Transcrição completa de AgTech Meets Reality: What Actually Works on the Farm

that my dad ran a couple different ranching operations, mainly cattle and hay. 00:02:20.879 --> 00:02:23.680 Learned a lot about that side of the business and that side of the state. 00:02:23.840 --> 00:02:28.560 And then my folks split, so I spent uh school years in Monterey County, about two hours south of here. 00:02:28.639 --> 00:02:30.159 Uh fifth generation ranch. 00:02:30.240 --> 00:02:31.360 That one was really fun. 00:02:31.599 --> 00:02:35.520 Uh, we bought it from the Mexican government in 1871. 00:02:35.680 --> 00:02:36.159 Oh, wow. 00:02:36.319 --> 00:02:38.240 So it is 155 years old. 00:02:38.560 --> 00:02:38.800 Wow. 00:02:38.960 --> 00:02:40.080 And a lot has changed. 00:02:40.960 --> 00:02:41.120 Sure. 00:02:41.280 --> 00:02:43.439 So I went to Cal Poly for a business degree. 00:02:43.599 --> 00:02:46.800 Then I came to Santa Clara for a law degree, met my charming wife. 00:02:46.879 --> 00:02:47.520 We have five kids. 00:02:47.680 --> 00:02:50.080 We're living in Los Gatos and uh loving it. 00:02:50.240 --> 00:02:52.000 And I spent a lot of time at startups. 00:02:52.080 --> 00:02:58.719 So I was at uh eBay's the one folks have heard of, but a couple others in the loosely enterprise data center space and the e-commerce space. 00:02:58.879 --> 00:03:04.240 Um, and then around 2014-2015, my ag friends were like, What is going on up there in your valley? 00:03:04.319 --> 00:03:06.879 And my valley friends are like, What is going on down there with the ranchers? 00:03:06.960 --> 00:03:08.000 And I'm like, you know what? 00:03:08.080 --> 00:03:09.280 I'll I'll go look around. 00:03:09.520 --> 00:03:10.560 Never came back. 00:03:10.719 --> 00:03:19.280 Um, so for the last 10 plus years, I've really been at that intersection of specialty crop agriculture in California and the technologists that can help them. 00:03:19.360 --> 00:03:21.439 And at Western Growers for the last five and a half years. 00:03:21.520 --> 00:03:23.599 So I worked with an accelerator for a while, Thrive. 00:03:24.000 --> 00:03:24.719 SVG Thrive. 00:03:24.879 --> 00:03:24.960 Yeah. 00:03:25.199 --> 00:03:27.280 That was a fun ride with John Hartnett and that crew. 00:03:27.360 --> 00:03:32.479 And then the Western Growers position came open and I said, boy, that was I knew the organization from my ranching background. 00:03:32.639 --> 00:03:32.960 Right. 00:03:33.199 --> 00:03:40.080 Um, and our ranch, by the way, full disclosure, I say that I'm a fifth-generation farmer, more like it's a fifth-generation farming operation. 00:03:40.159 --> 00:03:43.919 I've never really worked a full day on it other than to help out uh my family. 00:03:44.159 --> 00:03:44.400 Sure. 00:03:44.479 --> 00:03:47.520 Um and well, worked as a kid for you know free labor. 00:03:47.680 --> 00:03:57.199 Uh we run cattle, we have great tenants for the grapes, we have Mondavi, uh, now Constellation for the Grapes, now Gallo, actually, and then we have uh Leafy Greens grower partners. 00:03:57.360 --> 00:03:59.439 So um, but the ranch has been there forever. 00:03:59.599 --> 00:04:07.280 So bringing that with me to Silicon Valley, and then bringing that Silicon Valley startup with me to AgTech has been really helpful. 00:04:07.439 --> 00:04:16.959 And so at Western Growers, the charter, as you said in the intro, is um how do we solve labor and how do we solve the chemistry pressures that are you know never ending? 00:04:17.040 --> 00:04:28.959 And so that's that's that's the whole job right now is just more robots to help with labor and more biological, genetics, and regenerative ag startups and tools to help them use less chemistry. 00:04:29.279 --> 00:04:29.839 Got it. 00:04:30.160 --> 00:04:43.600 So I'm assuming that when growers come to you, they come not because they're just interested uh in in what's going on, but they come because they have an issue that that they want solved, right? 00:04:44.079 --> 00:04:54.560 So when when they talk to you about how technology can potentially help them solve their problems, is it mostly uh uh related to labor? 00:04:54.959 --> 00:04:55.920 Is it water? 00:04:56.160 --> 00:05:09.920 Like what what what do you see, or maybe over the years it's changing and and there are different pressures that that are more um uh top of mind, but from your perspective, what what what what are the questions that you usually get the most? 00:05:10.240 --> 00:05:22.240 Yes, and and this is where it is beneficial to be 60 years old, having sat at a lot of dinner tables with grandparents and parents and peers over the years, and you I mean it's it's always worth noting, they haven't changed much. 00:05:22.399 --> 00:05:24.240 The order may change, but they haven't changed much. 00:05:24.399 --> 00:05:31.279 It's always been labor, it's always been water in California, it's always been chemistry pressures and food safety. 00:05:31.439 --> 00:05:33.759 Um, those have been the rotating four. 00:05:33.839 --> 00:05:36.959 And when a food safety outbreak hits, that jumps up the list a little. 00:05:37.439 --> 00:05:42.480 When water allocations from Sigma hits, the sustainable groundwater, um, that may jump up a little bit. 00:05:42.639 --> 00:06:01.040 When labor, and we see a bump in H2A international uh farm workers by by th you know 3x in five years, and that's more expensive labor, labor for sure is now so I I would argue those four have been rotating, but the last 20 years labor has just been all consuming because you just you can't find enough of it here. 00:06:01.439 --> 00:06:08.160 The generational farm worker has become the generational McDonald's worker, sandwich shop worker, retail worker. 00:06:08.240 --> 00:06:09.439 They don't want to work on the farm. 00:06:09.759 --> 00:06:19.360 And so the kids in their 20s that in prior generations, for about a generation and a half, would come back to the farm and do the job that their parents did are now saying, eh, you know what, not so much.

00:06:19.680 --> 00:06:32.079 I think that uh in the past it used to be um very shiny being uh working on the farm, knowing that you're producing food for your community and everybody around. 00:06:32.319 --> 00:06:44.720 And uh I think it now uh people look at it as, you know, uh, I mean, why would I work crazy hours out in the sun or out in the rain or out in the heat or out in the cold? 00:06:44.879 --> 00:06:45.120 Right. 00:06:45.279 --> 00:06:56.800 Uh, you know, where there are bugs and what whatnot doing physical labor uh when I can sit in an air conditioned office and you know, get paid the same. 00:06:57.040 --> 00:07:03.120 I think that an by the way, another uh you know and you know, I like I told you, I grew up on a farm myself. 00:07:03.279 --> 00:07:03.600 Right. 00:07:03.839 --> 00:07:17.040 One of the things that that you hear a lot growing up is how challenging it is being in agriculture, how uh uh how hard it is, how there's no future for it. 00:07:17.279 --> 00:07:35.519 And a lot of the time, I think, uh your elders in the community, not it's not necessarily just your parents, but what you hear around in in your community um is people trying to steer you away, like go get a degree, go try to do this, though, go try to do that. 00:07:35.839 --> 00:07:51.040 And I think for kids that are really young age, this already kind of pivots their their way of thinking into other directions, and they don't necessarily even think of the uh idea of going back to the farm later on in life. 00:07:52.879 --> 00:07:55.040 With you, lived it, living it. 00:07:55.519 --> 00:08:04.639 Both of my folks were like, you're gonna have the ranch, you've grown up here, you've you've fed Hay to the cattle, you've done fence posts, you've done, I mean, right, you know what the operation looks like. 00:08:04.800 --> 00:08:11.360 Don't go get an aggregate, go go go, you know, get a business degree, which was I think good advice at the time because I did have the ag knowledge. 00:08:11.600 --> 00:08:13.839 Um, but it's interesting to that exact point. 00:08:13.920 --> 00:08:26.480 I find the ag tech so fascinating because the number of growers that have admitted they overinvest in technology like drones and sensors, just to get some of the next generation to get interested and maybe come back. 00:08:26.560 --> 00:08:26.720 Yep. 00:08:26.879 --> 00:08:34.320 So I'm not saying folks are buying drones that never ROI, but I'm saying if they don't ROI well and the kid comes back to the farm, that's a win. 00:08:34.480 --> 00:08:37.360 And so I think ironically, yeah, I totally agree with you. 00:08:37.519 --> 00:08:48.000 I mean, even in California, the mother load of especially crops, we still heard growing up in agricultural communities in Imperial Valley and Monterey County, oh yeah, you don't, you know, this won't be here in 40 years. 00:08:48.080 --> 00:08:50.159 And you know, it's it's more than here. 00:08:50.320 --> 00:08:56.240 Um, but when you hear that for so long, you definitely think about okay, in terms of a career path, probably not something I want to go chase. 00:08:56.320 --> 00:08:56.639 Yeah. 00:08:56.799 --> 00:09:00.799 Um that's and I would argue, so I work a lot with the universities, right? 00:09:00.960 --> 00:09:12.000 Davis, Cal Poly, Fresno State, Merced, and a bunch of others, and a lot of community colleges, Hartnell, Hancock, um, the the the ones on the five in the San Joaquin Valley. 00:09:12.320 --> 00:09:22.240 And I would argue that all of these institutions um have a hard time, like even the Ag 452 class at Cal Poly. 00:09:22.320 --> 00:09:23.120 I went down and trained that. 00:09:23.200 --> 00:09:24.559 This is a apply for class. 00:09:24.639 --> 00:09:27.200 You don't just sign up for it, you gotta get in to this class. 00:09:27.440 --> 00:09:32.240 It's about 30 kids, and I had them for two hours uh last year, January of 25. 00:09:32.720 --> 00:09:34.639 Two-thirds of them are graduating in June. 00:09:34.799 --> 00:09:35.200 Yeah. 00:09:35.440 --> 00:09:36.799 30 of them in the class. 00:09:37.039 --> 00:09:42.080 I asked, how many of you guys have a path forward in June that is ag related, like eight hands? 00:09:42.320 --> 00:09:42.720 Really? 00:09:42.960 --> 00:09:57.440 How do we let 22 kids get to the point where they sign up for that class, they go through the effort, they they sit there, they're paying attention, they're asking good questions, and 22 of them don't have a path for they had jobs, but not a path forward in ag. 00:09:57.759 --> 00:09:58.720 It's super interesting. 00:09:58.879 --> 00:10:00.240 It is, it is very interesting. 00:10:00.399 --> 00:10:02.399 And believe me, there are jobs out there for them. 00:10:02.480 --> 00:10:10.080 We any of my members, Taylor Farms, Driscolls Berries, Braga Fresh, they need good employees, even today. 00:10:10.399 --> 00:10:13.600 Yeah, and good help is always pretty hard to get. 00:10:13.840 --> 00:10:14.159 100%. 00:10:14.559 --> 00:10:27.039 And yeah, well, the way that I grew up, and like you s you like you told me told me earlier before we started, uh, I was also um free uh free labor as a kid uh for my dad. 00:10:27.279 --> 00:10:29.600 And uh I won't even tell you what I got paid. 00:10:30.320 --> 00:10:31.759 Yeah, it starts with the two. 00:10:33.120 --> 00:10:38.159 I so this one time I actually worked, I I worked over summer vacation. 00:10:38.320 --> 00:10:44.080 Um I worked with my dad, and what I got at the end of it, I was really into binoculars at the time. 00:10:44.240 --> 00:10:44.320 Okay. 00:10:44.559 --> 00:10:45.360 I really wanted one. 00:10:45.519 --> 00:10:45.679 Yep. 00:10:45.840 --> 00:10:52.000 So I got a binocular uh at the end of the uh at the end of you know summer vacation. 00:10:52.159 --> 00:10:58.960 I was uh I was working, I don't know, maybe a month, and I got a set of binoculars, and I was I was really excited about that. 00:10:59.039 --> 00:11:00.639 Um you thought

