One of the things that worries me the most about 2021-era AI startups is precisely this: early-stage burn rate. Burn rate applies not only to dollar amounts but equity as well. Raises ultimately have to tie to revenue at the very least, so even if the first stage VC went starry-eyed, it doesn't mean the second stage will. I suppose it's just the Great Filter of AI, but here's to the prudent leaders!
I met a YC founder who raised $3.5M, but kept the team to 3 people. He took 2 years to launch— then grew 10x to $2M ARR in a year: Benji built an end-to-end recruiting platform with just 3 people. Last month, he raised a $30M Series C. Since 2022, he grew from 70 to 130 employees. He hit $200K ARR the year he launched— then 10x’d to $2M ARR the year after. I asked Benji why it his end-to-end solution worked when so many “one stop shops for X” fail: 1. There were big unsolved pain points. 2. Existing vendors were small companies. 3. It was possible to build a bundle of best-in-class products. “If you can give people 1 product that works better than 4 products without losing functionality…people will be happy to use that.” It sounds too easy— and it is. Benji was a Director of Engineering, where he spent 90% of his time hiring— he experienced the problem first-hand. He thought about his idea for 18 months before going all-in. He had 100 conversations with potential customers before he started building. He graduated YC, raised $3.5M, but didn’t hire anyone. He kept his runway long. It wasn’t just turning 4 products into 1. Benji understood the pain point, the customers, and the space. He succeeded for the same reason most startups do: He put in the the work— the unsexy, everyday work. The work behind the scenes. The work that doesn’t make headlines. The work you never see. /// Listen to the full episode with Benji on The Product Market Fit Show #startups #venturecapital #founders
