In this episode, I speak with Danny Bernstein, CEO of Reservoir. American farms advertised more than 400,000 seasonal positions in 2025 and received 182 domestic applications. That number sits underneath every agricultural robotics company raising money today.
Danny spent close to 20 years in Silicon Valley. He was part of a startup that sold to Google, spent ten years at Google, and two years at Microsoft, before turning to the question of why the physical world has so few technical communities around it.
Reservoir runs Reservoir Farms, 40 acres of working commercial farmland in Salinas where robotics startups test machines on real crops. It opened in March 2026, followed a month later by a second site in Sonoma County carrying 15 acres of Pinot grapes. Monterey County filed $4.82 billion in gross agricultural production value for 2025, and the farm sits within driving distance of Driscoll's, Taylor Farms and Dole Vegetables.
In this episode we cover:
Why fresh produce still has no automated harvester
The labor math underneath agricultural robotics
Physics that replaces chemicals, and vision that reduces them
What actually breaks a machine in a field
The two-year payback every agricultural machine has to clear
Who manufactures and services these machines
Turning farm jobs into ag tech jobs
Danny Bernstein on LinkedIn
Reservoir Farms Website
Watch on YouTube
Every episode, I sit down with the founders, researchers, and operators building physical AI worldwide, tracing the full stack from components and supply chains to what actually deploys. See all published episodes here.
Chapters
00:49 Danny Bernstein, Reservoir, and a technical community for agriculture
00:49 Silicon Valley builds seven of everything, agriculture waits for one
03:15 Driscoll’s, Taylor Farms, Dole, and a $4.8 billion county
05:29 Not AI for luxury, and the three gaps worth building into
05:29 Precision surgery by robot, fruit picked by hand
07:50 400,000 advertised farm jobs and 182 domestic applicants
10:11 What actually breaks a machine in a field
12:36 Sonoma, and the plan to cover the top ten specialty crops
12:36 Washington, tree fruit, and the Cosmic Crisp patent
14:58 Two years to return the cost of the machine
17:14 Service teams, dealers, and Andros Engineering
21:50 Merced College, and building on a teaching farm
24:12 YC gives you tokens, Reservoir gives you a tracto
We are performing precision surgeries using robots, but we still hand harvest fruit. And there were over four hundred thousand of these jobs that were posted in twenty twenty five and only a hundred and eighty-two domestic applicants for those positions. These are jobs that Americans are simply don’t want to do sitting where you’re at today, what are some biggest gaps that you’ve seen that you wish more people are building? And not AI for luxury or
AI’s for abundance, but it’s really AI for resiliency. Why combinator gets a million dollars in tokens from Oken AI, we get access to a tractor.
Danny, welcome to the show. Thank you, Michelle. This is super fun. Thanks for coming out to Salinas. Yeah, I know this is a great day to be out here. So we’re out here, Salinas, 24 acres. 40 acres. 40 acres of you know, like different machines running on the field. So take me back to where this idea first started. Yeah, so Reservoir is a technical community for agriculture, and that’s kind of a new thing. And and so what inspired me is that I actually spent close to 20 years in Silicon Valley.
How impactful technical communities were toward accelerating big discoveries. And you’re in San Francisco and there are technical communities kind of everywhere, whether it’s Y Combinator or around UC Berkeley, around Stanford. And I started to study basically how were technologies developed for the physical world where these technical communities may not exist, and we have significant technical opportunities in areas like agriculture or forestry or land management.
But like where are the startups and how do they connect with each other? And that is like the, you know, 30 second version of kind of how we came up with this idea, which is what if we built like the most robust technical community around Ag and what if we did it in the most important growing region, Archieville, in the United States? Tell me more about Salinas, right? How did you pick this part of California? What’s so special about it? Yeah, so I spent close to twenty years in Silicon Valley. I was part of a startup that sold to Google.
And I was at Google for 10 years and I spent a couple of years at Microsoft. And what really defined my time in Silicon Valley was sort of the behavior of how Silicon Valley developed products, which is one company comes out with a thing, and that thing is the new thing. Let’s say it was Zoom or it was quad code or whatever the first thing is. And then every company basically comes up with their version of that thing. And they basically are competing around what is essentially a solve problem.
