SFTW Convo with Michael Stern
Welcome to another edition of “SFTW Convos” with Michael Stern, ex-CEO of The Climate Corporation. Currently, Mike works as an advisor and board director focusing on agriculture and food. He spends his time between Michigan and St. Louis.
Mike has had a long career in agriculture. Mike became CEO of The Climate Corporation in 2014 following a transition period with founder and CEO David Friedberg after it was acquired by Monsanto for almost a billion dollars. The acquisition put digital agriculture on the map and kicked off an era of increasing investments in the space for the next 8-10 years. VC investment has been trending down over the last few years.
Mike lived through the early days of digital agriculture and has the scars to show for it. He is a very thoughtful and articulate leader, with a keen sense of where things might be headed when it comes to agriculture.
I had been wanting to have this conversation for quite some time to understand how decisions were and are made about strategy, go-to-market approaches, customer segmentation, technology selection, and talent management. Mike and I touch on all of these topics and much more in this conversation.
Please enjoy getting inside the mind of one of the OGs of digital agriculture!
Summary of the Conversation
Mike Stern discusses the acquisition of Climate Corporation by Monsanto, exploring the motivations behind the acquisition, the assumptions made at the time, and the challenges faced in integrating digital technology into agriculture. He reflects on the impact of this acquisition on the ag tech ecosystem, the importance of distribution channels, and the role of venture capital in funding agricultural technology innovations. He discusses the complexities and challenges of funding and developing technology in the agriculture sector. He emphasizes the importance of understanding the unique dynamics of ag tech compared to other industries, such as fintech and biotech. The conversation covers the role of venture capital, the necessity of partnerships , and the potential for innovation in ag tech, particularly in light of climate change and population growth. Mike reflects on the lessons learned over the past decade and expresses optimism for the future of ag tech, highlighting the need for clear value propositions and effective problem-solving.
Michael Stern, ex-CEO of The Climate Corporation (Image provided by Mike Stern. Artist rendering by EI)
Reflecting on Monsanto’s acquisition of The Climate Corporation
Rhishi Pethe (RP): Mike, thanks so much for taking the time to have a conversation with me.
Michael Stern (MS): Thanks for having me.
RP: AgFunder did a podcast marking the 10th anniversary of The Climate Corporation acquisition, where we heard from David Friedberg about his thought process at the time. You were on the other side of that transaction, representing Monsanto.
In that conversation, Friedberg acknowledged some of the complexities and challenges that came with the acquisition and what ultimately unfolded. I’d love to hear your perspective from the Monsanto side.
What was the hypothesis going in—both from the company’s standpoint and from your own as an individual in this role? What were you thinking at the time, and how did you reach the conclusion that this was the right acquisition for Monsanto to make?
MS: Monsanto started thinking more broadly about data and precision agriculture around 2009 or 2010. That was when we made the decision to acquire Precision Planting. We were beginning to recognize that precision agriculture was evolving and that its future would likely be driven by data and new technology.
The acquisition of The Climate Corporation was really driven by the realization that we were collecting a massive amount of data—both through our breeding and technology programs. At the time, we were probably one of the most advanced gene sequencing companies in the world because we were sequencing all of our seed products. We were doing marker-assisted breeding, and beginning to make early selections in our breeding program in silico before moving to physical trials. On top of that, we had extensive field-based agronomics, testing our products in real-world conditions. So, we also had this vast network of data coming in from the field.
Then there was The Climate Corporation, which was focused on data but from a different angle—integrating weather and other factors. Initially, their work was centered around insurance, but as we started talking, we saw the potential to use their capabilities to provide deeper insights beyond just insurance.
Remember, this was back in 2013. Big data was just starting to gain traction, and AI, as we know it today, wasn’t even a widely used term yet. Some people were talking about machine learning, but it was still in its early stages. However, it was clear that data and computational technology were beginning to influence other industries, and we saw the potential for agriculture.
So, we took a step back and said: We probably have one of the largest agricultural data sets in the world. We've already made massive investments in technology, and we’re going to keep generating more data. Meanwhile, The Climate Corporation was utilizing large data sets and had deep expertise in data engineering, data science and even developing early agricultural apps—something that was virtually nonexistent in the industry at that time.
