You’re Not Thinking Big Enough: Rebuilding Food Systems with AI Agents — Cody Menefee, Firecrawl
AAI Engineer
Computing/SoftwareSmall Business/StartupsEnvironment
Transcript
00:00:00All right, hello everybody. My name is Cody. I put this picture up here because this jacket so far
00:00:20has not actually landed as well as I thought it would. No one gets the joke. So this was to really
00:00:26put it in front of your face. I don't just enjoy wearing heavily branded Letterman
00:00:30jackets. We intentionally tried to play into the bit a little bit. So my name is
00:00:35Cody. I'm on the growth team at Firecrawl and today I'm here to tell you
00:00:40you're not thinking big enough. But before I actually get into that I have to
00:00:45address a bit of an elephant in the room which is Theo stole my talk. Theo put out
00:00:50a video about a month ago called "You Need to Think Bigger" but I would like to say
00:00:54I submitted the name for this talk a month before Theo put his video out. I
00:00:58didn't steal his talk. He stole my talk. So today we're actually going to talk about
00:01:04farming and yes I actually mean farming. More specifically I mean livestock
00:01:10farming and even more specifically I mean automating pasture rotation for grass-fed
00:01:14livestock systems. I have a feeling most of you did not expect to learn about cows and
00:01:20grass and farming today but I'm here so you're going to. A little bit of
00:01:25background on who I am and why maybe you should listen to me. The short version is
00:01:30I actually have no credentials that qualify me for this talk but nonetheless I'm
00:01:34going to do my best to give it. I grew up in Kentucky. I have a background in
00:01:38blue-collar work. I was a bartender, a mechanic, a server, a whole bunch of things. Never actually a farmer though.
00:01:46And then I sort of found my way into engineering, software development, etc.
00:01:51I actually don't really like taking the title of software engineer. I'm pretty
00:01:56adverse to that. Feels like stolen valor because I am the vibe coder most of you
00:01:59all are scared of. I use AI agents all day long. I don't have any syntax memorized. I am
00:02:05not proficient in any particular coding language but I will crank out some stuff
00:02:10on a weekend. But today I actually work at Firecrawl where we're building context for AI agents. We have a
00:02:16series of web data APIs to give your agents access to the web. Again, I said I'm on the growth team,
00:02:21but today we're actually going to get into some more farming stuff. But first, a bit of credential
00:02:26I do have is this is a real picture of me hauling turkeys on top of my Tesla, and I do still have a
00:02:33crack in that glass ceiling because of it. This was in Nashville where I live in the middle of a
00:02:38residential neighborhood where you are not allowed to raise turkeys. But I raised 10 turkeys in my
00:02:43backyard because I wanted to know what it was like to actually raise livestock myself that I would eat.
00:02:49It's a very mentally difficult process, if I'm being totally honest. But this was me loading them up
00:02:56onto the roof of my Tesla, and then I drove for three hours with them to the processor, had to stop at a
00:03:01supercharger on the way, and lots of people were taking pictures. And what I can tell you is if your
00:03:07range is sufficiently decreased when you have a giant windbreak full of turkeys on top of the roof.
00:03:13So that was quite the anxious drive, I can tell you. I also almost left engineering to be a farmer. I
00:03:21really wanted to raise chickens. This is a real product image that I came up with. I wanted to wrap
00:03:26turkeys in white wrapping and literally just slap the word "e-e" on top of it. I thought it was provocative.
00:03:31I thought I would get you to buy chickens. But I realized it's actually really hard to make any money
00:03:36farming. Surprise, surprise. And I have a wife. I have two kids. It didn't feel right to ask them to
00:03:46give up the lives they had so that I could go cosplay as a farmer and raise chickens. So
00:03:51I decided to pivot and see if there were ways that we could scale farming itself and the types of
00:03:57systems that I'm interested in when it comes to livestock agriculture. So three things I want to
00:04:02get accomplished in this talk is one, convince you all to pursue bigger ideas. I think a lot of these
00:04:07talks, a lot of these conferences, a lot of us individually spend a lot of time talking about
00:04:12building software for people who build software, for people who build software, so on and so forth. And I
00:04:17really am just here to challenge you that there are other problems to solve than just another MCP
00:04:22for another SaaS solution at another company. But also I'm just really trying to take advantage of
00:04:27a captive audience. If you corner me anywhere at any time, there's a good chance I will talk to you
00:04:32about farming. So here I am. And hopefully I can convince you to come work at Firecrawl.
