for the last few months i have been working on long running persistent agents. i believe this is the next paradigm shifting product after chatgpt and codex. there are a number of challenges, and i'm currently writing a longer post with some learnings & thoughts on why i believe the next big unlock is solving theory of mind loose thoughts: - the next paradigm-shifting product after chatgpt and codex is the persistent personal/work agent - the blocker to making such agents is that our models can't "read the room" - reading the room sounds soft but it's deep theory of mind - reading the room is the difference between talking to a bot and talking to an embodied identity you can trust to accomplish tasks and communicate with your colleagues - reading the room an understanding of who "your person" is, their desires and motivations, and who your audience is - concretely, it's tracking what i know vs what my user knows vs what the room knows. information asymmetry as a first-class skill - part of this is understanding compartmentalization. enterprises call this tenting and workspace isolation. "if my user is part of this tent, don't divulge information in a broad channel that's not also tented" - if i give a friend my home address, i trust them not to announce it in a room of a thousand people. I do not yet trust a model to exercise that same discretion. - harnesses like openclaw keep trying to solve this at the application layer with permissions, workspace isolation, context injection, and increasingly elaborate agent harnesses. necessary for now, but this likely futile as the final answer. discretion has to live in the model - side effect: this is also part of why model writing reads as slop. good writing is meeting your audience where they are. same missing skill tldr: persistent agents live or die on reading the room, and theory of mind may be one of the last major gaps before agi