We believed it would be a powerful combination. We had direct access to farmers and distribution channels—we were the largest ag company in the world. We were generating massive amounts of data. And the writing was on the wall: data was going to drive the next wave of agricultural innovation. We didn’t know exactly what that would look like yet, but we knew that bringing together these two highly complementary companies would accelerate our ability to develop new tools and create more value for farmers—helping them improve yields, produce more with less, and leverage data in smarter ways.
Trying to do this on our own would have been too slow and too complex. Plus, we were based in St. Louis, while the talent pool for this kind of advanced data work was in San Francisco. The industrial logic behind the acquisition was clear: by combining the strengths of both companies, we could pioneer something new and create value for farmers..
In a way, this move was classic Monsanto. If you look at our history over the previous 15 years—driving biotech, accessing germplasm, advancing marker-assisted breeding, and innovating at the genetic level—it was always about staying ahead of the curve. This was the next step in that evolution.
RP: That makes sense. Was the push to adopt this newer, data-enabled approach primarily coming from within Monsanto, or were you also hearing it from your ecosystem—retailers, farmers, and other partners?
Was this shift purely internally driven, or were there external signals influencing your decision? Were you looking at trends in other industries as well?
MS: We were definitely looking at other industries, and you could start to see how data—and "apps"—were transforming connectivity with consumers. Smartphones were enabling broader, more seamless interactions than ever before, across a variety of sectors. You could already see this happening, not just with social media platforms, but also with banks and other industries that were shifting toward more personalized, digital interactions.
For us, it became clear that the way farmers engaged with information and decision-making would eventually follow the same path. Instead of relying solely on an agronomist or a salesperson standing in front of them, farmers would increasingly access insights and make decisions through their phones or computers. We didn’t know exactly when that shift would happen, but we could see the early signs.
At the time, though, this trend was still relatively quiet in agriculture. In fact, we originally came across The Climate Corporation through their weather app. Our venture capital arm had been active in biotech investments related to agriculture, but we also kept an eye on emerging technologies. While there was already significant venture capital flowing into gene sequencing and biotech, the idea of AgTech in a digital, data-driven sense was still in its infancy.
By 2012—and leading up to our acquisition in 2013—there weren’t many investors focused on AgTech from a digital or data standpoint. It was still a quiet space. But as we started conversations with David and The Climate Corporation, we saw the potential for their work to create real value in the future.
The acquisition wasn’t something that came from an external recommendation. It wasn’t like someone came to us and said, “Hey, you should buy this company.” It was an organic process. We identified Climate within our own ecosystem, started a conversation, and gradually began thinking about how their capabilities could align with our vision for the future.
RP: And it's been about 10, 12 years now since that happened. And you took on the role of CEO and head of digital farming after that. And as we talked about earlier, you went in with a certain set of assumptions. You're not clear what the timelines would be, but you could see that trend looking at other industries. So now as you reflect back on that, what were some of the assumptions that you had made at the point of that acquisition or right around that time, which you think have turned out to be true and which of them turned out to be less true or not true?
MS: The premise at the farmer level was that the data farmers were collecting wasn’t digitized in any meaningful way. Maybe they were starting to get data off their equipment, but it was stored on thumb drives. A lot of it was still just paper records. The idea was that, given advancements in digital technology—phones, computers, data storage, and accessibility—there had to be a way to help farmers digitize their operations.
We knew from our own sequencing experience—where every plant, every seed was being analyzed and consolidated—that having all that information in one place created immense value. So, why wouldn’t the same principle apply to farmers and their agronomic data.? Why wouldn’t organizing and digitizing their data create value?
The concept was that if we could find a way to make that happen, and if there was value in it, farmers would be willing to share their data with us because we were helping them make sense of it. And in turn, we could use that data to build models that would create even more value for them. That was where The Climate Corporation was on the cutting edge. We saw an opportunity—we could help collect that data and put it to use.
The fundamental premise of digitizing the farm—helping growers organize their data so they could make better decisions—was absolutely correct. That was the key driver behind Climate’s early growth, as well as other acquisitions we made in this space. But the first challenge was figuring out how to actually gather that data. Unlike Monsanto’s own lab-generated data—where we built the systems and had full integration—we were now dealing with data from tens of thousands of individual farms.