that was a great deal. 00:11:00.799 --> 00:11:02.799 Yeah, for me at the time, it definitely was. 00:11:05.759 --> 00:11:06.960 So my story on that one. 00:11:07.120 --> 00:11:09.840 I worked an entire summer down in El Centro in the heat. 00:11:09.919 --> 00:11:10.080 Yep. 00:11:10.240 --> 00:11:15.519 Got up at you know 4:30 so I could be able to work by five so I could finish by one and go to lunch and get some great Mexican food. 00:11:15.840 --> 00:11:21.039 And I worked that whole summer, and the outcome of that summer was my dad matched me. 00:11:21.120 --> 00:11:23.440 I I had 900, he had 900. 00:11:23.519 --> 00:11:31.840 We found a 57 Chevy in San Diego with the three on the tree up here, and I had that truck, and that was my truck, and I was very happy to have that truck. 00:11:32.000 --> 00:11:34.320 That was literally an entire summer of output. 00:11:34.559 --> 00:11:35.600 That's amazing. 00:11:35.840 --> 00:11:37.039 That's amazing. 00:11:37.279 --> 00:11:46.720 Um, so uh so yeah, my dad always told me if you want to get accepted to work here permanently, you need you need a college degree. 00:11:46.879 --> 00:11:47.120 Right. 00:11:47.360 --> 00:11:51.440 Like uh, because he really wanted us, uh I'm the oldest of three kids. 00:11:51.600 --> 00:11:58.960 I have two uh younger sisters, and he always told us, like, you need to go get a degree, you need to expand your horizons. 00:11:59.120 --> 00:12:04.159 If you want to come back to the farm, you know, it's it's always gonna be here for you. 00:12:04.399 --> 00:12:08.240 Uh, but I don't want you to choose this because I chose that. 00:12:08.480 --> 00:12:08.960 Right. 00:12:09.200 --> 00:12:14.000 And uh for my father, it's a little different because we're not I'm a second generation. 00:12:14.080 --> 00:12:15.519 He started He was the founder. 00:12:15.840 --> 00:12:16.480 He was the yes. 00:12:16.720 --> 00:12:16.960 Okay. 00:12:17.279 --> 00:12:17.600 Yeah. 00:12:17.759 --> 00:12:21.360 Um That's in my opinion, that's always the hardest chair to fill. 00:12:21.600 --> 00:12:21.759 Right. 00:12:22.000 --> 00:12:25.039 Getting it going from nothing, that is good on you. 00:12:25.279 --> 00:12:31.519 Yeah, so so he started it uh back in I guess uh early 80s. 00:12:31.759 --> 00:12:32.080 Okay. 00:12:32.320 --> 00:12:39.120 Uh they bought the farm they still live on when they're when my mom was pregnant with me, so that was probably 86. 00:12:39.200 --> 00:12:40.320 I was born in 87. 00:12:41.519 --> 00:12:47.039 And uh yeah, he started with uh when my dad started, he started with like 25 hives. 00:12:47.279 --> 00:12:47.600 Okay. 00:12:47.919 --> 00:12:50.480 And today he's got like five or six thousand. 00:12:50.720 --> 00:12:51.200 Wow. 00:12:51.360 --> 00:12:58.480 Uh and uh he's the biggest in Israel too, and um, you know, he was a hard worker his whole life. 00:12:58.720 --> 00:13:01.519 Um so from this, so the the business model hadn't changed. 00:13:01.600 --> 00:13:04.000

A lot of growers changed business models from day one. 00:13:04.159 --> 00:13:05.200 He was doing hives. 00:13:05.519 --> 00:13:06.320 He was doing hives. 00:13:06.399 --> 00:13:12.879 He did have a uh a few other things because when he bought the farm, uh it used to be a dairy farm previously. 00:13:13.279 --> 00:13:19.120 It had some land too uh for for orchards, but he bought it, it had uh a dairy farm on it. 00:13:19.279 --> 00:13:21.200 So he planted apples. 00:13:21.519 --> 00:13:23.519 So we were growing apples as well. 00:13:23.759 --> 00:13:33.679 We had um we had some apples and he was growing uh calves from um until they were able to eat solids. 00:13:33.840 --> 00:13:36.559 So we got them when they were still drinking milk, right? 00:13:37.120 --> 00:13:39.919 Transferred them to solids and then they would move on. 00:13:40.080 --> 00:13:50.720 But yeah, so over the years, you know, I I've had this example of somebody that took something from the made made something from nothing uh and made it pretty successful too. 00:13:51.360 --> 00:13:54.240 Um and I enjoyed working there. 00:13:54.399 --> 00:14:03.279 I loved I like working in beekeeping gives you a lot of opportunities, not just being outdoors, but re changing your environment all the time. 00:14:03.440 --> 00:14:11.600 Because it's not only you're moving between your different yards uh where you keep your bees, it's like the yards change based on the seasons. 00:14:11.840 --> 00:14:12.000 Right. 00:14:12.240 --> 00:14:18.159 So I really liked the the traveling part of of of that work. 00:14:19.360 --> 00:14:30.480 Um I wanted to uh talk to you about um an article that you recently you recently um posted on I I saw it on LinkedIn. 00:14:30.639 --> 00:14:30.960 Yep. 00:14:31.200 --> 00:14:37.840 Um how uh investments in AgTec changed over the last uh five years. 00:14:38.080 --> 00:14:42.639 So I think I think you mentioned in 21 it was like 53 billion dollars. 00:14:42.879 --> 00:14:43.519 Exactly. 00:14:43.840 --> 00:14:47.279 And in 2025 it was ten billion dollars. 00:14:47.600 --> 00:14:49.440 This is a huge change. 00:14:49.759 --> 00:14:50.240 Huge. 00:14:50.559 --> 00:14:54.000 As somebody that works in this industry, I f I feel it, like I see it. 00:14:54.159 --> 00:14:54.720 Right. 00:14:55.039 --> 00:15:05.759 But um yeah, I I wanted to to to ask you about that, see what what your perspective on it was, because this is a super interesting transition. 00:15:06.159 --> 00:15:11.519 And I want to know what what do you think brought us from one place to the other. 00:15:11.759 --> 00:15:18.000 Yeah, so what brought us to 53 billion really started back in 2013 with Climate Corp. 00:15:18.159 --> 00:15:18.960 Remember those guys? 00:15:19.039 --> 00:15:19.279 Yep. 00:15:19.679 --> 00:15:23.919 First billion dollar exit in AgTech was Dave Friedberg's little company, as we call it. 00:15:24.240 --> 00:15:31.519 And they got the billion dollar out uh to Monsanto, uh, and off Dave went, and everyone's like, oh, well, okay, so two things. 00:15:31.679 --> 00:15:38.799 You can start a startup in AgTech and get a billion dollar outcome, and clearly growers have some challenge areas because they're buying Dave's stuff. 00:15:39.279 --> 00:15:39.600 Okay. 00:15:40.159 --> 00:15:46.000 So from two billion dollars in 2013, things kept rolling, things kept funding. 00:15:46.159 --> 00:15:53.039 Everyone identified there are some real challenges, and there's some real TAMs, some some total addressable markets that are get are gettable. 00:15:53.360 --> 00:15:53.679 Right. 00:15:53.840 --> 00:16:02.320 So you saw the ramp up to 53 billion, and along the way, and it's fair to mention this, we went from ag tech to agri food tech. 00:16:02.559 --> 00:16:02.720 Yes. 00:16:03.039 --> 00:16:06.399 So we added all the food stuff to it to make it look bigger. 00:16:06.480 --> 00:16:09.039 That's what the Ag Funder News will now admit. 00:16:09.120 --> 00:16:13.200 I mean, Louisa will say, yeah, we we wanted it to appear bigger, so we added food to it. 00:16:13.279 --> 00:16:17.279 Because they're two very different segments when you really look at them, but you can see why they're together. 00:16:17.840 --> 00:16:20.000 So that category grew to 53 billion. 00:16:20.080 --> 00:16:24.240 The challenge with it in 2021, there were macro challenges and there were micro. 00:16:24.480 --> 00:16:28.399 Macro, you had a complete shrinkage of the IPO market. 00:16:28.480 --> 00:16:28.879 Remember that? 00:16:29.519 --> 00:16:36.960 1,050, 58 in 2021, and we went down to 185 two years later, right? 00:16:37.440 --> 00:16:50.559 Well, this lack of IPOs means the cash funnel between limited partners, venture capital, and then startups slows down because the cash never gets returned to the LP until there's an event. 00:16:50.639 --> 00:16:53.519 And without those IPOs, staying private longer, right? 00:16:53.679 --> 00:16:58.159 Without those IPOs, the LPs were left going, I've got no cash for the next fund, guys. 00:16:58.399 --> 00:16:58.639 Sure. 00:16:58.960 --> 00:17:01.759 Um, and so VCs were getting hit hard. 00:17:01.919 --> 00:17:02.879 They took a big hit. 00:17:02.960 --> 00:17:13.519 They went from VC, core VC, all all tech segments,$354 billion in 2021,$171 billion in 2023. 00:17:13.599 --> 00:17:15.599 So 50% drop, right? 00:17:15.839 --> 00:17:16.160 Yep. 00:17:16.319 --> 00:17:17.680 What saved them? 00:17:18.000 --> 00:17:18.559 AI. 00:17:18.720 --> 00:17:18.960 Yep. 00:17:19.200 --> 00:17:22.880 So AI is propping up the whole darn valley for the last two years. 00:17:23.039 --> 00:17:24.400 No end in sight, by the way, right? 00:17:24.880 --> 00:17:26.640 Um, so so good on you, AI. 00:17:26.880 --> 00:17:29.680 But why was AgTech then dropping 85%? 00:17:30.400 --> 00:17:33.599 Because two categories were really bad behavior. 00:17:33.759 --> 00:17:40.400 Um, we got overhyped controlled environment agriculture, we got overhyped

