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I was reading Zero to One and came across this section where Peter compares biotech startups with tech startups. It made me pause for a bit because it made so much sense, especially with my agri background.
He puts it out there pretty straight. Biotech startups are tough. You’re working in an environment full of uncertainty, the subject itself, biology is complex and hard to control, the path forward isn’t always clear, regulations can be intense, and the costs? Super high. Then you look at tech startups, particularly software. Things feel simpler, almost. Variables are often clearly defined, you can create controlled environments (like code on a server), costs can be lower, and there’s a huge pool of people ready to jump in, build, and experiment quickly.
As someone from agriculture, this resonated because I often puzzle over why it seems so hard for many agri-startups to really gain traction and sustain themselves, especially those trying to innovate at the core of farming. When I look around, sure, there are many exciting agri-startups working on tools such as building drones, designing better machines, optimizing inputs with software, creating marketplaces. Those are valuable, absolutely.
But fewer seem to break the territory of working directly with the soil, the plants, the intricate ecosystems. Why? Because that space is just unpredictable. It’s not like writing code where you expect a certain output if the logic is right. Here, things grow, they decay, they react to climate shifts, unexpected pests arrive, the soil microbes change the game. There are just so many moving parts.
Maybe the agri-startups that are truly digging into the biology aren’t like tech startups at all. Maybe they’re much more like biotech startups. And maybe that’s why they often struggle to fit the typical fast-paced tech mold. You just can’t copy the speed and iteration cycles of software when your ‘code’ is a living, breathing, responding organism or ecosystem. The very nature of the work is fundamentally different.
I was also reading about using remote sensing to spot plant diseases or nutrient issues from afar. Sounds incredibly exciting, doesn’t it? But the reality isn’t nearly so simple. The data those colored pixels on a map needs serious validation on the ground initially. You have to gather tons of real world data, run experiments, maybe take leaf samples, dig into the soil, and only then, maybe, can you figure out what’s actually stressing that plant whether its a pest or deficiency or something else. It’s not a button-click diagnosis. It requires understanding what nature is doing, what the plant is experiencing, how the whole environment is interacting. It’s biology first, technology second.
Even think about hydroponics. We create these controlled environments, lights, clean pipes and taking soil out of the equation, aiming for predictability. But even there, biology finds ways to surprise you. How the roots behave, precisely how nutrients are taken up, the subtle shifts in microbial life within the system they all bring their own layer of randomness. It’s not as purely plug and play as it might look from the outside.
Maybe that’s the beauty of it, too. Maybe the point isn’t just to move fast. Maybe it’s about building slow, with real intention, learning from the ground up. Because nature operates on its own clock, and it won’t reveal its secrets too fast. Not easy to decode tho.
What about scaling, then? It takes years if it sustains, doesn’t it?
Cheers
PS: Would love to hear what you think!
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