Building AI That Builds Itself

TL;DR: Today we’re releasing a new episode of our podcast AI & I. I go in depth with Yohei Nakajima, a general partner at Untapped Capital and creator of BabyAGI, the first open-source autonomous AI agent. We get into how BabyAGI has evolved, the philosophy that underpins all his creations, and his thoughts on the future of AI tooling. Watch on X or YouTube, or listen on Spotify or Apple Podcasts.

By night, he’s one of the most prolific internet tinkerers in AI. (He also sometimes works on automating his job as a venture capitalistVC.)

One of Yohei’s first viral creations was BabyAGI, an open-source autonomous agent that he built in March 2023. BabyAGI has the ability to generate and address tasks sequentially without human intervention. He’s since released seven iterations, as well as a coding agent called Ditto, a framework for building autonomous agents, and, most recently, BabyAGI 2o, a self-building autonomous agent that follows OpenAI’s unfortunate naming convention. 

I sat down with Yohei to talk about what feeds his drive to build new tools, how BabyAGI developed into a more powerful agent, and his personal philosophy around building in AI— namely, how the tools we build are extensions of ourselves. We also experiment with Ditto live on the show, building a game of Snake, and an app to help me track the names and numbers of people I’ve been meaning to schedule meetings with. And we screenshare a demo of his latest creation, BabyAGI 2o. Here’s a link to the transcript of this episode.  

This is a must-watch for anyone curious about autonomous agents, building cool AI tools on the internet, and the future of AI tooling.

Watch on X or YouTube, or listen on Spotify or Apple Podcasts. 

Go deeper with Yohei

Every paid subscribers can read the top takeaways from this episode, such as:

• How BabyAGI evolved into a more powerful version of itself 
• What Yohei learned about himself through his creations—and how that informs his philosophy around building 
• Yohei’s insights into why the future of AI tooling is personalized and modular 

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