alternative protein, right? 00:17:40.640 --> 00:17:50.079 Yeah, so all the vertical farms that everyone thought was gonna take over the world and put specially crop farmers and put the end of dirt farmers out of business, how'd that work out? 00:17:50.240 --> 00:17:59.920 And all the impossible Beyond Burgers, despite Ethan and Patrick making all kinds of noise about how the cattle on my ranch are the clean coal of the protein industry, and we do remember those quotes, boys. 00:18:00.079 --> 00:18:00.480 Of course. 00:18:00.640 --> 00:18:02.720 Um, how's that working out, right? 00:18:02.799 --> 00:18:08.480 The people they needed to write them checks to buy their operations are not interested in writing checks to them when they're struggling now, right? 00:18:08.559 --> 00:18:17.279 Yeah, and so those two categories all by themselves in the entire agri-food tech segment were 42% of that$53 billion. 00:18:17.680 --> 00:18:17.920 Wow. 00:18:18.079 --> 00:18:20.720 And both of them ended up being dumpster fires. 00:18:20.880 --> 00:18:21.200 Yeah. 00:18:21.519 --> 00:18:32.400 And so, again, no exits, no MA, no cash return to the LP across 42% of$53 billion, right? 00:18:33.039 --> 00:18:37.759 No IPOs at the macro level, two bad categories at the micro level. 00:18:37.920 --> 00:18:45.279 I am now confidently predicting that we will be in the eight to twelve billion dollar tranche in agri-food tech for about five years. 00:18:46.319 --> 00:18:50.400 And do you think do you think that this is like uh like a market reset? 00:18:50.559 --> 00:18:55.039 Like this is where we're we're supposed to be, or or do you think there's more to it? 00:18:55.200 --> 00:19:11.359 Because look, I uh generally speaking, uh, and you've just mentioned it, like the the investments and and the way that the way that um VCs now uh value at different tech companies, not just in ag, right? 00:19:11.519 --> 00:19:12.319 Everywhere. 00:19:12.480 --> 00:19:22.079 Uh after after the uh the uh there was like a gold rush during the beginning of COVID, but then everything kind of plummeted. 00:19:22.160 --> 00:19:26.079 And we've seen a lot of companies here in Silicon Valley not related to a gold rush. 00:19:26.240 --> 00:19:26.799 Yeah. 00:19:27.039 --> 00:19:28.640 Not related to ag at all. 00:19:28.880 --> 00:19:33.839 Companies that uh their valuation was cut in in half and even and even worse. 00:19:34.079 --> 00:19:34.240 Yeah. 00:19:34.640 --> 00:19:43.039 Um so like I'm sure that has some um some connection with what we're seeing in ag, right? 00:19:43.119 --> 00:19:46.079 Because it just i it affected everyone, right? 00:19:46.160 --> 00:19:49.359 But you're saying that in ag it was a lot worse. 00:19:49.440 --> 00:19:59.920 And and the question I have for you is is that a reset or or just something that we're going to experience for a while, like we're in a valley now and it's gonna come up again? 00:20:00.319 --> 00:20:14.799 So I do think it's a little bit of a reset

because I think 2025 was the first point where you could say Silicon Valley is getting back to healthy because they're picking back up over 200 billion in venture capital. 00:20:14.960 --> 00:20:17.599 And yes, the bubble explodes 25% of that. 00:20:17.680 --> 00:20:19.839 Yeah, but AI is carrying a lot of freight. 00:20:20.000 --> 00:20:29.839 I mean$20 billion in revenue for ChatGPT, three in a three in a couple months, three years after after launch, unprecedented, right? 00:20:30.000 --> 00:20:33.680 And so you're seeing revenue, you're seeing build out, you're seeing established players. 00:20:33.759 --> 00:20:43.039 So Silicon Valley is riding on the backs of both ChatGPT, Anthropic, and then Google, Facebook, Apple, Microsoft, right? 00:20:43.119 --> 00:20:44.960 All who need to put in the big builds. 00:20:45.359 --> 00:20:52.079 So it looks like Silicon Valley's getting back to health, heavily based on one category, but that's not new for our valley, right? 00:20:52.319 --> 00:20:52.480 Sure. 00:20:52.640 --> 00:20:54.720 Meanwhile, agri-food tech, what has to happen? 00:20:55.039 --> 00:21:02.400 My opinion, and the reason it is systemic, in my opinion, is the LPs only come back when exits return. 00:21:02.880 --> 00:21:05.359 And right now, IPOs are really hard in ag tech. 00:21:05.599 --> 00:21:13.759 We don't have the revenue velocity or the or the absolute revenue dollars to do IPOs when I mean what's the new number, right? 00:21:13.839 --> 00:21:17.039 Twenty years ago you used to say$100 million and 25% growth. 00:21:17.119 --> 00:21:18.160 You can maybe pull one off. 00:21:18.240 --> 00:21:19.759 Now it's closer to$500 million. 00:21:20.079 --> 00:21:20.319 Right. 00:21:20.480 --> 00:21:21.759 And probably similar growth. 00:21:21.920 --> 00:21:23.039 That's a big gap. 00:21:23.200 --> 00:21:25.119 That's a and that's a big number to go after, right? 00:21:25.200 --> 00:21:27.680 If you're not anthropic and then ChatGPT. 00:21:27.839 --> 00:21:29.200 And so I think so. 00:21:29.279 --> 00:21:31.599 We won't see IPOs get ag tech out of this funk. 00:21:31.920 --> 00:21:39.599 What we will see is real companies delivering real solutions that can solve problems growers have, not problems growers didn't know they had. 00:21:39.839 --> 00:21:43.759 And so um you then look at who's gonna do the exits. 00:21:43.920 --> 00:21:52.720 It's going to be for my world, it's two categories it's the OEMs, the original equipment manufacturers, the deers, ag codes, uh, case new Hollands of the world. 00:21:52.960 --> 00:21:57.440 And then on the other side, it's the biological and and genetics folks. 00:21:57.519 --> 00:21:59.839 Um, so it's the chemistry folks and biological folks and genetics. 00:22:00.480 --> 00:22:03.279 Folks that can buy companies at decent outcomes. 00:22:03.440 --> 00:22:08.640 So John Deere and Case have been buying companies, you know, 100 to 300 million for the most part. 00:22:08.799 --> 00:22:09.759 Those are good outcomes. 00:22:10.000 --> 00:22:11.359 The chemistry guys have been a little busy. 00:22:11.519 --> 00:22:12.720 Private equity's been busy. 00:22:12.799 --> 00:22:14.640 So you see some exits coming. 00:22:15.119 --> 00:22:19.920 And as that gets liquidity back up the funnel, I think LPs will realize you know what? 00:22:20.079 --> 00:22:21.200 Labor is still a problem. 00:22:21.359 --> 00:22:22.799 We're still going to need robots. 00:22:22.960 --> 00:22:24.480 Chemistry pressure is still real. 00:22:24.559 --> 00:22:27.839 The regulatory constraints around chemistry only getting up. 00:22:28.480 --> 00:22:35.359 While I don't like to see them taking away chemistry, in my opinion, sometimes but ahead of the science, they're going to keep doing that, right? 00:22:35.440 --> 00:22:42.160 The regulators in DC, Sacramento, Europe are pretty but pretty determined to get a lot of chemistry out of play. 00:22:42.319 --> 00:22:53.279 And so if that's happening, that is headwinds for my growers in terms of margins and profitability, but it's tailwinds for the startup selling to them because those are real pressures to try new products. 00:22:53.440 --> 00:22:53.759 Yeah. 00:22:53.920 --> 00:22:56.079 Um, but and so last thought, sorry. 00:22:56.640 --> 00:23:02.960 So until grower, because grower revenue is down about 25 to 30 percent system-wide the last couple of years, right? 00:23:03.119 --> 00:23:05.519 Turns out 22 and 23 were okay years. 00:23:05.759 --> 00:23:07.200 Now we're down, now we're way down. 00:23:07.279 --> 00:23:08.319 Well, that does two things. 00:23:08.480 --> 00:23:15.599 The growers can't buy as many tractors, and the growers can't pay as much for the inputs they used to, seeds and chemists, chemistry. 00:23:15.680 --> 00:23:15.920 Yep. 00:23:16.160 --> 00:23:33.599 And so until those companies see margins return, and I would argue until they see the cost of RD becoming larger and riskier, so that corporate development and MA almost becomes a better strategic objective, you're not going to see those checks getting written. 00:23:33.680 --> 00:23:47.759 But once they see RD, and I predict they will, getting more expensive and riskier, and once they see startups with real with real solutions coming to the front, I think that checkbook will open back up from the OEMs and the Bayer Singentas of the world and the genetics folks. 00:23:47.920 --> 00:24:02.079 And once we get those those checkbooks to open back up, then the LPs will realize okay, I can fund a startup with a reasonably clear line of sight that there's an acquisition, there's an acquirer out there that at the right set of metrics would look to do a deal. 00:24:02.319 --> 00:24:02.720 Yeah. 00:24:03.200 --> 00:24:05.519 So the money, the money is gonna drive a lot of it. 00:24:06.000 --> 00:24:07.200 Money always drives everything. 00:24:07.519 --> 00:24:07.920 Surprise. 00:24:08.079 --> 00:24:08.319 Yeah. 00:24:08.400 --> 00:24:08.640 Yeah. 00:24:09.200 --> 00:24:10.640

