Our early testers are showing us how to use it:

- Update Claude's skills/memory based on their workday (in a scheduled task/heartbeat)

- Typing "help me with what I'm working on right now" without having to prompt/describe

- Enriching meeting transcripts with what was actually on screen (and vice versa)

- Forking it into their coaching app so coaches can see what learners did between sessions

- Someone new to tech used Familiar during a trial week at a YC startup, so that AI could coach him every few hours (and got the job)

We've consistently seen AI use Familiar context like a "router" layer. Recently, my agent "saw" that I spent a long time on a document, so it fetched the full doc directly. We've also seen the agent traverse the markdown, then decide to fetch the original image (so cool).

Familiar uses Apple's native OCR, deletes screenshot images after 48 hours, and redacts passwords/credit card numbers/SSNs/API tokens/etc. We'd love contributions on what else to block: https://github.com/familiar-software/familiar/tree/main/src/... or in general ways to improve privacy.

We stand on the shoulders of giants: screenpipe, rewind, dayflow, etc. Since then: 1) Local agents got good at handling massive amounts of messy text files 2) Local agents have their own memory and skills systems

Familiar is our "bitter lesson" version: just hand over context and get out of the way. The right way to do that piece is open source/free/offline.