2/2 Result: **reposix** — a FUSE filesystem + git-remote-helper for issue trackers.
Claims **92.3% token reduction vs MCP** on the same task (~12.9× more usable context).
Only inputs I gave it: https://t.co/huVLjYcfXK
Morning brief: https://t.co/UqzGaIz8iq
Just had a "whoa, coding agents are cool" moment.
Idea: expose REST APIs (GitHub Issues, Confluence, Google Keep…) as file systems. Agents are wildly more efficient on files than tool schemas.
I told Claude Code "you have until 8 AM. Go wild. Night!"
I woke up to this 👇
Reeve is a prototype, but I hope to contribute its core bets to the OpenClaw roadmap:
1. Isolated sessions
2. Wrapper: Orchestrate CLIs (Goose/Claude) > Custom Runtime.
3. Desk: Git-based Memory > Vector DB.
...
Full comparison: https://t.co/StOG0z55lt
🧵3/3
🦄@steipete I💖OpenClaw! Insane!🦞
I built a similar agent (Reeve) in a vacuum—unaware of OpenClaw & "ClawHavoc" security news.
https://t.co/dbQc07TrRl
I optimized for "Session Isolation" vs. Autonomy. My research suggests this architecture fixes the current Drift issues.🧵1/3
I consider myself a YouTube educational video connoisseur, but this one has been the most refreshing one I've seen in a while:
https://t.co/VbzVl12MRS
It reminds me of when I watched minutephysics for the first time.
Greetings to the 45K people on the internet who have seen this video. I suppose being a nerd is also a spectrum, and my goosebumps have revealed where I stand.
https://t.co/0IwypydaTV
It's findings such as these that remind me that Artificial General Intelligence is still a while away.
So much of our intellectual abilities are bootstrapped by evolution, not learned.
https://t.co/Wmnlx7ZW0D
#AI#AGI
Learning by Playing - Solving Sparse Reward Tasks from Scratch: https://t.co/o74adjsA9R
"To learn complex tasks from scratch, an agent has to learn to explore and master a set of basic skills first."