The End of Organizing

But ultimately, the organizing solutions we’ve built are brittle. We build and abandon new systems all the time, and rarely, if ever, go back to look at old notes. Tags get created and then abandoned. Links rarely get followed. And we feel guilty: there’s a lot of value locked up in what we’ve collected over the years, if we could just figure out how to use it. Paying for a new notes tool is like signing up for a gym membership on January 1. You know you’ll abandon it, but the money you spend soothes your anxiety about not making the most of what you have.

A better way to unlock the value in your old notes is to use intelligence to surface the right note, at the right time, and in the right format for you to use it most effectively. When you have intelligence at your disposal, you don’t need to organize

The problem is, we put things into notes because we don't know what we'll use them for. You write down a quote from a book because you could eventually use it in 1,000 different ways.

You’ll continually reorganize your system, or feel a pull to put a note in many different places, or tag it to make sure it pops up again in different contexts.

This usually doesn’t work so well, and even when you do bump into an old note at the right time, you’re faced with another problem:

Looking at old notes is a bit like looking at stale garbage.

As I wrote in “The Fall of Roam,” when you read an old note you have to load its context back into your head about when you took it and why before you understand what it’s saying, and whether or not it’s relevant to the task at hand.

So you rarely go back to use your old notes.

For an old note to be helpful it needs to be presented to Future You in a way that clicks into what you’re working on instantly—with as little processing as possible.

AI models like GPT-3 can solve organizing in a few key ways.

First, they can automatically tag and link notes together with no manual work required. It doesn’t even require an LLM—there are less advanced, cheaper models that can do this out of the box today.

Second, they can enrich notes as you’re writing them and synthesize them into research reports, eliminating much of the need for tagging and linking in the first place.

Third, they can resurface key information from previous notes into a CoPilot-like experience for note-taking. This makes searching through old notes unnecessary and helps you bring to bear all of the information you’ve ever written down every time you tap a key

Imagine an autocomplete experience—like GitHub CoPilot—that uses your note archive to try to fill in whatever you’re writing.

An experience like this turns your note archive into an intimate thought partner that uses everything you’ve ever written to make you smarter as you type.