And then if you flip it around basically and you look at what are the areas that don’t have that kind of activity, where you don’t have seven companies competing to solve one challenge. And agriculture is like that, where we have a bunch of really significant gaps in technology. And we’ll talk about it. But like an example would be automated harvest for fresh produce. Simple idea. Automated harvesters, automated robots for harvest, specifically in fresh produce where the output is more delicate.
We have practically no solutions. So you contrast that with Silicon Valley, where they’re like seven different ways to vibe code or seven different ways to do video calling, or seven different ways to message someone or email someone, right? We have an abundance of solutions we have to choose. You flip that around and you look at an area like agriculture where you don’t have that abundance. So we started calling it technology as resilience. And then if you look at basically agriculture in particular, and you were to hone in on fresh produce.
which is on micronutrients supply, like our most valuable calories are our micronutrients. And that’s fresh produce. And Salinas ends up being really the fresh produce capital of the United States, if not the world. Yeah, so Monterey County is a five billion dollar ag economy and Salinas is really the center point of that. So where we’re sitting right now, we are within driving distance of the headquarters of Driscoll’s, of Taylor Farms, of Dole Vegetables, all these like incredibly
massive vegetable and fruit production companies. So where do you build the technical community around those products? You do it here. So you’re really in the backyard of all these like the center of all these different agricultural powerhouse. When you talk to like companies like Drisle or, you know, even John Deere that is like in the space for a long time, like how do they view like ArcTech and the autonomous
wave that’s coming to this industry. Yeah, I mean they view it like a imperative, like it’s a must happen. It’s not a nice to have, it’s a must have. And it’s because of labor and input related costs. So chemicals, inputs, fertilizer, all the sort of ingredients of farming are becoming more expensive and more regulated. And then the labor of of agriculture is becoming increasingly expensive and scarce. We cannot pack each of those.
And so then they basically view technology as the only way out of those challenges. There isn’t really an alternative to technology. We’re not going to suddenly have millions of people who want to get into farming. It’s not going happen. We’re not going to suddenly have a pipeline of new chemicals that are going to be better than what was previously there because of anything we have more and more sort of chemical resistance in our crops now. And we haven’t had significant novel new solutions in chemistry come into ag in a very long time. It’s like something like two in the last thirty years.
It’s the view of growers, of operators, of agribusinesses, even of communities, that technology is essential. And so it’s viewed as one of the areas of AI that are not AI for luxury or AI sort of for abundance, but it’s really AI for resiliency. And that’s a different story altogether. And you mentioned about how there are so many gaps in
you know, how AI is solving in agriculture. It’s different from like vibe coding, having different so many different ways to play around with that. Tell me more, setting where you’re at today, what are some biggest gaps that you’ve seen that you wish more people are building? Yeah, sure. So I we really put them in three categories. The first is using physics to replace chemicals. The second is using AI or machine learning or vision.
to reduce chemical use, basically more targeted application of chemicals. So chemical replacement, chemical reduction. And then the third one is automating the jobs that nobody wants to do. And we have a lot of really hard jobs in agriculture right now. So we’re in Salinas, it’s about 70 degrees today. But if you drive two hours east to the Central Valley where we’re in the middle of harvest or kind of in the middle of tree fruit harvest, it could be 105 today. We do not have any automated harvest technology in Stonefruit.
We hand harvest peaches, we hand harvest table grapes. All of those sort of incredible fresh produce items require hand harvest still in 2026. we are performing precision surgeries, you know, using robots, but we still hand harvest fruit. Those are the three categories. Physics to replace chemicals, AI, sort of machine learning and machine vision to reduce chemical use and automating the hardest-to-fill jobs. Remember hearing a case where, you know, with these harvests.
being so such a labor intensive and still dependent on like human going onto the field is actually pretty dangerous, right? Like they get heat stroke and, you know, hours and hours under the sun. It’s actually like not safe to work so many hours. And so that’s where machines can really increase our quality of life and also lower the cost of Yeah, these are jobs that Americans simply don’t want to do. There was a the American Farm Bureau performed a study in twenty twenty five. They looked at
The 400,000 jobs that were posted were basically farm workers, and there were only 182 domestic applicants. Wow. So it’s 0.04% of the 400,000 jobs that were posted received a domestic applicant. The reason they know that is because there’s a visa that is our for foreign sort of the the for the farm worker that’s brought in from a place like Mexico to the United States to do that work. It’s called an H-2A visa.
