Evidence receipt / uncertainty
Published · transcript-backedShawn Wang: uncertainty
1 Jun 2023 Latent Space Building the AI × UX Scenius — with Linus Lee of Notion AI
“I don't know what to do with this. So I think a lot of people judge Notion AI based on what they originally saw, which is write me a blog post or do a summary or do action items.”
Source trail
Everything needed to verify it.
- Speaker
- Shawn Wang
- Attribution
- Verified speaker
- Claim type
- uncertainty
- Recorded
- 1 Jun 2023
- Publisher
- Latent Space
Transcript context
…Again, like it goes way back to the early, the thing we touched on early in the conversation around like, if you have too much generality, there's not enough, there are not enough guardrails to obviously point to use cases. Blank piece of paper. I don't know what to do with this. So I think a lot of people judge Notion AI based on what they originally saw, which is write me a blog post or do a summary or do action items. Which, fun fact, for latent space, my very, very first Hacker News hit was reverse engineering Notion AI. I actually don't know if I got it exactly right. I think I got the easy ones right. And then apparently I got the action items one really wrong. So there's some art into doing that. But also you've since launched a bunch of other products and maybe you've already hinted at AI Autofill. Maybe we can just talk a little bit about what does the scope or suite of Notion AI products have been so far and what you're launching this week? Yeah. So we have, I think, three main facets of Notion AI and Notion at the moment. We have sort of the first thing that ever launched with Notion AI, which I think that helps you write. It's, going back to earlier in the conversation, it's kind of a writing, kind of a content generation tool. If you have a document and you want to generate a summary, it helps you generate a summary, pull out action items, you can draft a blog post, you can help it improve, it's helped to improve your writings, it can help fix grammar and spelling mistakes. But under the hood, it's a fairly lightweight, a thick layer of prompts. But otherwise, it's a pretty straightforward use case of language models, right? And so there's that, a tool that helps you write documents. There's a thing called an AI block, which is a slightly more constrained version of that where one common way that we use it inside Notion is we take all of our meeting notes inside Notion. And frequently when you have a meeting and you want other people to be able to go back to it and reference it, it's nice to have a summary of that meeting. So all of our meeting notes templates, at least on the AI team, have an AI block at the top that automatically summarizes the contents of that page. And so whenever we're done with a meeting, we just press a button and it'll re-summarize that, including things like what are the core action items for every person in the meeting. And so that block, as I said before, is nice because it's a constrained space for the AI to work in, and we don't have to prompt it every single time. And then the newest member of this AI collection of features is AI autofill, which brings Notion AI to databases. So if you have a whole database of user interviews and you want to pull out what are the companies, core pain points, what are their core features, maybe what are their competitor products they use, you can just make columns. And in the same way that you write Excel formulas, you can write a little AI formula, basically, where the AI will look at the contents of the page and pull out each of these key pieces of information. The slightly new thing that autofill introduces is this idea of a more automated background…
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