We believed that simply helping farmers organize their data would create value. And in many ways, that assumption proved true. You can see that even today. FieldView, the platform we eventually launched, was incredibly successful and continues to be widely used because it does exactly that—it organizes farm data in a simple and effective way.
That said, there were a couple of things we underestimated.
First, the complexity of the data. We knew we needed to bring together multiple data layers, but actually structuring that data in a way that allowed us to build meaningful models turned out to be far more difficult than we expected. Farm-level data is highly variable. We knew that from our agricultural research, but integrating field data with other layers—like weather and soil data—quickly became a much bigger challenge than anticipated. We underestimated the time, cost, and talent required just to organize the data, let alone create value from it.
Second, even after organizing the data, generating insights from this data that farmers found valuable enough to pay for was harder than we thought. I still believe there is tremendous potential in digital agriculture and large-scale farm data, but the challenge was identifying the "killer apps"—the must-have tools that provided clear, tangible value at the farm level. Farmers had already invested $300 for a bag of seed, and we were now asking them to pay more for recommendations on how to use that seed. Understandably, many of them pushed back, saying, “Wait a minute—you’re charging me for the seed, and now you want to charge me again just to tell me how to use it?” In hindsight, that resistance makes complete sense, and we probably should have anticipated it.
One way to solve this could have been offering prescriptions for our own seed for free while charging for recommendations on competitor seed, like Pioneer. But then that introduced another issue: If Monsanto owned Climate, would farmers trust us to be unbiased? Would they believe we were providing the best recommendations for Pioneer seed, or would they assume we were favoring Dekalb? These were real concerns, and looking back, they make perfect sense.
At the time, though, we were in the thick of it—trying to figure things out in real time. These challenges weren’t obvious at the outset, but they became clear as we moved forward. We were trying to solve problems on the fly, in a brand-new space, while also convincing farmers (and ourselves) that we were delivering real value from a vast and complex data set.
Go-to-market for The Climate Corporation
RP: Yeah, no, that’s really interesting. I have two follow-up questions on that.
First, you mentioned the challenge of a farmer sitting there with a bag of seed and wondering, “Why do I have to pay extra just to be told how to best use it?” Looking back now, that’s a clear friction point—but when Monsanto initially acquired Climate, the business model was built around having a direct relationship with the farmer.
Since then, a lot of people have rethought that approach, questioning whether direct-to-farmer is the best model. Maybe there needs to be an intermediary—whether that’s a retailer, an agronomist, or another partner in the value chain. How do you think about that now? And at the time of the acquisition, how was the decision made to go direct rather than working through existing distribution channels?
MS: I would say it was more nuanced than that. We were open-minded about our approach, largely because of how our business was structured. Having led the business in the United States and across the Americas, I understood that we had always operated with a multifaceted, multi-channel strategy. We had seed brands that sold directly to farmers and national brands that sold through retail.
Because of that, we knew we had to develop a model that could serve both channels effectively. Initially, we leaned toward a direct sales approach for two key reasons. First, we saw this as a more technical sale, requiring direct engagement with farmers. Second, we recognized that if we wanted retailers to support and sell this technology, we had to get them comfortable with it—not just from a technical standpoint, but also in terms of value creation and revenue sharing. After all, that’s how retailers operate; they sell a bag of seed on our behalf, and we compensate them accordingly.
So, starting with a direct model made sense. It allowed us to figure out how best to engage with farmers without relying on a middleman. But as we gained more experience, the team collectively came to the realization that if we truly wanted to scale quickly, we had to fully leverage our existing distribution network. And the reality was that the majority of our sales flowed through retailers. That meant we had to find a way to integrate them into the FieldView ecosystem and get them fully on board.
We approached this in a few different ways—sometimes using incentives, other times taking a more hands-on approach to collaboration. Different retailers had different levels of interest and willingness to engage, but we saw getting them on board as essential. By this point—two to three years after acquiring The Climate Corporation—the broader AgTech and digital agriculture space had exploded with venture capital investment, largely catalyzed by our acquisition. We knew that in order to stay ahead in the farmer data acquisition race,, we needed to scale fast. That meant getting as many farmers onto our platform as quickly as possible, which required retailer buy-in.
