The crucial moments and decisions leading up to the launch of Notion AI

Key ideas

Zhao recounts how Notion moved from doubting early models to prototyping AI at an offsite, and the product decisions the founders settled along the way to launch.

1. 1

   Keep watching a technology that disappoints

   Zhao says early GPT-3 left the team unconvinced: a demo produced a made-up answer, and he wondered what it could do besides generate low-quality content. Simon kept following the field, DALL-E caught his attention, and Zhao says early access to GPT-4 in fall 2022 changed his view.

2. 2

   Connect new technology to your existing mission

   Zhao writes that GPT-4 made AI look like a route to Notion's mission of making software toolmaking ubiquitous, an idea he traces to Doug Engelbart's 1962 paper. He frames AI as letting people mold a computer to their needs and extend their thinking.

3. 3

   Founders can prototype the unknowns themselves

   Zhao says he and Simon knew AI would matter but not what to build or what interface it needed, so they worked it out with a few product and engineering people in a hotel room during a company offsite. He says the quiet of a company away from Slack helped, and that the two stayed three extra days to finish.

4. 4

   Settle the hard product calls early

   Zhao lists the choices made during prototyping: a new interface for AI writing, equal weight for packaged prompts and free-form requests, a new spacebar entry point despite early pushback, and AI on by default. He says the default came from not wanting to maintain two versions of Notion.

5. 5

   Use a private alpha to learn

   Zhao says Notion launched a private alpha less than a month after the offsite and then spent ten weeks collecting user feedback before general availability in February 2023. He says the waitlist came in far above what the team had hoped for.

In Ivan’s words

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