And it’s how we actually perform harvest today is using imported labor that stays in rural communities for ten, eleven months in specific housing called, you know, H-2A housing or farm worker housing. Each individual H-2A job is posted publicly to ensure that there isn’t a domestic applicant for that particular position. And there were over four hundred thousand of these jobs that were posted in twenty twenty five.
And only a hundred and eighty-two domestic applicants for those positions. It’s wild. And so basically you’re saying that even though we have an unemployment in this country and some of our rural communities had nine, ten, eleven percent unemployment, these are jobs that Americans are simply not even applying for. And there are a variety of reasons why. It’s hard work. We also have a gig economy now that if you don’t want to do outdoor work, you can just drive a car and pick up, you know, Doordash.
So there are different ways to make ends meet now that didn’t exist in previous generations. So yeah, people do not want to work on farms. These are hard jobs. And technology is really for markets like the United States or Japan or Australia where there’s a premium on labor and labor is expensive. Technology is the gap. It’s that’s the solve. Yeah, and definitely in not just America, like globally, you’re seeing people abroad sit in front of their computers or on their phones or driving car.
Delivery, there’s definitely this gap that machines can help bridge. You sitting out here seeing all these machines running on the fields, what are the things or conditions that really break a machine? Is that the dust or is that the humidity, vibration, or you know, what are the surprising things that you’ve seen that are you saying yes to all of those? But if we take a step back, the robotics talent, the physical AI talent, if we think about where it’s originating from, it’s mostly from
PhD labs or from computer science schools or from places like Google or Nvidia or whatever, you have individuals that are, you know, in Palo Alto, in San Francisco, in Cambridge Mass, and if they decide tomorrow that they want to start a agricultural robotics company, like where do they begin? And so a lot of what we did to design Reservoir Farms is we actually thought about that persona. So I’ll very often say to the team, let’s think about the roboticist in Palo Alto and what she or he is looking for in a startup space.
And that’s how we design a Reservoir Farm. So we have forty acres behind us. It has leafy greens, so vegetables and strawberries. Right now those forty acres are it’s sort of farmed like an R and D farm or a test farm. So we have a few acres of iceberg, then a few acres of romaine lettuce, then we have five acres of strawberries, which is easily the most expensive to farm, like exponentially more expensive to farm. They it red gold. We can talk about that. And then we have some brassicas, we have broccoli and cauliflower.
So in one farm they can access behind us, you can access several different ultra high value commodities to be able to build your machine. They can get a lot of what those sorts of conditions are. Our particular farm is flat. It’s actually laser leveled. Most of the farms in Salinas Valley are laser leveled. If you go thirty minutes north, Castroville or or Prendale, you’ll see a lot of strawberry fields that are on s pretty severe slopes. And a lot of vineyards are on slopes and sometimes
winemakers actually love, you know, kind of the the challenged vineyard, you know, like that the this these Pinot Grapes had to struggle and therefore you can taste this or that. So there are a lot of different conditions that introduce a lot of variety and a lot of complexity. Sometimes you’re in a GPS-denied environment. Sometimes you have very low connectivity. So we see a lot of different things that come up. mud, muck, mire, all the above exist here. So this is like really a proving ground for physical AI. And there’s a feeling in ag in particular.
that if you can make it here, you can make it anywhere. And the vision is to have not just in Salinas, but also in like wine country and tell me more about that. So we opened Reservoir Farms in Salinas in March. And then a month later we opened our second location in Sonoma County. So Salinas is two hours south of San Francisco, but only about an hour south of San Jose. So it’s very accessible to NVIDIA to Google, etc. And they’ve all been here, which has been great.