00:04:39So first things first, I believe livestock belongs on pasture. I think animals should live on grass.
00:04:45I think it's better for the animal, the consumer, the farmer, the ecosystem. I can give you a whole
00:04:48TED talk on each of those if I need to. You can find me later if you need me to tell you why it's
00:04:53better for animals to be on grass. But I don't have enough time to get into all of that. Take my word
00:04:57for it. Let's start there. The assumption is animals should be on grass. This is the goal I want to hit.
00:05:05I am not actually anti-containment farming. I think there's a reason we needed to do that. But 97% of cows are
00:05:11still currently finished on feedlots. 3% are raised on pasture. My opinion here, more animals could be on
00:05:17grass. I want to try to figure out how we get more animals on grass. The question is, why aren't they on
00:05:22grass? And that is, labor is the bottleneck. It is a pain in the ass to actually raise animals on grass.
00:05:28Pasture done right actually means moving animals constantly. And that takes a lot of work. If you think
00:05:35about grass-fed beef, you might think of I have 100 cows, 100 acres. I put 100 cows on 100 acres. They eat grass.
00:05:41I got beef at the end of the year. That's not quite how it works. You will very rapidly decrease the
00:05:48quality of your pasture if you just let cows graze where they want because they'll graze their favorite
00:05:51things, ignore things that they shouldn't, trample areas consistently, so on and so forth. So the solution to that is
00:05:58rotational grazing. What this means is you break up your pasture into individual paddocks where the animals
00:06:04have enough food for one day and then you move them every single day. This allows certain areas to rest
00:06:10and other areas to be grazed and over time will increase the efficacy of your pasture. But this takes
00:06:17a whole, whole, whole lot of work. This means you have to move fences, animals, water, and keep track of it
00:06:25every single day in order to appropriately move the animals as often as they need to. There are some
00:06:33solutions actually trying to work on this problem. You may have seen a company called Halter in the news
00:06:38recently. Peter Thiel invested at a two billion dollar valuation. No Fence is another company. What these
00:06:44companies do is provide collars for the animals connected to GPS satellites that allow you to draw
00:06:50virtual boundaries where you can move the animals remotely. I think this is a great step in the
00:06:56direction of trying to expand labor but this has a problem which is you have to know where to move the
00:07:05animals. This is not a science to actually be honest with you. You can't just move them in a straight line
00:07:10across the pasture routinely every single day to the same part of land. The reason is is grass doesn't
00:07:17grow the same every single day. There are drought conditions, rainfall, how much impact a particular
00:07:23section of the paddock has had and the way that this is sold today is actually farmers going out on
00:07:28pasture putting eyeballs on the grass and making intuitive decisions about where the next best move should
00:07:33be. So the question is how do we replace the farmers eyes on pasture so that they can remotely make
00:07:41educated decisions on where to move their virtual fences? There's a bit more that actually goes into
00:07:48this as well and that is you can't just you have to also know how tall the grass is. Grass has a growing
00:07:54cycle. If you grow it way too short it takes a really long time to come back. If you let it go too long
00:07:59it becomes old and bitter and the animals don't like it. There's this juvenile sweet spot that you
00:08:04want to keep the grass in. You want to cut it before it gets too tall but then you also don't want to
00:08:08cut it too short. You need to keep the animals moving and then constantly coming back to the same pasture
00:08:13so that your grass stays at the most optimal growing age and constantly has the most productivity possible.
00:08:21So a couple of ways that we can do this. These are things these are my solutions. This is something
00:08:26I've actually been working on thinking about how we can do this. A couple of options that I have are
00:08:31drone orthomosaic maps. If we could find a way to automate drone flights we could go fly them around
00:08:36our pasture take a whole bunch of pictures get some very high fidelity high resolution images of the
00:08:41grass that farmers could analyze. The problem with this is there's a lot of skilled upgrade you need to do with
00:08:48the farmers to teach them how to fly drones. A lot of regulatory issues with keeping the drones in
00:08:52sight and ideally this would be autonomous and there currently isn't a jurisdiction in the world that
00:08:56has approved autonomous drones for these types of applications. So this is a really big bottleneck.