That makes a lot of sense. 00:24:11.519 --> 00:24:30.960 Um okay, this actually connects us pretty well to the next topic that I wanted to talk to you about, which is uh adoption, trust, scale up, uh, you know, when you bring when you bring um uh new tech into the ag world. 00:24:31.200 --> 00:24:35.839 And I mean you see a lot of uh pilots across the specialty crops. 00:24:36.160 --> 00:24:49.680 Um why do you think that so many ag tech solutions uh show promise early on, but then struggle to kind of scale and reach real operational levels? 00:24:49.920 --> 00:24:50.319 Right. 00:24:50.480 --> 00:24:52.559 So it's the third hurdle, as I call it. 00:24:52.799 --> 00:24:57.599 So the first hurdle for the startup is does your product work like you wanted it to work? 00:24:57.680 --> 00:24:57.839 Right? 00:24:58.000 --> 00:24:59.279 Does it do the job? 00:24:59.519 --> 00:25:04.799 And that is generally a field trial, and you can validate that, and and we can do that in a number of ways in a number of places. 00:25:04.960 --> 00:25:06.480 Doesn't have to be done on a grower operation. 00:25:06.640 --> 00:25:11.279 You can do that on on Cal Poly land, Davis land with the call-up extension resource. 00:25:11.359 --> 00:25:13.519 Yep, checkbox, it works. 00:25:13.839 --> 00:25:16.960 Second hurdle then is does it work at scale in different conditions? 00:25:17.119 --> 00:25:24.079 So if it's wet, if it's dry, if it's hot, if it's cold, if it's night, if it's day, when does it when does it bump up against its limitations? 00:25:24.160 --> 00:25:25.359 Because growers are gonna want to know. 00:25:25.440 --> 00:25:25.759 Yeah. 00:25:26.160 --> 00:25:31.039 And that's a series of tests, series of trials over years in different locations, different soil types, etc. 00:25:31.359 --> 00:25:32.960 Okay, second box, we check that. 00:25:33.039 --> 00:25:40.079 And that can also be done on UC land, CSU land, um land grant universities with co-op extension, all good, right? 00:25:40.160 --> 00:25:41.920 Doesn't have to be growers. 00:25:42.079 --> 00:25:52.079 But the third hurdle, and this is the big one for every startup, does it work as intended and in different conditions at economics that work for the grower? 00:25:52.480 --> 00:25:53.279 That is the key. 00:25:53.359 --> 00:25:55.839 And that's where I see so many startups really struggle. 00:25:55.920 --> 00:26:06.000 So that crossing the chasm analogy from technology and Jeffrey Moore in AgTech, it's always getting it from works in multiple conditions to works at grower's math. 00:26:06.079 --> 00:26:12.160 And so we work really hard with startups and growers to develop a common framework around what does that look like. 00:26:12.400 --> 00:26:32.480 And the two steps are you have to tie your solution to the problem statement and the financial statement for the grower, and you have to then do an extensive comparison of what did year one look like without my product, and what did year two look like with my product, and how does that math impact the grower's operation? 00:26:32.799 --> 00:26:37.599 So this is I think I think uh you're exactly right with the the grower's math. 00:26:37.920 --> 00:26:53.039 Because I I think a lot of uh a lot of companies, a lot of tech companies, they go into uh a meeting with the grower, and they have they did all the math, they have extensive uh uh um spreadsheets, right? 00:26:53.200 --> 00:27:05.759 Right that it that tells you exactly how by implementing this product uh your ROI is this and that because you're not only uh making more money, you're also saving more money, but da da da da. 00:27:06.319 --> 00:27:10.880 And it's like it makes sense to them, and it really does, right? 00:27:11.359 --> 00:27:18.160 But if the grower can't understand it, or in his head, it doesn't math out, right? 00:27:18.480 --> 00:27:20.319 Then there's nothing you can say. 00:27:20.480 --> 00:27:20.799 That's right. 00:27:20.880 --> 00:27:23.359 Like there's absolutely nothing that you can say. 00:27:23.680 --> 00:27:36.640 You need to know how to speak the grower's language, the farmer's language, um, and and uh and actually deliver what you're saying you're gonna you're gonna, you know. 00:27:36.960 --> 00:27:37.279 Yeah. 00:27:37.519 --> 00:27:48.559 Um otherwise, yeah, people people I I think I think working with the agricultural community is just different than just uh any consumer product. 00:27:48.799 --> 00:27:50.559 It's it's really it's really different. 00:27:50.720 --> 00:27:54.960 These are people that uh a lot of times they're very cynical. 00:27:55.599 --> 00:28:00.000 Um they they don't easily trust just anyone. 00:28:00.559 --> 00:28:10.000 Um I got comments, you know, when I was going to meetings early on in the early days of Be Hero when AgTech was still kind of new, right? 00:28:10.160 --> 00:28:10.799 Yeah. 00:28:11.200 --> 00:28:14.319 And I came in with uh with an F-150. 00:28:14.480 --> 00:28:16.400 This is the truck that I drive. 00:28:17.039 --> 00:28:23.680 And growers told me explicitly, you know how I know you're you know what you're talking about? 00:28:23.839 --> 00:28:24.960 This is what you drive. 00:28:25.119 --> 00:28:29.039 I get startup companies come here in their Toyota Prius, and I know immediately. 00:28:29.279 --> 00:28:30.640 They're Model S Tesla. 00:28:30.880 --> 00:28:31.359 Yeah, exactly. 00:28:31.440 --> 00:28:31.759 Yeah, yeah. 00:28:31.920 --> 00:28:34.000 And it's like I I didn't even think of that. 00:28:34.160 --> 00:28:37.359 Like I grew up on a farm, I drove pickup trucks trucks my entire life. 00:28:37.519 --> 00:28:41.359 I got to America, I was like, I'm gonna buy a pickup truck, you know? 00:28:41.680 --> 00:28:43.599 And so this is my daily. 00:28:44.079 --> 00:28:49.119 Um and yeah, those things really matter. 00:28:49.599 --> 00:28:59.759 Uh, and I think that people like they they have a really good offering, but they don't understand that the grower doesn't want

that, right? 00:29:00.000 --> 00:29:06.079 And you have to you have to um adjust yourself and the product to what the growers actually are looking for. 00:29:06.319 --> 00:29:08.000 Yep, no, it's exactly right. 00:29:08.079 --> 00:29:15.680 So, what we did at Western Growers the last year and a half, we launched the case study program, and Ben Pillow and my colleague has been tremendous. 00:29:15.920 --> 00:29:20.480 We actually looked at year one for a for a carbon robotics, the laser weeder, right? 00:29:20.640 --> 00:29:24.799 And we said, okay, let's go to one of the early movers that bought carbon. 00:29:24.960 --> 00:29:35.279 We went to Braga Fresh, I mentioned them earlier, and we asked the Braga team, we said, Hey, what did it look like for you to do manual weeding across a lot of these acres over a year? 00:29:35.359 --> 00:29:37.279 And what did it look like once the robot came in? 00:29:37.359 --> 00:29:39.359 And they said, Well, let's take a look. 00:29:39.519 --> 00:29:44.799 So we did 3,200 acres worth of analysis, all certified organic, eight different crop types. 00:29:44.880 --> 00:29:46.240 That's where the robots work the best, right? 00:29:46.319 --> 00:29:48.720 Because organic, so many more labor hours, right? 00:29:49.039 --> 00:29:56.960 Um and they said for 3,200 acres, one year, the hand weeding labor all on its own,$2.1 million. 00:29:57.759 --> 00:30:06.079 Then they said when we added carbon robotics, a$1.4 million robot, yes, that same acreage, one year later,$1.3 million. 00:30:06.240 --> 00:30:06.799 Oh wow. 00:30:07.039 --> 00:30:11.440 That$800,000, that's how you ROI a$1.4 million laser weeder, right? 00:30:11.519 --> 00:30:11.680 Right. 00:30:11.839 --> 00:30:17.599 But until we did that case study, we couldn't say with conviction that we knew the math worked for growers. 00:30:17.759 --> 00:30:18.880 Now we can. 00:30:19.039 --> 00:30:20.799 Now they can see that case study. 00:30:20.880 --> 00:30:25.680 And then we went one step further, and this is really cool, and Ben and I love this part. 00:30:25.920 --> 00:30:30.960 We gave them a template that any grower can use to say, look, your operation's different. 00:30:31.119 --> 00:30:37.920 You may be using H2A, you may be using direct labor, you may be using domestic labor, you may be using lease tractors, you may buy your tractors, right? 00:30:38.559 --> 00:30:43.920 You put in your math, and we'll tell you what the ROI should look like on your operation. 00:30:44.079 --> 00:30:45.119 And that's been really cool. 00:30:45.279 --> 00:30:48.559 So basically, we we now shortcut two steps for you. 00:30:48.720 --> 00:30:53.279 We'll show you the Braga case study, and we'll give you the template to do the math on your own. 00:30:53.599 --> 00:30:55.359 That's super interesting. 00:30:55.920 --> 00:31:10.319 Um and usually when you see tech tech and automation meet, you know, the real life farming, what from your experience at least, uh uh what's the first thing