And visited us. And then we’re in Sonoma County, which is an hour north of San Francisco. So we have startups that are splitting their time between YC and Founders Inc. and Reservoir, which is pretty cool. And that makes sense, right? Because YC, last time I checked, didn’t have a farm. So it’s useful to them. So yeah, we opened in Wine Country. We have fifteen acres of Pinot Grapes there. And it’s a similar structure that a startup can get onto our farm and be testing in rows and vineyards. And our plan is to
Roll out farms to cover at the very least the top ten US specialty crops by farm gate value. So wine grapes, table grapes, almonds, leafy greens, brassicas, carrots, tomatoes, blueberries, strawberries, and maybe I forgot a few more onions than they’re onions. And so then a startup that is thinking about working across ag, which is fragmented by crop, which is part of the complexity of this market.
they can work with Reservoir and then in one year or what a year and a half, they can actually access lots of different crops and test in lots of different environments. So Bonsai Robotics, which is one of the startups here that our fund actually invested in, they in the same week tested at our wine country location on vineyards and then tested on strawberries here in Salinas using the same machine. It’s pretty fun. So you’ll cover the whole supermarket. Yeah, we like to yeah we’ll open in Washington State sometime in the next six months.
And that will be tree fruit and blueberries. And we love Washington because it’s really like the intellectual and industrial epicenter of tree fruit and blueberries. The Cosmic Crisp Apple, which is my favorite apple. The Cosmic Crisp apple is legally by rules around the intellectual property, only can be grown in Washington. So yeah, so it’s licensed by Washington State University, which has the patent, and they actually license it to Washington growers.
And they could only grow it in Washington, I think in Clint 2032. Wow. But it’s an amazing, amazing apple. So then if you think about where would you build a startup in your startup space or where would you build a technical community that was focused on tree fruit, you would of course be in Washington, which is 60% of the apples in the United States. And then blueberries actually like there is extraordinary efficiency for blueberries in Washington relative to pretty much every other state. They grow more more inexpensively.
And similarly to these other environments, there is a lot of automation gaps. We don’t have hand harvest. We don’t have automated harvest in tree fruit. We don’t have automated harvest in fresh blueberries. So there’s a lot of opportunity, a lot of like big like really meaningful and high value tech gaps in these areas. While we’re doing our preparation, we talked about the operational layer of Archtek, right? And so there’s so many things that
goes in like beyond building the machine, beyond the road model and actually getting machines on the ground and keep them working. So talk to me more about that and what you’ve observed and what the gaps have been. Yeah, I mean the ab tech CEO has a lot to think about for sure. I think it really attracts it’s a very high demand sort of job. We tend to see more senior CEOs here because of that, not exclusively, but because of it, it requires a lot of resilience, a lot of humility. I mean there are a couple things. One is that the most
Critical thing is that they’re delivering a machine that really must deliver ROI within two years, maybe three, ideally one. So they are dealing with a very discerning customer that knows their numbers and is really kind of commanding a pretty high bar. It is a much more sort of sophisticated and informed sort of customer than I think a lot of roboticists are gonna be accustomed to. And that’s exciting. I mean, I think it’s a big challenge, but it’s exciting. And if it and if you can make it work, like
Carbon Robotics, for example, their laser weeder, they’re now doing a hundred million ARR. It’s great. So that’s a company that is is starting to scale in their other examples. But an AgTec CEO needs to think about the logistics of their machine, how they get it from here to there. They have to think about the servicing of those machines. Are they going to be servicing in-house with their own team? So Carbon Robotics, for example, is built an in-house service team. Bonsai is beginning to build one. And then but Bonsai also has what’s called dealer relationships.