The advantage of bringing retailers into the fold was immense. Once we got them on board—through a combination of education, incentives, and direct support—it became clear that we could achieve significant leverage in the marketplace. At Climate in the U.S., we had about 30 regional sales reps who worked alongside 500 Monsanto area business managers. Those business managers, in turn, interacted with and supported roughly 7,000 retail sales reps and agronomists..
So, instead of just 30 sales reps pushing FieldView, we were effectively leveraging a network of 7,500 sellers. That scale was critical, not just for accelerating adoption but also for securing our competitive position. With so many new AgTech solutions emerging, we knew that if we could align our distribution channels early, it would be extremely difficult for competitors to displace us.
And that strategy paid off. We went from a few million acres in the US to 150 million acres across 23 countries in just six years. That rapid growth was directly tied to our ability to integrate FieldView into our existing distribution infrastructure—adjusting the approach for different markets, but always applying the same core concept.
Image generated by ChatGPT “A new CEO pondering the use of digital agriculture and data” (Artist rendering by EI)
The impact of the acquisition
RP: Yeah, I think distribution is critical in any industry, but especially in agriculture.
You mentioned that the acquisition of Climate led to a wave of VC investment. Before that, AgTech was barely a category—maybe it existed in a small way, but the acquisition really accelerated its emergence as a distinct sector.
Can you talk more about that shift? How did the Climate acquisition change the perception of AgTech, and what impact did that influx of venture capital have on the industry?
MS: AgTech VC was mostly focused on biology. When people said AgTech, they were thinking genetics as opposed to digital ag. The Climate acquisition by Monsanto changed this. Now the largest Ag company in the world was investing heavily in digital agriculture.
RP: The whole digital side of agriculture really took off because of that acquisition. That was the immediate impact—or at least what unfolded in the years that followed. Looking at the long-term impact, even with all the assumptions that didn’t play out exactly as expected, what do you think Climate Corporation’s lasting effect has been on the ecosystem?
It’s become somewhat fashionable to criticize farm management systems—people say they don’t work, they’re not a good business, and that direct-to-farmer models aren’t viable. But beyond those critiques, what are the broader implications of how this all played out? Are there positive takeaways from the Climate acquisition and the digital ag movement that are shaping the future in ways we might not have anticipated?
MS: First of all, it absolutely catalyzed a lot of investment. Within months of Monsanto spending a billion dollars to acquire The Climate Corporation, the landscape started to shift. Most of the big ag companies already had venture capital arms, but they were primarily focused on ag biotech. This acquisition opened up an entirely new avenue—suddenly, digital agriculture was seen as a transformative technology platform.
It also brought more scrutiny. The major players—DuPont Pioneer, Dow, BASF, Bayer, and the other multinationals—started paying closer attention. Several of them made their own acquisitions, each exploring different approaches. But beyond that, I think it fundamentally shifted how the broader venture capital community, particularly in San Francisco, viewed agriculture.
This wasn't just about ag—it was about food, which is an enormous industry. Even if you looked strictly at agricultural inputs on a global scale, the market was massive. And from a venture capital perspective, it had all the hallmarks of a sector ripe for digital disruption: a huge total addressable market, geographic diversity, and an industry that had been slower to adopt digital tools.
I think what really changed was that a whole wave of investors who had never considered digital ag before started seeing the potential. And of course, when there’s capital available, there are always entrepreneurs with ideas.
The good news is that this surge in investment led to a wave of technological exploration in agriculture. As with any industry, some ideas worked, and some didn’t. But it opened the door for broader thinking, gave entrepreneurs access to capital, and accelerated the push to improve farming technology. And that, in the long run, is a good thing.
Is Venture Capital the right model for AgTech?
RP: Yeah, I think this is a good follow-up to that discussion.
There’s been a lot written and said about whether venture capital is the right financing model for AgTech. Some argue that it isn’t well-suited for the sector due to long adoption timelines and the challenges of scaling in agriculture. Do you agree with that argument? If so, why? If not, what makes VC still a viable model for AgTech? And if VC isn’t the best fit, what alternative financing mechanisms should entrepreneurs in AgTech be considering?
MS: I don’t buy into the argument that the venture capital model is inherently the wrong fit for AgTech, but I do think there’s been a lot of learning in this space. One of the biggest challenges—one that often gets overlooked—is the mismatch between the time horizon of venture capital expectations and the speed at which digital agriculture/Agtech can deliver measurable value. You touched on this, and I think it’s critical to unpack.