to break normally? 00:31:11.200 --> 00:31:12.319 Well, you'll laugh. 00:31:12.400 --> 00:31:14.240 It's that human piece, right? 00:31:14.559 --> 00:31:22.319 So uh we've seen this from Burrow, the little harvest assist guy, all the way up to you know, mechanical weeding robots, laser weeding robots. 00:31:22.640 --> 00:31:34.079 If you can't get that technology to integrate in with the operations team through either a direct sales team or a channel sales partner, the equipment graveyard is real, right? 00:31:34.319 --> 00:31:38.400 People have spent six and seven figures on equipment for decades in this valley. 00:31:38.480 --> 00:31:38.720 Right. 00:31:38.880 --> 00:31:40.160 And not all of it works, right? 00:31:40.319 --> 00:31:41.119 Why does that happen? 00:31:41.440 --> 00:31:43.279 Key guy leaves at the wrong time, right? 00:31:43.440 --> 00:31:47.039 Could be a key guy at the operations team, could be a key guy at your seller partner, right? 00:31:47.279 --> 00:31:52.960 Let's see you got a good dealer, but that dealer loses the top rep who relocates, you you've got a mess on your hands, right? 00:31:53.039 --> 00:31:58.720 And so the startup's job is never done because if you're selling direct, you got to make sure that rep's doing the job. 00:31:58.799 --> 00:32:02.079 If you're selling through channel, you gotta make sure that rep's doing the job and you dotted line. 00:32:02.160 --> 00:32:03.599 You don't sell a line to that guy. 00:32:03.759 --> 00:32:04.000 Yeah. 00:32:04.160 --> 00:32:07.680 Um, and then you gotta make sure the operations team has their guy. 00:32:07.759 --> 00:32:16.319 So, I mean, the key guys are those touch points, and until everything's in place and everything's integrated, the job is not done. 00:32:16.559 --> 00:32:17.200 Yeah. 00:32:17.519 --> 00:32:27.680 And uh the even even in um uh in a traditional um industry like agriculture, you still have the early adopters. 00:32:27.759 --> 00:32:38.000 People that want to try it first, they they they look at something, they think it's so cool and can uh help them in the future, and they're willing to spend some money or time uh to try it out. 00:32:38.400 --> 00:32:43.759 Um so let's let's say that getting to the early adopters is the easy part, right? 00:32:43.920 --> 00:32:44.079 Right. 00:32:44.160 --> 00:32:50.799 Like you'll find them eventually, and and they're early adopters, they'll want you, they'll let you try stuff on their field. 00:32:51.119 --> 00:32:58.799 How like what type of uh proof points the normal folk um usually are looking for? 00:32:59.039 --> 00:32:59.519 Yep. 00:32:59.839 --> 00:33:01.119 So I would say two things. 00:33:01.200 --> 00:33:03.759 Let's back up to that, find the early adopter part, right? 00:33:04.160 --> 00:33:14.400 I would argue let's find a medium to large size early adopter because they'll have the resources you need to do a successful pilot and rollout way more often than the little guys. 00:33:14.640 --> 00:33:16.559 Not their fault, just they don't have the resources, right? 00:33:17.039 --> 00:33:32.000 So if you're at Tularie next week at World Ag Expo, if you're at World AgriTech in a couple weeks in San Francisco, your first job as a sales and marketing team member of a startup is I need to identify whether this guy is a customer now or a customer in five years. 00:33:32.319 --> 00:33:39.279 Because if I start working with that customer in five years now, I am wasting resources I do not have to waste. 00:33:39.440 --> 00:33:43.359 So I would argue job one at the trade show floor is have a lot of conversations. 00:33:44.000 --> 00:33:47.839 But job two is have a lot of qualifying conversations. 00:33:48.000 --> 00:33:48.240 Right. 00:33:48.400 --> 00:33:50.000 How do you identify early adopters? 00:33:50.160 --> 00:33:51.440 Tell me about your farm. 00:33:51.680 --> 00:33:53.759 Tell me about the equipment you're using on the farm. 00:33:53.920 --> 00:34:02.720 If they're talking about 30-year-old tractors and 40-year-old tractors and and they don't mention anything shiny and new, maybe not an early adopter, right? 00:34:02.960 --> 00:34:03.839 So dig in a little. 00:34:04.000 --> 00:34:06.079 Hey, what robots have you tried? 00:34:06.240 --> 00:34:08.000 What robots have you rolled out? 00:34:08.159 --> 00:34:11.119 What robots have you seen work for you in your operation? 00:34:11.280 --> 00:34:16.239 If they haven't tried stuff, if they haven't rolled stuff out, if it hasn't worked, they're probably not your guy either, right? 00:34:16.320 --> 00:34:18.239 Even when they try stuff, it doesn't work. 00:34:18.400 --> 00:34:21.440 That's a red flag for a startup because you will get blamed for that. 00:34:21.519 --> 00:34:23.039 You will take the brand hit for that, right? 00:34:23.440 --> 00:34:23.760 Always. 00:34:23.920 --> 00:34:32.320 Um, and very often, and I I won't name any names, but I mean, growers will under-resource, not their fault, they just expectations were set wrong in a lot of cases. 00:34:32.400 --> 00:34:36.320 They'll under-resource trials so they don't go well, so the rollout never happens. 00:34:36.480 --> 00:34:36.800 Yep. 00:34:37.039 --> 00:34:47.039 You want to identify folks who have tried early technologies, gone through multiple successful and failed tests, lived through the other side, and then bought and rolled out stuff. 00:34:47.119 --> 00:34:55.119 If they haven't done stuff that tried and failed and succeeded and failed, and then rolled stuff out, you want to keep on moving, right? 00:34:55.199 --> 00:34:59.440 Or at least put them down the priority queue from a Salesforce or a CRM perspective, right? 00:34:59.519 --> 00:35:16.559 So for me, you've got to find the early adopter, you've got to then find the successful quote unquote early adopter, and you've got to really over-service that guy because the only way you're gonna get to that mid-sized guy behind the large guy is by finding a mid-sized guy to buy

and make him a reference account. 00:35:16.719 --> 00:35:16.880 Yeah. 00:35:17.039 --> 00:35:24.480 He's not gonna, your average 500,000-acre guy, they're not gonna look at Taylor Farms or Driscoll's Berries or Braga Fresh and say, Oh, it's a great case study. 00:35:24.559 --> 00:35:25.360 It's just like me. 00:35:25.519 --> 00:35:26.639 It's not just like them. 00:35:26.719 --> 00:35:26.960 Yeah. 00:35:27.119 --> 00:35:36.079 So you need to go for you need to downscale it from Taylor and Braga and Driscoll's down to another 500-acre operator so your sales team could say, you know what? 00:35:36.320 --> 00:35:37.840 We did test with those guys. 00:35:38.000 --> 00:35:40.079 They did well, different set of math. 00:35:40.239 --> 00:35:47.840 Here's the test we did with a guy that looks like you 500 acres, middle of Salinas Valley, growing leafy greens, maybe not vertically integrated, maybe just a grower. 00:35:48.320 --> 00:35:50.079 So let's help you understand what you need. 00:35:50.159 --> 00:36:00.320 So that's that's where I see a lot of folks struggle, is even when they get the whale account that is the early adopter, moving downstream to scale out sales, still really hard. 00:36:00.559 --> 00:36:09.199 Yeah, I think it also relates to just generally the the um um how well known they are in the industry. 00:36:09.280 --> 00:36:11.920 If they're considered to be thought leaders, 100%. 00:36:12.320 --> 00:36:16.480 Uh then that also helps um on top of like their size. 00:36:16.639 --> 00:36:18.159 But usually it comes together. 00:36:18.400 --> 00:36:18.639 Right. 00:36:18.800 --> 00:36:30.800 Uh I mean, people that grow 20 acres uh because they've owned this piece of property forever, uh, they don't always tend to uh to be very vocal in the industry, you know. 00:36:31.119 --> 00:36:31.440 Right. 00:36:31.599 --> 00:36:32.800 Uh sometimes they are. 00:36:33.039 --> 00:36:33.920 No, you're exactly right. 00:36:34.000 --> 00:36:35.360 There are a lot of quiet growers, right? 00:36:35.519 --> 00:36:36.800 They just don't make a lot of noise. 00:36:37.039 --> 00:36:43.679 And um and that's okay, but they're gonna want to hear from you that you've got someone that profiles and pattern matches to them. 00:36:43.920 --> 00:36:44.320 Exactly. 00:36:44.480 --> 00:36:45.199 Which is the key. 00:36:45.280 --> 00:36:47.840 So no, it's it's it's a tricky sales process. 00:36:48.159 --> 00:37:00.000 This does go to an issue I talk a lot about with both growers and startups is look, if you're you're coming from Israel, you're coming from South America, you're coming from Europe, you're entering the California market. 00:37:00.079 --> 00:37:01.039 You know this, right? 00:37:01.360 --> 00:37:04.079 You get to the California market, what's the first two things you learn? 00:37:04.239 --> 00:37:05.519 Wow, is this a big market? 00:37:05.599 --> 00:37:06.960 And wow, is this complicated? 00:37:07.199 --> 00:37:07.519 Sure. 00:37:07.760 --> 00:37:14.079 So having a sales partner with you on some of this journey is, in my opinion, tremendously beneficial. 00:37:14.320 --> 00:37:18.960 And I think, and it's funny, I've mixed it up with some of the startup CEOs say, no, no, it's got to be direct, I have to control it. 00:37:19.440 --> 00:37:20.880 Okay, okay, fair enough. 00:37:21.039 --> 00:37:25.920 But understand when you say that, so I graduated high school in '83, King City, down in Monterey County. 00:37:26.559 --> 00:37:27.920 Comp alle 88, right? 00:37:28.079 --> 00:37:28.960 Five-year plan. 00:37:29.280 --> 00:37:40.880 Um there's guys that went to high school and went to college with me that are now growers and sales guys who are selling to each other for decades. 00:37:41.119 --> 00:37:41.519 Right. 00:37:41.760 --> 00:37:50.320 You can walk into that and win a sale, but you better be good and you better be able to create a relationship capital very fast because those guys have known each other. 00:37:50.559 --> 00:37:56.239 Their kids have been at school sports together, their kids have been at, you know, parties together. 00:37:56.400 --> 00:37:59.199 I mean, it's a whole different world full of relationships. 00:37:59.840 --> 00:38:04.400 Relationships in agriculture is is uh something that is precious. 00:38:04.639 --> 00:38:12.639 It's like it's very, very important being able to form new relationships uh and maybe capitalize on old ones. 00:38:12.800 --> 00:38:13.119 Yeah. 00:38:13.280 --> 00:38:16.159 Um yeah, it's I mean your dad lived it. 00:38:16.400 --> 00:38:16.960 He did. 00:38:17.119 --> 00:38:17.360 Right? 00:38:17.519 --> 00:38:18.320 Yeah, still does. 00:38:18.400 --> 00:38:18.800 Yeah. 00:38:19.519 --> 00:38:21.599 And now he's got incumbent advantage, right? 00:38:22.000 --> 00:38:22.880 Uh a hundred percent. 00:38:23.039 --> 00:38:23.440 It's huge. 00:38:23.599 --> 00:38:24.079 A hundred percent. 00:38:24.239 --> 00:38:24.639 It's huge. 00:38:24.719 --> 00:38:26.239 So that's so you think about it. 00:38:26.400 --> 00:38:31.679 You're walking in with a new robot, you've got no relationship capital in Salinas Valley. 00:38:31.840 --> 00:38:36.320 You built this robot for five years in Israel, you've asked for the meeting. 00:38:36.480 --> 00:38:36.960 Yeah. 00:38:37.199 --> 00:38:38.800 Where do you start with that guy? 00:38:39.039 --> 00:38:39.360 Yeah. 00:38:39.679 --> 00:38:40.639 It's super hard. 00:38:40.960 --> 00:38:42.400 It is it is very hard. 00:38:42.559 --> 00:38:51.199 Um but I think a good way to form new relationships is with uh credibility. 00:38:51.519 --> 00:38:52.000 Absolutely. 00:38:52.239 --> 00:38:59.920 If if you show credibility, if you show that uh that you do what you said you would, um people appreciate it here. 00:39:00.079 --> 00:39:13.760 When you shake someone's hand and your word is your bond, you know, even if you don't know each other, but you prove it, um that forms that forms a relationship uh pretty fast. 00:39:14.000 -->