00:09:01I think it has pretty high fidelity in the quality of imagery but is going to be a hard problem to
00:09:05solve in terms of actually getting all those hurdles accomplished. Satellites is my most favorite option
00:09:11today. There's a really cool company called Planet out there taking pictures of the entire globe every single day
00:09:17with a one by one meter resolution but there's still those satellites really high up in the sky
00:09:25and it's hard to tell some of the things you need to tell to actually make those educated decisions.
00:09:31The middle photo here is actually from a friend of mine out in Missouri working as a research grad
00:09:35assistant at the Missouri Lincoln University and this idea is just putting a trail cam next to a tree
00:09:42and some measuring apparatus that that camera can look at and just figuring out how tall is the grass in
00:09:48relation to that particular object just so that we have some sort of reference point that we can use to
00:09:54see how well the grass is growing back. If we can solve this problem along with the
00:09:59the collar situation I think there's a world here where we can drop an LLM in the middle of this loop
00:10:07and start to work on autonomous grazing operations and so what this would mean is an LLM essentially
00:10:14making the next best decision on where the animal should be any given day but this is a multivariate
00:10:19analysis. This requires the LLM to have several data inputs including where the animals are in GPS location,
00:10:25where they were yesterday, where they might go tomorrow, what the drought condition is in the area,
00:10:30how tall the grass is across the entire farm and actually it has to make this decision not just
00:10:36on a day-to-day basis but in varying degrees of relation. So where's the best next place for a
00:10:43particular cow to be but where's the best place for the herd to be in relationship to the pasture itself,
00:10:49in relationship to the farm as a whole and then more broadly the ecosystem at large. There's
00:10:55all of these components feed back into each other and if you can optimize this entire picture you
00:11:00have a more productive farm where you can actually have more animals on fewer acres which is how we
00:11:05end up actually scaling to compete with the feedlot style where you can actually have more cows on fewer grass.
00:11:12How do we solve this problem? There's a couple of components. There's three main blockers that I think
00:11:17need to exist in order for us to actually create this system. The first one is building a knowledge
00:11:21base and this is primarily what I'm working on at Firecrawl and then an open source project I have
00:11:26called OpenPasture. The idea here is a lot of the knowledge on when to move, why to move, how to move,
00:11:32the benefits of moving, etc. is all locked up in primarily YouTube videos. There's a bunch of really
00:11:38cool farmers out there. I can give you a whole bunch of channels that you can go down rabbit holes on
00:11:42of just good old guys out in Missouri, Tennessee, Kentucky trying to move their animals every single
00:11:48day telling you what they're learning, telling you what species are best for this, what lagoons are you
00:11:54want to aim for in the biodiversity and your pasture. There's a whole bunch of things that go into this
00:11:59and we need to build that knowledge base. Firecrawl is a toolkit that I use to actually
00:12:03collect this data. I'm going out scraping those YouTube videos, scraping research papers out to
00:12:08archive, building this knowledge base up and OpenPasture is the actual repository I put this
00:12:13information in to make it available to any farmer I think that might be able to use it.
00:12:18The next thing to solve is the actual visualization layer. There's a lot of components we need to know
00:12:24about the grass that the farmer is primarily getting out of the intuition from looking at the
00:12:28pasture. The two main things worth figuring out about the pasture both where the animals are where they
00:12:34should go and where you want them to be is what is the biomass, how much foliage actually is available
00:12:40for them to consume, and then long term what is the biodiversity of that particular pasture. If they
00:12:46overgraze sections too heavily they'll start to over index on different types of cool season, warm season,
00:12:52grasses, lagoons, etc. and ideally you want a really rounded really diverse pasture over time to make sure that
00:12:58the cattle are getting the nutrients they need so you don't have to supplement with things like hay, copper,
00:13:03aluminum, etc. Ideally they get all of the macronutrients and micronutrients from the grass itself which
00:13:10becomes an entirely ideally hands-off system. And then the third one is those geofence companies, so
00:13:19NoFence, Halter, while I appreciate the technology they're trying to push forward, I have a pretty strong
00:13:24disagreement with them which is in order to use their software they require you buy their collars and you
00:13:29can't plug your own software into their collars. From a business standpoint I get why this is, from an
00:13:34industry standpoint I think it's really a pain in the ass. I would like to innovate on the software layer,
00:13:39I would like to push GPS locations to these collars that my LLM can predict. I don't want to have to
00:13:45rely on their software to do this because I don't think it's as good or I think I can make it better,
00:13:49I'm being totally honest with you. So a bit of the purpose of this talk is actually a call to action
00:13:55for you all in the audience. I need someone to make me a caller. I need it to be open, the APIs need to
00:14:02be open. Ideally it's an off-the-shelf solution, some component parts that we can slap together.