The simplest way to frame it is this: If you’re a venture-backed digital AgTech company providing agronomic insights to growers—like many startups in this space—you essentially have one shot per year to prove your value. That’s a broad generalization, and there are some evolving models we could discuss, but if you’re dealing with on-farm, data-driven agronomic recommendations, the reality is that results are tied to a single growing season.
And the truth is, you’re not always going to get it right—no matter how good your planning and technology was.. There are simply too many variables beyond your control. A farmer could follow your recommendations perfectly, but if there’s a drought or other extreme weather event, their yields might suffer. If your users have a rough year due to circumstances unrelated to your product, it becomes nearly impossible to demonstrate a clear value proposition. That means you’ve effectively lost a year of proving your ability to create value on their farm..
Now, let’s say you’re burning through $10 to $12 million annually—fairly typical for a AgTech startup. That lost year puts you in a tough position when it comes time to raise your next round of funding. You don’t have meaningful growth to show, your dataset is still limited, and your ability to scale is unclear. Compare this to a FinTech or consumer facing app where user engagement happens daily or even hourly. In AgTech, you don’t get that kind of immediate feedback loop—progress is much slower and more iterative.
So while I still believe venture capital is the right funding model for AgTech, the key is having the right time horizon. That also means not every VC firm is suited to invest in this space. I have yet to see an AgTech startup that hasn’t faced significant challenges along the way. Even if a company has a strong first year, they’re still small. Beyond proving their technology works, they also have to figure out distribution—whether that means engaging retailers or going direct to farmers.
And then there’s the adoption curve. Farmers are independent business owners managing risk. If they plant 1,000 acres, they’re not going to test a brand-new tool across their entire operation in year one. Maybe they’ll try it on 10% of their land. If the results are good, they might scale up to 25% the next year. But if the results are just marginal—or if they have an off year due to external factors—they may decide to sit on the sidelines for a season and wait until they see stronger proof. This makes AgTech adoption a much longer and more variable process than other industries.
So yes, I believe venture capital is the right approach, but it requires investors who understand the unique challenges of AgTech and are willing to be patient. When there’s a mismatch between VC expectations and the realities of the agricultural cycle, it creates real problems.
RP: Yeah, but don’t the same constraints apply in a biotech scenario? Let’s say you’re developing a new variety or trait—there’s still risk involved. You could have a bad year due to drought, and suddenly, the new trait doesn’t perform well. Farmers are still going to start small, maybe testing it on 5% of their acres before scaling up.
All those same conditions—uncertainty, slow adoption, and the need for multiple seasons to prove value—apply to biotech as well. So why is it viewed differently when it comes to financing models for AgTech?
MS: Well, a lot of biotech falls into different categories. In agricultural biotechnology, some of it is purely technique-based—things like finding better ways to insert a gene into a plant. We’re seeing a lot of that now with gene editing, but even before CRISPR and similar technologies, there was significant innovation in sequencing and genetic modification techniques.
Beyond the techniques, biotech also includes the development of new traits. For example, if a company developed a new trait that kills pests, they might take it to Monsanto and say, “We’ve developed this—would you be interested?” The key advantage in biotech is that a significant portion of the proof-of-concept work can be done in controlled environments like labs or greenhouses. This allows researchers to de-risk the technology substantially before taking it into the field.
For instance, in a lab or greenhouse setting, you can test a new trait multiple times under highly controlled conditions. If you go through two or three rounds of greenhouse testing and consistently see positive results—let’s say a new protein effectively kills target pests, or the plant expresses the desired phenotype—you have a much higher probability of success once you take it into real-world field trials. You can measure it, observe it, and validate the fundamental science before making the leap to large-scale agricultural deployment.
Compare that to digital AgTech, where the process is fundamentally different. If you’re developing a variable-rate seeding model, for example, you can’t test that in a greenhouse. You have to go straight to the farm, where conditions are unpredictable, and the variables are far less controlled. That makes testing and validation much more difficult, and inherently riskier in terms of proving value quickly.
RP: Yeah, even though digital offers the advantage of lower marginal costs when adding a new customer, I think you’re still starting out with a much higher risk compared to something like biotech.
