Earth, it is said, Home to over 10,000 AI startups. They are more abundant than cheetahs. Their number is more than Sahar’s red wood. Of course, this figure is a guess – startups come, startups go. But last year, more than 2,000 of them received their first round of funding. As investors pour billions of dollars into artificial intelligence, it’s worth asking: What are all these booming creatures doing?
I decided to get as close as I could to as many recent AI founders as I could. The goal was not to try to pick winners, but to see what it’s like to build AI products on the ground—how AI tools have changed the nature of their work. How terrifying to compete in such a crowded field. It all felt a bit like trying to dance on the rotating surface of the sun. OpenAI provides an update, and a slew of posts on X predict a hundred startup slayings. Brutally!
Is this a revolution that will end with so many engineers? Of course, not all of them can survive. A startup is an experiment and most experiments fail. But run thousands of them into the economic landscape and you might know what’s in store for you in the near future.
It is Navi Anand Founder of a company called Bindwell. When we got on a video call, he half-smiled and spoke vaguely as he told me how he uses custom AI models to produce pesticides. Bindwell’s website once described the models as “insanely fast” and claimed they could predict the results of tests that would take days in “just a few seconds”. Hearing Anand explain how he is bringing AI drug discovery principles to agricultural crops, it’s easy to forget that he’s 19 years old.
Anand grew up in India reading Hacker News with his father, and was building his own large language models by halfway through high school. Before graduating, he, his co-founder (now 18), and two other friends from summer camp published a paper on bioRxiv, about an LLM they built to predict an aspect of protein behavior. This caused scientists to make noise about X. This article was cited in a reputable journal. They decided to try to create a startup, brainstormed and worked on protein-based pesticides. Then, the legend goes, a Wood Sprite (sorry, venture capitalist) called LinkedIn and offered them $750,000 to drop out of high school and college and work full-time at the company. They accepted and started. Teenagers knew next to nothing about agribusiness. It was last December.
Five months later, Anand and his co-founder opened their first biological testing lab in the San Francisco Bay Area, then moved to another lab, where they personally squeezed drops of promising molecules into tiny vials. (In theory, a protein-based compound could more precisely target a grasshopper or aphid, rather than kill off humans, earthworms, bees.) I asked him how he acquired the skills to work in the wet lab. “I hired a friend,” he said happily. The friend coached him the summer before he returned to college in the fall. “Now I can do some biochemical assays,” says Anand. “Not like a wide range of assays, but an initial validation of our models in the wet lab.”
Huh, I thought how many teenagers had built their LLM in a few months, learned pest control biochemistry, used their models to identify potential molecules and were now pipetting in their own labs, it didn’t seem like much of a gimmick. In fact, when I counted all the things they had done, it seemed absolutely absurd. I expected to hear that AI tools would speed up parts of a company’s construction, but I had only a vague understanding of the scale of their impact. So in my next interview, with the founders of a 14-month-old startup called Roundabout Technologies, I got straight to the point: what has changed and how much.
