Groundmist post 1: distribution

Came across this via Boris Mann in the runup to Ahoy2025 - the very first time I saw someone developing the #ai4community tools I want for decentralised collective intelligence: "Groundmist echoes the design of AT Protocol... but applies these ideas and select elements of the protocol to local-first software and data... It uses Automerge, AT Protocol's Identity and Lexicon systems, and a personal sync server."

It allows:

• users to edit public and private data seamlessly: "atproto applications can use local-first AppViews for managing private data before it gets published to the protocol", because there's ...
• 1-click publishing for local-first data to your PDS, where it "can be displayed and viewed flexibly according to user or viewer preference using atproto AppViews"

This note summarises the first in the author's series of blog posts - Distribution: " Exploring the AT Protocol as a distribution layer for local-first software", which introduces both the local-first software movement and ATproto, which may "have drastically different goals, they both offer us better ways of interacting with our data, one in the context of data that's private or shared among small groups and the other in the context of public data... many types of data have a lifecycle which begins as private but moves to public... [so] I wanted 1-click publishing pipeline to send local-first content directly to my PDS" to combine the benefits of both.

So she "built a personal content curation app called Groundmist Library... to keep an archive of creative work you've read, watched, and listened to that was worthy of attention... build a single unified historical view of the inputs that you found valuable ... share a chosen subset publicly while keeping the rest private... My data should be private by default, but publishing a specific item of content should be frictionless" - exactly what I want to create by adding a private section to myhub.

Also she wants "To easily run local models over the history looking for trends, insights, and recommendations" - why I integrated with ChatGPT, although I too would like to incorporate local models into the OS Hub toolbox. Otoh, she's not interested in note-taking.

When it comes to publishing, "I want a low effort, low friction way to publish my data to a unified data store from which I can display it flexibly in a variety of ways... [ATproto's] PDSs provides a place to unify public data, and their Lexicon schema system provides a structured way for software from different organizations to understand each others' data, acting as a legibility layer that enables interoperation... easy to create new views over any combination of these public data sets."

This of course "unlocks access to the distribution of the [ATmosphere]... such as Bluesky with its 30 million users. Published data can be cross-posted. It can be easily discovered and shared, and it can benefit from existing network connections"