In biotech, there are other established pathways for validation and adoption, whereas in digital ag, proving value and driving adoption can be more uncertain. That makes sense.
MS: Just to follow up on that—I know you may have another question related to this—but the flip side is that we’ve seen a shift in how multinationals approach venture capital. Many of them are now taking a model that looks a lot more like the traditional pharmaceutical approach.
In pharma, large companies often invest in drugs that have already gone through Phase 1 or even Phase 2 trials—meaning they’ve been somewhat de-risked. We’re seeing a similar trend in AgTech, where the major corporations use their venture capital arms to invest in startups that have already made some progress. They’re not necessarily looking to take big, early-stage risks, but rather to follow promising technologies, secure board seats, gain insights, and assess the potential before making larger moves.
At this point, nearly every major multinational has some form of this approach. It’s still venture capital, but the timelines are more aligned with the realities of agricultural innovation. That said, these corporate VC arms don’t have the same magnitude of capital that’s available in the broader venture capital market. So while this model provides an alternative path for funding and scaling innovation, it doesn’t fully replace the larger pool of independent VC investment that fuels much of the startup ecosystem.
Distribution is king
RP: You’re absolutely right about the timeline—corporates tend to have longer horizons. But they’re also looking at investments from a strategic standpoint, not just purely for financial returns. Their incentives are different.
For most AgTech startups, gaining access to distribution is one of the biggest challenges—and as you mentioned, it can be incredibly expensive. Do you have any advice for AgTech startups trying to navigate this? Given how costly and complex it is to reach farmers directly, what strategies would you recommend? How should startups think about building the right relationships, especially when they don’t have the kind of established distribution networks that companies like Monsanto or Bayer do?
Distribution is king (Image generated by ChatGPT)
MS: In all my advising and just being part of this ecosystem for the past 10 to 12 years, I’d say the most common mistake startups make is believing they can bypass traditional distribution to reach farmers.
I’m not saying it’s impossible, but what often happens is that startups focus on the revenue growth side—thinking, “We’ll just get on a lot of farms”—without fully considering the cost side of that equation. They don’t account for how expensive and difficult it actually is to acquire customers at scale in agriculture.
If you’re a Series A or Series B startup, a huge portion of your funding is going into getting your technology into farmers’ hands. But then you hit a tough reality—scaling requires salespeople, support teams, and a much bigger operational footprint than anticipated. And that’s where I think AgTech often struggles to fit within the traditional venture capital model.
A big part of the problem is the narrative that agriculture is an industry that hasn’t changed in hundreds of years and is ripe for disruption. That’s a classic entrepreneur pitch: We’re going to disrupt ag. But while agriculture can be disrupted, you quickly run into the fundamental disconnect between venture capital timelines and the realities of getting a product into the market.
A more measured—and often less risky—approach is to figure out strategic partnerships early on. That doesn’t mean partnering with everyone or giving away control, but it does mean leveraging companies that already have deep relationships with growers—whether that’s big seed companies, retailers, or other players in the value chain. These partners can help you get in front of farmers faster and build trust in your product.
If I’m an investor sitting on the board, I want to answer one key question as soon as possible: Does this technology create enough value for a farmer to pay for it and how much will they pay? And the sooner you can test that—at scale—the better off you’re going to be.
This is a mistake I see a lot of entrepreneurs and young CEOs make…we are going to market on our own. There are always exceptions, of course, but in general, the key challenge in AgTech is getting in front of your end customer. And in most cases, that means collaborating with partners who can get you there faster.
That’s exactly how we approached it at Climate. Even within Monsanto, we knew that having 30 sales reps working with 500 business managers who in turn worked with 7,000 retailers was the key to rapid scale. We leveraged existing distribution channels rather than trying to build a new one from scratch.
The trade-off, of course, is that you typically have to pay for that access in some way. But it’s still far more cost-effective than hiring an entire salesforce from the ground up. It’s all about finding the right balance—and it’s never easy.
Does AgTech have a future?
RP: As a follow-up to that—since you’ve talked about the longer time horizons needed for AgTech to scale and the critical role of distribution, which often requires partnerships with established players—I have a more macro-level question for you.