00:39:20.079 Still hard to beat a 20, 30, 40 year long relationship, but it's a good start. 00:39:20.320 --> 00:39:21.039 I totally agree. 00:39:21.360 --> 00:39:21.920 Yep, yep. 00:39:22.000 --> 00:39:23.360 No, you have to you have to make it happen. 00:39:23.440 --> 00:39:29.679 And that's that's why I tell every startup, I said, as you're coming to California, think hard about where you set up shop. 00:39:29.760 --> 00:39:30.079 Yeah. 00:39:30.239 --> 00:39:34.320 Think about your primary crop type and set up shop within 30 miles of a lot of them. 00:39:34.480 --> 00:39:34.719 Yeah. 00:39:34.880 --> 00:39:37.199 So if you're in trees, go by the tree people. 00:39:37.280 --> 00:39:37.440 Yeah. 00:39:37.519 --> 00:39:39.840 If you're in row crops, go by the row crop people. 00:39:40.000 --> 00:39:42.239 If you're in lettuce, go to Salinas Valley, right? 00:39:42.480 --> 00:39:42.719 Yeah, yeah. 00:39:42.880 --> 00:39:44.320 Don't set up shop in San Jose. 00:39:44.400 --> 00:39:46.639 Don't set up shop in, you know, San Francisco. 00:39:46.880 --> 00:39:52.000 Set up shop closer to the fields where you're gonna want to be in, and then get in those fields all the time. 00:39:52.320 --> 00:39:58.400 The first thing we've done before we had an actual office was get uh uh uh a Fresno address. 00:39:58.639 --> 00:39:59.840 That's right, I remember that. 00:40:00.400 --> 00:40:00.960 Yep. 00:40:01.199 --> 00:40:02.639 So we do have an office. 00:40:02.719 --> 00:40:06.079 Uh we're not in Fresno, we're in Del Rey, but uh in that area. 00:40:06.400 --> 00:40:09.679 Problem is the Central Valley is pretty big. 00:40:09.920 --> 00:40:10.400 It's huge. 00:40:10.559 --> 00:40:11.679 I know I agree. 00:40:12.320 --> 00:40:16.159 We're 30 The Mercedes to Bakersfield corridor is not an easy drive. 00:40:16.400 --> 00:40:16.880 Yeah, yeah, yeah. 00:40:17.360 --> 00:40:17.760 100%. 00:40:18.239 --> 00:40:25.599 Yeah, I I I once visited uh uh one of our growers up in Williams and then in Bakersfield on the same day. 00:40:25.920 --> 00:40:28.159 That was that was a drive. 00:40:28.400 --> 00:40:36.639 So And you know, for as wide open as it is, there's a lot of times where you're sitting on that freeway, either the five or the 99, and you just gotta grind traffic. 00:40:36.960 --> 00:40:39.280 Oh, 100% in the 99 afternoon? 00:40:39.519 --> 00:40:40.880 Yeah, no, thank you. 00:40:41.119 --> 00:40:47.119 Um I wanted to ask you about uh um uh w weather and volatility, right? 00:40:47.280 --> 00:40:55.199 Because not everything, you know, uh um new technology can necessarily solve or or control, right? 00:40:55.519 --> 00:41:02.559 Um but uh the short term weather volatility seems to be increasing. 00:41:02.800 --> 00:41:19.039 And uh how do you think that raises the bar for different Arctic solutions um that are supposed to to kind of support mid-season decisions when you don't when you can't even really uh predict what the weather is gonna look like this year or this season? 00:41:19.280 --> 00:41:19.679 Yeah. 00:41:19.920 --> 00:41:23.920 So I think it does two things, and it's funny, neither of them are really ag related, right? 00:41:24.320 --> 00:41:35.199 Number one, it changes the grower's risk profile because when one out of five years is gonna get a bad weather event instead of one out of twenty, I've got four times the risk, right? 00:41:35.360 --> 00:41:35.599 Of course. 00:41:35.840 --> 00:41:41.280 And so the grower has to allow for that risk and leave some extra margin in there in case that happens. 00:41:41.519 --> 00:41:45.840 And the second thing that happens is I didn't I didn't reduce my margin to manage that risk. 00:41:45.920 --> 00:41:46.400 And guess what? 00:41:46.480 --> 00:41:47.760 I don't have enough money to buy. 00:41:48.000 --> 00:41:49.360 Ag tech, right? 00:41:49.599 --> 00:41:54.880 And so I would say um the increased weather weather volatility is definitely real. 00:41:55.199 --> 00:41:58.639 And the other impact is it can it can impact your yields. 00:41:58.719 --> 00:42:14.559 Like I've got our neighbor down in South County in Monterey County, he's an uh an olive grower, and they had, I believe the nightmare scenario he had was early heat that caused the blooms to get faked out and realize I need to I need to start, and then late frost. 00:42:15.280 --> 00:42:20.159 So his yield was like not 20% off, 20% of normal, right? 00:42:20.320 --> 00:42:24.480 So he was like 80% light for that whole year across 7,000 trees. 00:42:24.559 --> 00:42:25.360 That's a problem. 00:42:25.519 --> 00:42:30.960 It is uh luckily he has a mill, and the mill did well that year, but that that doesn't save everybody, right? 00:42:31.199 --> 00:42:31.440 No. 00:42:31.599 --> 00:42:36.800 Um and so I think the weather is just like so many other risk factors, right? 00:42:36.960 --> 00:42:42.400 Regulatory, uh markets, international markets coming over here and putting pressure on prices. 00:42:43.039 --> 00:42:45.599 Um the grower always looks for two things. 00:42:45.679 --> 00:42:50.400 All right, what's the scope of the risk, and how can I mitigate that risk most effectively? 00:42:50.639 --> 00:42:54.719 Sometimes it's tech, sometimes it's operational, sometimes it's something else. 00:42:54.880 --> 00:42:55.199 Yeah. 00:42:55.360 --> 00:42:57.440 But that's their framework is always the same. 00:42:57.599 --> 00:42:59.280 All right, how big is that new risk? 00:42:59.440 --> 00:43:06.079 And how can I get it down not to zero, but how can I get it if it's a if it's a 10 going to 11, how do I get it down to two? 00:43:06.400 --> 00:43:06.639 Yeah. 00:43:06.880 --> 00:43:10.079 And if you're if your solution can help with that, they are listening. 00:43:10.400 --> 00:43:34.800 And with all those uh um changes or or um with all this unpredictability, do you think growers are looking more for for um solutions, technologic technological solutions that are able to help them react really quickly,

or learn from what happened after the fact, right? 00:43:34.960 --> 00:43:45.280 Learn from what happened, gather that data and and uh and change their the way they do things uh for the next season or or the following. 00:43:45.599 --> 00:43:45.840 Right. 00:43:46.079 --> 00:43:47.679 So everyone would love real time. 00:43:47.920 --> 00:43:48.079 Sure. 00:43:48.239 --> 00:43:52.159 But it's the most expensive and the least accurate in a lot of cases, because it is real time. 00:43:52.320 --> 00:43:52.559 Yeah. 00:43:52.719 --> 00:43:59.119 So what they'll definitely take, because they know that this is more realistic, is all right, to your point, let me get smarter from this season. 00:44:00.239 --> 00:44:03.039 Next rotation or next season, I can I can do better, right? 00:44:03.199 --> 00:44:22.079 And so so whatever method that is, whether that's sensors, whether it's you know, satellites, whether it's drones, whether it's ground truth, um, how can I get data off this rotation, this acre, this block, that I can then put into an analytics tool and give me a better planting plan for next time, right? 00:44:22.239 --> 00:44:22.320 Yeah. 00:44:22.559 --> 00:44:29.679 When where I do think there's gonna be a lot of progress the next five years, and this is partly because of the AI evolution, right? 00:44:30.000 --> 00:44:36.719 Is you're going to see disparate data sets, like not just the field data on your stuff, but what about the market conditions? 00:44:36.880 --> 00:44:40.719 How many acres are planted of X, how many acres are planted of Y? 00:44:41.119 --> 00:44:53.679 And the more you know about how many acres of iceberg is out there, acres of Romaine is out there, maybe you change your rotation strategy a little bit that year and move some of the acres to something else because that looks like there's going to be a market gap. 00:44:53.840 --> 00:45:12.400 So I think that that match between real-time data in the real world about what's coming to market and real-time to last season time data about what's best planted on your acreage can lead to a whole opportunity of recommendation engines that don't need hardware. 00:45:12.559 --> 00:45:12.719 Right. 00:45:12.960 --> 00:45:14.320 It's a different solution. 00:45:14.480 --> 00:45:19.440 And when you look at some of the, I mean, you th they're vibe coding ERP apps, for goodness sake, right? 00:45:19.679 --> 00:45:20.079 Yeah, yeah, yeah. 00:45:20.480 --> 00:45:29.360 Um, so what could a grower operations team vibe code over a couple of weeks in a rotation that actually does some nice data analytics work? 00:45:29.440 --> 00:45:30.800 I'm very curious to see. 00:45:31.039 --> 00:45:31.599 Yeah. 00:45:31.920 --> 00:45:39.679 And you've said that growers respond best to technologies that kind of reduce uncertainty and and support real decision making. 00:45:40.320 --> 00:45:42.800 So I gotta talk about pollination. 00:45:42.960 --> 00:45:43.920 I mean, it's February. 00:45:44.079 --> 00:45:45.519 We're we're just about to start. 00:45:45.920 --> 00:45:48.960 I can't, I can't uh I can't not talk about it. 00:45:49.280 --> 00:46:03.199 So when you look at companies like Behero, that you know, we we we take the approach of of combined biology, uh operations, and and and data into something that growers can actually act on. 00:46:03.440 --> 00:46:14.639 So how do you think that approach um answers the growers uh uh questions, or is it answering the grower question at all? 00:46:14.880 --> 00:46:26.079 Uh the the the attempt to kind of try and use the biology as well uh as as part of what you're doing and not just okay, it's there, I have I I can't really do anything about it. 00:46:26.400 --> 00:46:26.960 Right. 00:46:27.360 --> 00:46:30.719 So this is where automation is so different than this stuff, right? 00:46:30.800 --> 00:46:30.880 Yeah. 00:46:31.119 --> 00:46:37.760 Automation, I run the laser weeder through the field, I can measure what it got, I can measure what it didn't got, I can I can measure all of it, right? 00:46:38.239 --> 00:46:39.760 And causation's pretty obvious. 00:46:39.920 --> 00:46:40.239 Yeah. 00:46:40.480 --> 00:46:48.079 With pollination, with biologicals, with genetics, with regenerative ag, it's really so correlation is a little easier. 00:46:48.239 --> 00:46:50.480 I can say, okay, if I did this, this happened. 00:46:50.800 --> 00:46:52.480 Causation gets really hard, right? 00:46:52.559 --> 00:47:03.599 So I think where you guys are doing a nice job is in putting that correlation status into causation status, back to the earlier discussion, with grower math, right? 00:47:03.760 --> 00:47:04.000 Yeah. 00:47:04.239 --> 00:47:06.880 So what does the grower need out of pollination, right? 00:47:07.039 --> 00:47:08.400 Is it is it more yield? 00:47:08.639 --> 00:47:09.599 Is it more certainty? 00:47:09.679 --> 00:47:10.559 Is it more predictability? 00:47:10.639 --> 00:47:11.199 Is it something else? 00:47:11.280 --> 00:47:18.400 Well, again, where on the financial statement are you guys able to have an impact and and what were you able to measure that impact at? 00:47:18.559 --> 00:47:19.920 And then you can have the discussion, right? 00:47:20.079 --> 00:47:23.039 Okay, that guy's special because he's got X, Y, and Z. 00:47:23.199 --> 00:47:24.159 Not everyone does. 00:47:24.320 --> 00:47:30.000 I mean, example, if you're already doing regenerative ag, maybe the pollinator is 2x more effective, right? 00:47:30.159 --> 00:47:30.320 Yeah. 00:47:30.480 --> 00:47:33.519 If you're already doing good soil health, maybe it's two times more effective. 00:47:33.679 --> 00:47:37.440 So you need to be able to say, that guy's soil health was this. 00:47:37.679 --> 00:47:38.320 So Mr. 00:47:38.400 --> 00:47:38.800 and Mrs. 00:47:38.960 --> 00:47:46.719 Next Post, next customer, you know what, if your soil health isn't that, we're not sure what your results are going to be, but we'd like to test it with you to find