So there are ag dealers that sell, may sell John Deere Tractors, and then they also sell ag tech as well, sort of more emerging ag tech. So they have to think about those sorts of channel partnerships, both for sale and service. They of course have to think about manufacturing and a manufacturing supply chain. So a lot of companies will do their own manufacturing for like maybe the first two or three years and sort of manufacture out of a warehouse, or they’ll work with specialized manufacturing firms or actually domestic.
that they come in a contract with, like Andros Engineering, which I’m sure you’ve never heard of. But if you go to Andros, which is in Passa Robles, our friends at Andros, you will see them hand assembling half a dozen different extraordinary AgTech machines that are all software enabled, AI enabled, and they’re building them. And there’s another one, GK Machine, which is in Oregon, which is doing something similar. And so you have these very specific manufacturing pipelines.
And addition to all the supply chain considerations they have to think about. So it’s a very opsy job. And then they have to think about how are they marketing their products and how are they pricing their product are they doing? Is it lease based? Is it service based? Is it, you know, selling the machine, etc.? So it is demanding that way and I would say I have a lot of respect for the ad tech CEO. It’s it’s not for the faint of heart for sure. I think one of the things that really stood out to me is how we’re farm is
currently operating like very closely with the community college around here. And I think that also touch upon the shifts in the labor market that we like as more autonomy is going to the industry, like what does the future like architect labor market look like? And what do we need the skills to be? And how do we train up the next generation of people operating on the field? No, it’s a big one for sure. And and we’re not the only ones talking about it, but
We think about we are building a technical community for agriculture and we’re doing it in place. Like we’re doing it in rural regions of the United States. So rural Washington, rural Arizona, rural California, and then we’ll go beyond that, rural New York, rural Florida, et cetera. And it’s difficult to imagine convincing the San Francisco engineer to want to be in place here. Like their ties are there, they’re part of that ecosystem. They’ve gotten accustomed to creature comforts of being in San Francisco. So when you think about
Who is going to be very affinitized towards rural California? Well, it’s the people who are from there. And so we have a labor pool here. We have a we have a high tech labor pool here that we need to work with the community to to train up. So we have to think about what are the hiring needs of a Carbon or a Bonsai or a Verdant Robotics. We have to work with the community colleges that are in region. It’s also the California state schools. It’s a little bit with University of California as well.
And we have to have a really like ongoing, I’m talking like weekly, sometimes daily dialogue about the sort of opportunities that go between those firms as we transition ag jobs to ag tech jobs. It’s one thing to be servicing and implement on a tractor that’s dumb, that’s just like mechanized. It’s like you just let’s say it’s like a big, dumb tilling machine, no offense to a tilling machine. But then going into something that’s smart, that’s AI enabled, that might have, you know, twenty four GPUs on it or something like that. Like we’re talking a
another level of complexity. We have a machine out there that’s an automated harvester that’s pre-commercial that has eight robotic arms. How many cameras? I don’t know, but like maybe a few dozen cameras. So there we’re talking about like a different different level of service orientation. So what we did is that when we began to build Reservoir Farms, the concept for it, which was two years ago, one of the first conversations we had was with the local community college here, which is called Hartnell College. It’s been around for over a hundred years.
And they are basically a feeder into agribusinesses here. Those have been historically like pest control advisors or you know, agronomists, they might be folks who help you figure out what kind of chemistry you should be using on your farm or figuring out kind of how to problem solve around disease control or weed control. But now those same sort of pipelines of agricultural talent need to be thinking about AI enabled machines and robotics with a hundred different degrees of freedom.
So that’s a really different thing. So how do we do it? We basically set an MOU with them about how we work together. And then fast forward to today, we have eight interns with our startups here from Hartnell College. We have eight community college interns at a deep tech, high tech startup incubator, which is incredibly cool. And so we view it like that there’s a strategic role of inclusive innovation in physical AI. If you’re building physical, if you’re building AI for the real world and you’re doing it in place.
You have to be thinking really early on about your labor pool. And we encourage companies to think about it. But then we as the sort of convener, as the technical community, we, you know, have to think about it as well. So we’re learning a lot, but it’s a it’s a neat and new mode. Yeah. And it’s really about kind of like mixing the like chemistry, like learning about the
the pesticide side of things, but also like how it interacts with like the autonomous and the world model side of things to use. It’s real. It’s like community integration. Exactly. So in the Central Valley of California, which is about two hours east of here, we are launching a version of Reservoir there next year. And we decided to launch it actually on a community college campus. Wow. So there’s a school called Merced College, which is Merced is basically two hours south of Sacramento and then two hours north of Bakersfield.
