How Notion Built Custom Agents: Rebuilding Four or Five Times to Reach an Agent-Native System of Record
Notion's early attempts to build agents starting in late 2022 failed repeatedly because there was no tool-calling standard, context windows were too short, frontier models were not reliable enough, and too much complexity was exposed to the model.
Before a function-calling standard existed, Notion tried to fine-tune frontier models with a custom tool-calling framework and pursued partnerships with multiple frontier labs, but neither approach produced robust production-ready behavior.
After being rebuilt four or five times, Notion Custom Agents launched as Notion's most successful product launch in terms of free trials and conversions.
Frequently asked questions
What did this team achieve with this AI workflow?
After being rebuilt four or five times, Notion Custom Agents launched as Notion's most successful product launch in terms of free trials and conversions.
What tools did this team use?
Notion, MCP, CLI, Gemini, GPT four, fireworks.
What results were reported?
Launch success (free trials and conversions): most successful launch in terms of free trials and converting people; Agent rebuild iterations before production: fourth or fifth time; Meeting Notes growth impact: one of Notion’s strongest growth loops (source-reported, not independently verified).
What failed first in this deployment?
Before a function-calling standard existed, Notion tried to fine-tune frontier models with a custom tool-calling framework and pursued partnerships with multiple frontier labs, but neither approach produced robust pro…
How is this back office ops AI workflow structured?
Email triage trigger → Web search enrichment → Structured database output → Manager agent routing → Self-inspection feedback loop.