so bitter for me and all Cartesians. So many people put their trust in Descartes Labs: investing when we were just an idea, leaving comfortable jobs at universities and labs, moving themselves and their families to Santa Fe, committing their best years to the company. Many employees bought their options as they left the company; tens of millions of dollars of their equity went up in flames because Descartes Labs almost ran out of money.
To me, the most painful part of the Descartes Labs flameout was that it could have been avoided. The board acted aggressively exactly when they should have had a sober and reasonable plan. When the house was clearly on fire, they seemed to run around screaming about the house being on fire, but worried they’d get burned if they threw any water on it. One can blame the leadership of the company, but ultimately it’s the board that hires and fires the CEO. The unconscionable burn forced a firesale, leaving all shareholders in a worse position.
I’m sure there are many angles to this story and I welcome alternative perspectives. However, even though I’m sure that I got some things wrong, there’s one thing I’m absolutely sure of: this didn’t have to happen and the blame lies primarily on the investors.
I’ll still be rooting for Descartes Labs, even as a minor shareholder. More importantly, I want to fight for the rights of founders and startup employees. If the story of Descartes Labs resonates with you as a founder: if the board intervened in your company and destroyed value, I’d love to talk to you.