So then this really substantial stretch of California’s inland, Eastern California, let’s say, middle to eastern California, you have several of the largest ag economies in the country. So Kern County and Fresno County are both eight billion dollar ag economies annually. They’re massive. And so we thought, you know, we should probably build a Reservoir there. This is tree nuts, table grapes, processed tomatoes, carrots, etc. It’s like a really, really big part of the agricultural industrial sort of state.
We thought a lot about what would be the ideal scenario for building Reservoir there. And we decided that doing it at a community college farm made a lot of sense because community college farms are multi-crop because they’re trying to train students. So on one farm you have tree nuts, table grapes, citrus, stone fruit, processed tomatoes, melons, peppers, etc. You would never have that in an industrial farm. So then a startup can be thinking, How am I building my machine? Not just for one crop and one task.
Each new crop a startup adds is more TAM for them. For sure. So it’s like you can think add a crop, add TAM, add a task, add TAM. So this particular farm in the Central Valley is perfect for us. And rather than building, let’s say, you know, ten miles from that farm, we worked out a public-private partnership with a college to build Reservoir Farms right there. So we’re doing some different things and working on it a lot. I’m curious in terms of these inters working at your farm and also with all these startups that
being debated by your community, like what are the things that they are learning that they cannot learn in a a community college inside their classrooms? Yeah, it’s a great question. I mean they’re they’re learning about the very specific intricacies of of machine maintenance and repair. They’re beginning to see sort of hands-on design decisions about machines. They’re also learning the equipment and sort of how it’s used in the real world. So we have site managers and site coordinators that are employed by Reservoir.
all of which are are ag engineers, mechanical engineers that that know the way around a shop. And so they’re getting that pretty extraordinary hands-on experience. But a lot of times the startups themselves are. So if you think about what are the characteristics of a startup founder in ag tech, they may be a software wonk, but they may not be a machinist. And so very often we are teaching the re startup founders how to drive a tractor, how to work a forklift. One of the unique things about Reservoir is that we have tractors here.
for them to build on and test on and add sensors to and do all the things that they would need to do in an ACTEC context. I think we’re the only startup incubator in the world that has access to John Deere tractors for as part of our perks. You know? So like you know at White Combinator gets, you know, what you know a million dollars in tokens from OkenAI, we get access to a tractor. So I think it’s pretty unique. Take me five years out, right? So where do you see worse of a farm at? Like how many farms would you have and what are some
New use cases that you’re excited about. Yeah. I mean, I think we’ll certainly have farms across the American West to cover the largest crops. We’ll have expanded nationally. I think we’ll have also established Reservoir Farms and sort of the major international hubs that have some characteristic chal similar characteristics of challenges. So basically every first world market has a labor shortage. If they are also growing their own specialty crops growing if they’re in agricultural market, like sort of exporter versus importer, they have significant challenges. So it makes sense to do Reservoir elsewhere.
And there’s a lot of the due tech ecosystems that have formed around those areas, like Australia and the Netherlands and Israel and other places. So it just makes a lot of sense for us to be there. We would hope to see several solutions that are plugging gaps and harvest automation. I would think by like 2030, 2032, that we’re automating more and more of harvest, that we have automation of berries and leafy greens and vegetables and brush. So that’s a big one. I we also want to see the scaled adoption of sort of physical tools to replace chemistry.
So that’s UV light for disease control, that is laser weeders, that’s electric weeders, and a bunch of other novel solutions that we’re expecting as well. So that area, which is basically using atoms instead of chemistry in order to control disease, control weeds, that’s good for the world. It’s also necessary because we’re gonna see increased regulation around the use of chemistry, and it’s gonna become increasingly expensive to do chemistry at scale. And so
That’s something that we’re tracking and you know you’ll have to come back hopefully sooner than I. So awesome. Yeah. Well, thank you so much, Danny. This is awesome. I appreciate it, Michelle. Thank you so much. Thank you.