We’re seeing slowing population growth, increasing climate change concerns, and other shifts impacting the industry. If I’m a young, ambitious entrepreneur thinking about starting a company, I have to weigh the opportunity cost—I could be working on something else, whether it’s gaming, FinTech, or another fast-scaling industry.
Given all this, where do you see real growth opportunities in agriculture? And for someone considering starting an AgTech company, how should they think about it? Should they go for it despite the challenges, or are there fundamental reasons they might be better off focusing elsewhere?
MS: First I would take a step back. I think there is still a tremendous need in agriculture for technology to drive improvements. While population growth may be slowing—or maybe not, depending on how you look at it—it’s still going to be significantly larger by 2040 than it is today. And the fundamental premise that drove digital ag, and certainly shaped how we thought about it at The Climate Corporation, remains the same:
We have a growing population, a changing climate, and shrinking arable land. That means we have to figure out—through technology, not just digital tools but all kinds of innovation—how to produce more food on less land, often under increasingly variable climatic conditions. That fundamental challenge creates massive opportunities to build valuable solutions in agriculture, whether through AgTech, digital ag, or other advancements.
I still firmly believe in the opportunity for technology to transform global agriculture, but entrepreneurs need to go in with their eyes wide open. And I think the data backs that up. It’s been over a decade since Monsanto acquired Climate, and in that time, there have been very few major exits in AgTech. Maybe three or four, and even those don’t appear to have been wildly successful.
There have been plenty of AgTech startups, but it’s hard to point to one digital ag company that has built a truly killer app—something that has fundamentally reshaped the industry and created massive, sustained value. Most of the big exits happened early, and since then, we’ve seen much.
Why? Because the data sets are large and complex. Because getting in front of farmers is challenging. Because the value creation model isn’t always clear. Should digital ag tools be owned by a multinational? Should they be independent? And if independent, how do they reach scale?
It’s a complicated space, but it’s also one that is full of opportunity. Big ideas drive innovation, and venture capital exists to give those ideas a chance to take shape. So for entrepreneurs looking to enter this space, my advice is: Go for it. But do your homework.
Talk to as many people as possible who actually understand the business. Learn the nuances. Too often, there’s this mentality of, We’re going to disrupt this industry because the incumbents are slow, outdated, or resistant to change. And sure, maybe in some ways that’s true. But at the same time, there are fundamental business questions that established companies have already worked through—questions about distribution, adoption, and value creation that gives them strong and sticky relationships with farmers.
If you’re serious about building something that scales, you have to be willing to think beyond disruption and consider how to collaborate within the broader ecosystem. Success in AgTech isn’t just about having a great idea—it’s about figuring out how to integrate that idea into an industry that operates very differently from traditional tech sectors.
RP: Correct me if I’m wrong, but the way I’m summarizing your perspective so far is that the industry, as a whole, is still learning key lessons from the past decade. The challenges of working with agricultural data have proven to be more complex and resource-intensive than initially expected, and maybe 10 years simply hasn’t been enough time to see major, successful exits. That’s one possible hypothesis.
But beyond that, do you think the industry is focusing on the right set of problems—ones that can truly create value and scale into big opportunities?
For example, I was recently talking with someone who has been in the industry for 30 or 40 years, and I asked them, “How do you think things will change in the next 10 years?” Their response was, “I don’t know how it will change, but what I want to change is that I deal with paper every day—someone needs to solve that problem.” That’s a very practical, nuts-and-bolts issue. It’s not AI, it’s not a flashy disruption—it’s just something that would make life easier in a fundamental way.
MS: Y I think a great example of this is Bushel. If you look at the problem they set out to solve, they recognized that the entire grain buying, selling, and contracting process was still largely done on paper. It was complicated, inefficient, and difficult for farmers to keep track of. So they developed tools that digitize that entire ecosystem.
To me, that’s a great example of AgTech done right. It’s addressing a clear, well-defined pain point—for both grain elevators and farmers—and applying digital tools to simplify and streamline the process. Farmers can see all their contracts, grain tickets, and transactions in one place, rather than dealing with stacks of paperwork. It just makes life easier.
I think there are definitely opportunities like this, where digital tools can create obvious value. But it all comes down to doing your homework first. One of the biggest lessons I’ve learned from working with entrepreneurs in AgTech is that you have to really understand your product-market fit.