out. 00:47:46.880 --> 00:47:47.199 Yeah. 00:47:47.679 --> 00:48:01.760 Yeah, I think I I think trying to understand exactly how like the behavior of of your crop based on uh everything else that happens in the farm, it's really hard. 00:48:01.840 --> 00:48:02.239 Yeah. 00:48:02.400 --> 00:48:07.519 Uh, but it's also super important in order in order to be uh successful. 00:48:07.840 --> 00:48:22.719 Um so yeah, I guess I don't have like uh uh an epiphany here, but I I'm just saying this the the the combination of all the different uh things that that happen in the orchard. 00:48:23.039 --> 00:48:31.280 Um because this is how biologically everything was engineered over uh I guess millions of years. 00:48:31.599 --> 00:48:32.079 Exactly. 00:48:32.239 --> 00:48:41.519 Uh and we need to somehow tap into that, understand how it works to the best of our ability and and and try to make it a little bit better. 00:48:41.679 --> 00:48:42.159 Yeah. 00:48:42.400 --> 00:48:53.440 Um I want to ask you before we kind of we s we're getting close to the end of of our conversation, and I want to ask you a hard question. 00:48:54.480 --> 00:49:00.320 Um you've watched multiple actic cycles uh come up and go. 00:49:00.719 --> 00:49:26.159 Um what's what from your perspective the hardest truth about ag innovation that the industry still avoids admitting that some functions, and I'll use harvest as an example, may never, and definitely are not at the moment, great fits for venture capital. 00:49:26.400 --> 00:49:39.280 As much as we want to tell every founder, go out and raise a bunch, go conquer the world, go take it on, go build that unicorn, go, you know, cash out your stock and go get that house and you know, whatever, Menlo Park. 00:49:39.920 --> 00:49:42.559 That's not always realistic for AgTech. 00:49:42.800 --> 00:49:45.360 When you look at harvest, like look at the weeding, right? 00:49:45.440 --> 00:49:49.760 So for weeding, one machine can do 80 crops, right? 00:49:49.840 --> 00:49:51.679 I mean, we're up we're up to massive crop loads. 00:49:51.760 --> 00:49:52.079 Yep. 00:49:52.400 --> 00:49:58.000 But for harvest, we haven't yet seen a machine conquer one crop, sure, let alone two. 00:49:58.079 --> 00:50:00.559 So the TAM are automatically smaller. 00:50:01.519 --> 00:50:21.360 The dev cycle's inherently longer because finding a weed and destroy it a little easier, not easy, but easier than find that apple, that head of lettuce, that pick your pick your favorite, identify the ones that are ready to pick, pick them very carefully. 00:50:21.599 --> 00:50:25.119 Because you don't want to destroy them, and put them in a bin very carefully. 00:50:25.519 --> 00:50:26.320 That's a lot. 00:50:26.480 --> 00:50:26.960 It is. 00:50:27.119 --> 00:50:39.519 And so we've come to the conclusion, Western growers, that harvest is going to be the last mile for automation, which is frustrating for my especially crop growers because two-thirds of the hours are harvest. 00:50:40.480 --> 00:50:45.519 And so we've looked at it, all the good results are happening in non-harvest. 00:50:45.599 --> 00:50:47.920 The weeding, the planting, the thinning, the harvest assist. 00:50:48.000 --> 00:50:48.239 Yep. 00:50:48.480 --> 00:50:51.519 $250 million category last year. 00:50:51.760 --> 00:50:53.119 On its way to a billion. 00:50:53.280 --> 00:50:59.039 Venture capitalists understand it, they're writing checks, startups are doing the work, carving the miles, all good. 00:50:59.360 --> 00:51:03.920 Harvest, we've got virtually no success in fresh produce harvest. 00:51:04.159 --> 00:51:06.960 And so we're taking on some new approaches this year. 00:51:07.039 --> 00:51:07.360 Yeah. 00:51:07.599 --> 00:51:10.639 And we're gonna use non-venture capital to make an app. 00:51:10.719 --> 00:51:12.800 We're gonna use grower capital and partner capital. 00:51:13.039 --> 00:51:21.360 And the whole goal of that is the automation solutions that are in market now, we believe that it's 50 to 100 million in venture capital to get them to commercialize. 00:51:21.440 --> 00:51:24.880 Yeah, we want to cut that number by a half to two-thirds if we can. 00:51:25.119 --> 00:51:26.000 Well, that will be great. 00:51:26.559 --> 00:51:33.119 Because we're not confident that we can get 50 to 100 million dollars for every specialty crop, even the popular ones. 00:51:33.360 --> 00:51:42.239 And we are confident that we can work with non-startup-scale RD teams to get to an outcome, right? 00:51:42.320 --> 00:51:51.920 Think about the original manufacturers, think about the the Voss, uh the the the companies, uh GK, um, all these manufacturing companies that are around here. 00:51:52.480 --> 00:51:56.159 Um the names are escaping me at the moment. 00:51:56.239 --> 00:52:02.639 Um, but basically, uh Milano Technical Group, some of these guys, these guys are used to working on pay for hire. 00:52:02.960 --> 00:52:05.119 Uh, Andros is the guy in Passer Robles. 00:52:05.360 --> 00:52:08.960 So you've got all these guys where they're used to pay me and I'll build. 00:52:09.119 --> 00:52:10.079 Pay me and I'll build. 00:52:10.559 --> 00:52:11.760 They don't need a hockey stick. 00:52:11.920 --> 00:52:12.079 Right. 00:52:12.239 --> 00:52:13.679 They don't need a unicorn outcome. 00:52:13.840 --> 00:52:21.280 We want to work with those players to try and get them to non-venture capital development outcomes so we can sell to our growers. 00:52:21.440 --> 00:52:24.000 It's working with the Strawberry Center in Cal Poly right now, right? 00:52:24.079 --> 00:52:35.199 The Strawberry Commission funded an entire set of initiatives around automation because they realized everything but harvest for strawberry on the manual labor front is not venture capital scale. 00:52:35.440 --> 00:52:35.760 Really? 00:52:36.000 --> 00:52:41.840 So they looked and they realized, okay, yes, strawberry is 60% of the labor for harvest, but 40% is not. 00:52:41.920 --> 00:52:46.639

And those are like 10 to 11 disparate tasks that I need automated to have my labor problem. 00:52:46.800 --> 00:52:46.880 Yeah. 00:52:47.039 --> 00:52:49.599 And they looked at Cal Poly and they said, all right, here's our list. 00:52:49.840 --> 00:52:51.039 Here's the top five. 00:52:51.199 --> 00:52:51.760 And guess what? 00:52:51.920 --> 00:53:03.280 Over 10 years at the Strawberry Center, with the industry funding professional engineers to stand up student teams on campus at Cal Poly, they've gotten three machines and three different tasks. 00:53:03.840 --> 00:53:08.480 I believe it's detopping, plastic hole punching, and runner cutting, I think it is. 00:53:08.719 --> 00:53:10.960 And they got to an RD stage. 00:53:11.119 --> 00:53:17.519 They got grower feedback that the machines were done and they're being sold on the Central Coast through normal dealer channels. 00:53:17.679 --> 00:53:20.800 Not a dollar of venture capital anywhere in the supply chain and RD chain. 00:53:21.039 --> 00:53:21.760 That is so interesting. 00:53:21.920 --> 00:53:22.239 Right? 00:53:22.400 --> 00:53:22.639 Yeah. 00:53:22.880 --> 00:53:32.239 And so that's the model we're looking at for harvest, acknowledging that hole punching and detopping are a little more straightforward and can be done by student engineering teams. 00:53:32.400 --> 00:53:36.639 Again, that harvest process I laid out, that might be the hardest process to solve in agriculture. 00:53:36.800 --> 00:53:36.960 Right. 00:53:37.280 --> 00:53:42.239 Because all the AgTech companies, what they're looking for is like a SaaS business model, right? 00:53:42.400 --> 00:53:50.880 Like we want to stay there forever and you know, get get paid monthly, annually, whatever you you you call it. 00:53:51.039 --> 00:53:53.119 But yeah, that's that's very interesting. 00:53:53.280 --> 00:53:53.519 Yeah, yeah. 00:53:53.840 --> 00:53:54.800 ARR, MRR. 00:53:55.119 --> 00:53:55.440 Exactly. 00:53:55.679 --> 00:54:05.840 And as I always tell startups, I said, look, if your investor's giving you advice, uh-huh, and it's generally to move faster, and the grower is giving you advice, and it's generally slow down. 00:54:06.400 --> 00:54:07.519 Let's figure this out first. 00:54:07.920 --> 00:54:15.519 No sudden movements, you have to listen to the grower and find a way to placate that investor because if you do it the other way around, that grower stops talking to you. 00:54:15.679 --> 00:54:17.119 Your investor has to talk to you. 00:54:17.519 --> 00:54:18.000 Sure. 00:54:18.320 --> 00:54:19.920 That is very true. 00:54:20.719 --> 00:54:22.320 Um that's great. 00:54:22.559 --> 00:54:23.119 Thank you. 00:54:23.280 --> 00:54:26.239 Um we're gonna get into our uh last segment. 00:54:26.400 --> 00:54:30.239 Okay, and uh we call it 60 seconds between the rows. 00:54:30.559 --> 00:54:36.079 Uh I'm gonna ask you rapid rapid fire questions, and I'm expecting rapid fire answers. 00:54:36.320 --> 00:54:36.880 I'll do my best. 00:54:37.039 --> 00:54:39.840 Don't overthink anything because it's funner that way. 00:54:40.159 --> 00:54:41.199 Duly noted. 00:54:42.000 --> 00:54:46.079 Uh all right, so uh 60 seconds between the row, here we go. 00:54:46.239 --> 00:54:46.880 Yes, sir. 00:54:47.039 --> 00:54:50.800 Um we'll start with the first question: labor or capital? 00:54:51.679 --> 00:54:52.639 Which would I take? 00:54:52.800 --> 00:54:53.119 Yes. 00:54:53.280 --> 00:54:56.800 What which one do you think is is more important on a farm? 00:54:57.760 --> 00:54:58.400 Labor. 00:54:58.639 --> 00:54:59.199 Labor. 00:54:59.679 --> 00:55:02.639 Uh field data or gut instinct? 00:55:02.960 --> 00:55:03.840 Field data. 00:55:04.800 --> 00:55:07.760 Best way to earn growers trust. 00:55:09.280 --> 00:55:10.000 Results. 00:55:10.239 --> 00:55:11.840 Oh, that's a good one. 00:55:12.559 --> 00:55:16.320 One ag tech buzzword, you will retire. 00:55:17.760 --> 00:55:18.559 C E A. 00:55:19.039 --> 00:55:19.519 What's that? 00:55:19.840 --> 00:55:20.960 Controlled environment agriculture. 00:55:21.119 --> 00:55:21.920 The vertical farming. 00:55:22.400 --> 00:55:23.360 I'm done with it. 00:55:23.679 --> 00:55:25.119 It wasted a lot of capital. 00:55:25.360 --> 00:55:26.400 Uh yeah. 00:55:27.119 --> 00:55:31.199 Um one area of innovation that's underrated. 00:55:32.079 --> 00:55:33.280 Analytics tools. 00:55:33.760 --> 00:55:34.079 Okay. 00:55:34.400 --> 00:55:37.119 Do you think I'm going out of script? 00:55:37.280 --> 00:55:41.360 Do you think growers understand how to use analytical tools? 00:55:41.840 --> 00:55:42.639 Not yet. 00:55:43.280 --> 00:55:45.679 That that those two are probably probably related related. 00:55:48.719 --> 00:55:54.400 Um what's a harder job, being a grower or an ag tech founder? 00:55:55.840 --> 00:55:58.320 Ag tech founder because of the capital constraints. 00:55:58.719 --> 00:55:59.039 Okay. 00:56:00.159 --> 00:56:03.039 Uh the Redwoods or the Beach? 00:56:03.519 --> 00:56:04.159 The beach. 00:56:04.400 --> 00:56:04.719 Okay. 00:56:06.239 --> 00:56:12.480 AI today, is it already life-changing or still mostly a gimmick? 00:56:12.800 --> 00:56:13.920 For me, life-changing. 00:56:14.000 --> 00:56:17.760 I've been using it two and a half years and it has saved me so many hours. 00:56:18.079 --> 00:56:18.400 Okay. 00:56:18.719 --> 00:56:20.000 So many hours. 00:56:20.400 --> 00:56:23.679 And uh you've made it successfully thus far. 00:56:23.840 --> 00:56:24.639 We have one more question. 00:56:24.880 --> 00:56:25.199 Okay. 00:56:25.440 --> 00:56:27.280 Morning fog or afternoon sun? 00:56:27.679 --> 00:56:28.320 Afternoon sun. 00:56:28.559 --> 00:56:28.719 Okay. 00:56:28.960 --> 00:56:29.280 Every day. 00:56:29.599 --> 00:56:32.320 When you said the beach, I already suspected this is going to be the answer for you. 00:56:32.480 --> 00:56:34.320 Well, and for me, it's a golf course more than a beach. 00:56:34.480 --> 00:56:34.639 Yeah. 00:56:35.599 -->

