Jesse Zhang

“I actually spent a while building agents for myself to capture all the business context well so it just kind of looks over my shoulder all the time and is constantly compiling context — here are the people that we've hired, here are the deals that we're working on, here are the current challenges that we have.”

“Even if you have a, quote, dumber model, you can get it to higher performance on that specific task. So when we fine-tune smaller, dumber models, it's that they're just not as general purpose, but on the specific task we want them to do, they actually outperform the large, smart, state-of-the-art models. We end up getting all three things. It is better at the task, it is cheaper, and it is faster.”

“Shyam, who's the CTO of Palantir today, had a phrase internally — forward deployed engineers eat pain and excrete product.”

“The reasons are really interesting... having supervisor models track the agents so the agents don't mistake, running multiple agents in parallel so they don't make mistakes... it's like four times the agentic use just to have multiple agents regulating agents.”

“In Zhang's telling, they aren't competitors, and open source models' success isn't coming at the expense of frontier labs. Instead, they're two phases of the same life cycle, with expensive frontier models being used to prove out use cases that can be passed along to cheaper open source alternatives as they mature.”

“Jesse Zhang, founder & CEO, Decagon”