What problem are you solving? How is this digital tool going to make someone's life easier? How are you creating clear and measurable value for your customer. If the solution is clunky or unintuitive, it just becomes another frustration
That’s especially true in agriculture. When you start working with technology in the field, things get much more complicated. There are more variables, more external factors, and it’s harder to ensure consistent results.
That said, I do believe there are areas within agriculture that are ripe for disruption. Farm automation is a big one. There’s no doubt in my mind that automation will play a major role in the future of farming, and for good reason—it has the potential to simplify operations and make farming more efficient. I also think precision application of inputs will continue to be an area of important technical advancements.
So while AgTech presents some unique challenges, there are still massive opportunities—especially for entrepreneurs who take the time to deeply understand the industry and focus on building solutions that truly work for farmers and create clear and consistently measurable value..
Future casting
RP:You mentioned automation as one of the areas you’re excited about. What are some other innovations or trends that you’re keeping an eye on—things that you believe will drive meaningful change in agriculture? What areas do you see as having the biggest potential impact in the coming years?
MS: I believe we’re going to see not just autonomous vehicles in the field, but a broader shift toward much more controlled applications of agricultural inputs. Whether it’s fertilizer, herbicides, or other treatments, the way we apply them is becoming more precise, with more choices in how those applications are delivered—whether via drones, in-field equipment, or other emerging technologies. I see that continuing to evolve rapidly.
The reason for that is simple: there’s real value to be created. Beyond that, external regulatory pressures are acting as a forcing function, pushing the industry to develop new solutions. And that’s a good thing—it’s driving innovation in ways that might not have happened as quickly otherwise.
I also think AI is going to play a transformative role in agriculture. It’s a bit cliché to say that now, but if you go back to the early days when we were working with machine learning models, the whole premise was that data would drive better decision-making. What’s changed now is that compute power has advanced so much that we can handle large, complex data sets in ways that simply weren’t possible before. The ability to train truly useful models has accelerated dramatically.
Over the next 10 years, I don’t see how AI and compute advancements don’t play a massive role in advancing digital ag and solving some of the challenges we’ve been grappling with. One of the last major initiatives I worked on at Climate—along with my team—was recognizing that compute was going to be a critical factor in the future of agriculture. And the reality was, we were never going to compete with companies like Microsoft, Google, AWS, or IBM in that space. Even five or six years ago, you couldn’t watch a national TV commercial without seeing one of those companies showcasing a tractor in the field, signaling their growing interest in agriculture.
Ultimately, we made the decision to partner with Microsoft, because it was clear that the pace of advancement in compute, AI, and related technologies was only going to accelerate. I believe those advancements are going to be one of the biggest drivers of innovation in agriculture over the next decade.
On the ag biotech side, I also think gene editing is still in its early days. There’s already a lot of investment in that space, but I believe we’re going to see entirely new and novel applications emerge—applications that create real value in ways we haven’t even fully considered yet.
So, looking ahead, I think there’s an immense need to improve agriculture, and we have a strong foundation of technologies that are going to continue evolving. The next 10 years are going to look very different from the last 10, which were largely about figuring things out—learning, iterating, and understanding what works.
If we look back in another decade and digital ag still hasn’t demonstrated clear value, then sure—some people might argue that we squandered a lot of capital and got it wrong. But I’m not in that camp. I don’t believe that’s how this plays out.
I think it has simply taken longer than expected. It has required more money, more learning, and time for other foundational technologies to catch up. But now, we’re at a point where we can truly start utilizing these vast data sets in ways that weren’t possible before.
So, I remain optimistic. I’m bullish on the future of agriculture and the role that technology—whether digital ag, AI, or biotech—will play in shaping it.
RP: Cool. Yes, I'm very much an optimist. Thank you very much for your time today!
Relevant SFTW editions
- Meeting Farmers Evolving Expectations with Doug Sauder of John Deere (February 2025)
- The retreat of CVC in Agrifood (January 2025)
- All I want for Christmas is AI (December 2024)
- Can a new breed of startups save AgTech? (October 2024)
- Data has gravity (October 2024)
- FieldView’s number of nights metric (June 2024)
- The Dominion of Incumbents (March 2023)
Narrow (Thin) markets in commodity row crops - Part 1 and Part 2 (September 2022)