00:14:08Farmers are pretty scrappy and like to heal their own things. There's a lot of analogity towards
00:14:13John Deere and this sort of like right to repair. So my ask to anyone maybe looking at this problem
00:14:19is design me a caller where the patent can be open and the APIs are open so that we can compete on
00:14:23software and optimize this solution. The next thing I'd like to maybe tease you about is this actually goes
00:14:31beyond just ruminants. So ruminants is a type of animal, cows, sheep, goats, those are all ruminant
00:14:36animals. They chew grass, they digest it in their ruminant, which is an organ further called ruminants.
00:14:43But there's actually an additional benefit we get where we can stack species on these pasture rotations.
00:14:48This is a company called Pasture Bird. They were a big catalyst for me to really get and obsessed with
00:14:53this idea. What they did is took your normal chicken house, put it up on big wheels, and automated the
00:14:59movement so it creeps its width every 24 hours across pasture. The reason you can do it this
00:15:05scientifically with chickens is because they don't actually get most of their nutrients from the
00:15:08grass. You have to supplement them with grain feed because chickens are omnivores, not quite just
00:15:13herbivores. So you can just inch this coop across the grass, giving them a fertile land to grow on. The
00:15:22nitrogen from their droppings actually help as a manure or as a fertilizer for the grass itself. And
00:15:30there's an added benefit here when you stack the ruminants with the chickens. If you run your ruminants
00:15:34first, they sort of cut off the top of the grass, and the chickens come behind them and peck out the
00:15:39parasites from their droppings. And it reduces the parasite load overall across your farm, which reduces the
00:15:45medication expense you have to actually pay to keep your animals healthy. And over term you have a more
00:15:50robust seed stock or breeding stock so that you can have stronger animals over time that require fewer
00:15:56interventions and can be left alone to just eat grass and turn into meat eventually. So the three things
00:16:04I really hope you all take away from this talk is one, I think we need to find big real world physical
00:16:09problems that we can solve that require multivariate analysis and not quite yes or no decisions. There
00:16:17are lots of problems out there that don't actually have deterministic solutions. I hear a lot of
00:16:22engineers talk about how we turn LLMs into deterministic processes. And my contention is actually
00:16:27there's a lot of problems that you can't solve with deterministic algorithms. This is one of them.
00:16:33It's a multivariate analysis. There isn't a next best paddock to move to. There's just your best
00:16:38guess on where you think they should go. And I think if we can take systems like that, these
00:16:44multi-data input systems, and drop an LLM in the center to actually reason over the data and at least
00:16:49make a suggestion that the human can confirm or deny, we can really start to scale systems like this that
00:16:55are very much restricted by the farmer's ability to scale their own labor, their own decision-making power,
00:17:02and really give them the tools that they need to grow their operations to hopefully, I think, all animals could be
00:17:08raised on grass if we solve these problems. And then the last one is, is maybe you can come help me solve
00:17:13some of these problems. The number one problem is actually just giving the agents the context they need,
00:17:19gathering the data, packaging that data, and then presenting it in a way that the LLM can reason over.
00:17:24And that's what we do over at Firecrawl. So you're not thinking big enough. Firecrawl is where we're
00:17:29building the context layer for AI, and I hope you can come build it with us. We're hiring.
00:17:34So here's all the job postings we currently have. Go to our website. Maybe find one that works out for
00:17:39you. Reach out to me. We'd love to have more people trying to figure out how we get data off the web to
00:17:44solve some more of these complex problems and present that data as context to these AI agents.
00:17:50And perhaps we can make the world a better place. My name's Cody. Open Pastures is my open source
00:17:57project. Firecrawl is where I do my day-to-day life. And these are my socials. I'll hang around
00:18:02for a little bit. I'd love to chat more about animals, cows, birds, all you like. Thank you very much for coming.
Community Posts
No posts yet. Be the first to write about this video!
Write about this video