00:56:36.159 There you go. 00:56:36.320 --> 00:56:37.920 I'll take afternoon sun every time. 00:56:38.079 --> 00:56:40.800 In Monterey, there are a few uh a few good spots. 00:56:41.039 --> 00:56:41.360 100%. 00:56:41.760 --> 00:56:42.000 Yep. 00:56:42.159 --> 00:56:42.960 One of my favorites. 00:56:43.119 --> 00:56:44.480 Yeah, I'm sure. 00:56:44.800 --> 00:56:51.840 Um by the way, I I uh I've played golf like an actual game one time in my life. 00:56:52.079 --> 00:56:53.519 Oh, what was the occasion? 00:56:53.920 --> 00:56:56.960 Uh I was uh at a growers event. 00:56:57.199 --> 00:56:57.920 I was gonna add yep. 00:56:58.480 --> 00:57:02.159 Apple Apple Growers in in uh Yakima Fu Valley. 00:57:02.559 --> 00:57:04.000 Of course, in Ez Han Rahan. 00:57:04.159 --> 00:57:06.960 And and I learned that it's not about the golfing. 00:57:07.199 --> 00:57:07.760 Not at all. 00:57:07.920 --> 00:57:09.519 And it was a lot of fun. 00:57:09.679 --> 00:57:10.079 Awesome. 00:57:10.239 --> 00:57:13.039 And it didn't matter that I I'm not very good. 00:57:13.599 --> 00:57:16.000 It's uh the John Feinstein book title is right. 00:57:16.079 --> 00:57:18.559 It's a good walk spoiled by a few shots. 00:57:19.039 --> 00:57:19.679 It's awesome. 00:57:19.920 --> 00:57:21.199 That's why we have scramble tournaments. 00:57:22.320 --> 00:57:23.840 It was a scramble shots, don't have to count. 00:57:24.079 --> 00:57:27.360 It was a scramble tournament, and boy, did we scramble. 00:57:28.239 --> 00:57:29.519 It was it was a lot of fun. 00:57:30.159 --> 00:57:30.880 It sounds like it. 00:57:31.039 --> 00:57:31.679 Good for you. 00:57:31.840 --> 00:57:32.000 Yeah. 00:57:32.559 --> 00:57:34.320 You know, a lot of guys won't take that chance. 00:57:34.639 --> 00:57:37.119 Doesn't matter if you haven't golfed, it's not about the golf. 00:57:37.199 --> 00:57:38.000 You're so right. 00:57:38.400 --> 00:57:38.960 You're so right. 00:57:39.199 --> 00:57:40.480 And that it's four hours. 00:57:40.719 --> 00:57:43.119 Like I was invited to join a team of growers. 00:57:43.199 --> 00:57:43.360 Okay. 00:57:43.920 --> 00:57:48.800 I was flattered and I wanted to do it, but I also didn't want them to lose because of me. 00:57:48.960 --> 00:57:55.599 And I was like, look, I'm really flattered about the invitation, but uh, I'm I've never played, like I'm gonna be really bad. 00:57:55.760 --> 00:57:58.239 Like I I've been to uh top golf, you know? 00:57:58.400 --> 00:58:00.159 Right, I can't I can hit the ball. 00:58:00.320 --> 00:58:01.039 Isn't that fun? 00:58:01.280 --> 00:58:02.000 Yeah, yeah. 00:58:02.400 --> 00:58:05.199 And they're like, oh no, you don't understand, it doesn't matter. 00:58:05.280 --> 00:58:06.880 Just come, it'll be fun. 00:58:07.039 --> 00:58:08.559 And I came and it was fun. 00:58:08.719 --> 00:58:09.360 That's awesome. 00:58:09.519 --> 00:58:15.599 And I had to wait a couple hours before I could get in my uh rental car and drive back to the airport. 00:58:15.760 --> 00:58:19.440 But some of us get overserved on a golf course. 00:58:19.599 --> 00:58:21.199 It does happen, exactly. 00:58:21.440 --> 00:58:22.239 That's so good. 00:58:22.559 --> 00:58:23.440 I did not expect it. 00:58:23.519 --> 00:58:26.000 I mean, we're out in the sun, it was such a beautiful day. 00:58:26.079 --> 00:58:27.760 I was like, I need to do this more. 00:58:27.920 --> 00:58:31.119 Oh no, a beer on a golf course is like a beer on a plane, it's like a two and a half X. 00:58:31.199 --> 00:58:31.760 Yeah, yeah, yeah. 00:58:32.239 --> 00:58:33.679 It hits you a little harder. 00:58:33.920 --> 00:58:35.440 But hey, don't forget this. 00:58:35.599 --> 00:58:39.679 If you're not a golfer, they should be factoring in your handicap, which will be nice and high. 00:58:39.760 --> 00:58:44.239 So you actually help the good players because your handicap factors in with theirs. 00:58:44.719 --> 00:58:47.599 We uh the group did get to uh second place. 00:58:47.840 --> 00:58:48.719 Oh see? 00:58:49.039 --> 00:58:49.360 Yeah. 00:58:49.679 --> 00:58:56.719 We were far, we were far behind the first place, but we were second, sounds like they might have cheated a little better than you guys. 00:58:57.760 --> 00:58:59.679 Scramble Fred of its are notorious. 00:58:59.920 --> 00:59:04.960 No, they were they were uh they were very like about it. 00:59:05.119 --> 00:59:12.079 You know, they were like really they they hated when they were they started behind us and they got mad when we took a tour. 00:59:12.480 --> 00:59:13.599 Oh did they? 00:59:13.760 --> 00:59:14.000 Yeah, yeah. 00:59:14.159 --> 00:59:20.079 So we at some point we let them pass and they were really playing through in a scramble tournament. 00:59:20.159 --> 00:59:20.480 Wow. 00:59:20.639 --> 00:59:21.039 Yeah, yeah. 00:59:21.280 --> 00:59:22.960 No, it's something most folks don't know. 00:59:23.119 --> 00:59:27.920 Yes, golfers are outdoors a lot, yes, they work hard, but they play hard too, and there's a lot of good golfers. 00:59:28.079 --> 00:59:28.719 Oh, I'm sure. 00:59:28.880 --> 00:59:37.679 So, my one story on there, David Gill, a King City farmer, yeah, he won the Pebble Beach Pro Am over Tiger Woods and his partner playing with a professional. 00:59:38.159 --> 00:59:39.360 What a story that is. 00:59:39.519 --> 00:59:40.159 Yeah. 00:59:40.800 --> 00:59:43.039 Well, Walt, uh, this was a great conversation. 00:59:43.119 --> 00:59:44.639 I really enjoyed it personally. 00:59:44.800 --> 00:59:46.559 Uh I've I've learned a lot. 00:59:46.719 --> 00:59:51.360 Uh and uh I hope everybody else that's listening also learned a lot. 00:59:51.599 --> 00:59:58.079 So uh thanks for uh getting it getting into like what growers want with me. 00:59:58.480 --> 01:00:02.400 Um again, this was a very a fascinating conversation. 01:00:02.559 --> 01:00:05.920 So um I guess that's it for for this episode. 01:00:06.079 --> 01:00:07.440 Thank you again for joining. 01:00:07.519 --> 01:00:11.679 Uh you I'm Itai Kanat, and uh we'll see you next time.