Why Notion’s biggest AI breakthrough came from simplifying everything

When initially experimenting with LLMs and agentic AI, software engineers at Notion AI applied advanced code generation, complex schemas, and heavy instructioning. 

Quickly, though, trial and error taught the team that it could get rid of all of that complicated data modeling. Notion’s AI engineering lead Ryan Nystrom and his team pivoted to simple prompts, human-readable representations, minimal abstraction, and familiar markdown formats. The result was dramatically improved model performance. 

Applying this re-wired approach, the AI-native company released V3 of its productivity software in September. Its notable feature: Cutomizable AI agents — which have quickly become Notion’s most successful AI tool to date. Based on usage patterns compared to previous versions, Nystrom calls it a “step function improvement.”

“It's that feeling of when the product is being pulled out of you rather than you trying to push,” Nystrom explains in a VB Beyond the Pilot podcast. “We knew ...