Mr Vibe Coder

the anatomy of the perfect 𝗦𝗢𝗨𝗟.𝗺𝗱 file for AI agents. 𝗦𝗢𝗨𝗟.𝗺𝗱 is the one file you write yourself for an AI agent. it sits at the top of the system prompt, before memory, before skills, before tools. it defines who the agent is when it shows up. an hour spent on it changes every conversation that follows. most other layers update themselves. this one is yours. i just broke down what a 𝗦𝗢𝗨𝗟.𝗺𝗱 file that actually works looks like. here are the 8 sections that matter: → identity (a one-line statement of who, not what) → core truths (imperative principles, each with a one-line unpacking) → worldview (opinionated takes by domain, sharp enough to predict) → voice (concrete rules for how the agent talks, not adjectives) → expertise (primary domain, fluent tools, where it defers) → boundaries (explicit "won't" lines, no soft language) → memory policy (what persists, what stays private) → pet peeves (phrases and tones the agent never produces) generally people write "be helpful and professional" and call it done. that changes nothing. every model already tries to be helpful and professional by default. the agents that compound have 𝗦𝗢𝗨𝗟.𝗺𝗱 files with real opinions, hard limits, and a voice you can predict before you read the response. a strong 𝗦𝗢𝗨𝗟.𝗺𝗱 is 30 to 80 lines. specificity beats coverage. bookmark this. the first agent you build will need it. i wrote a full masterclass on Hermes Agent that walks through the 𝗦𝗢𝗨𝗟.𝗺𝗱 layer, the three-tier memory system, the self-evolving skills loop, and how to run three specialized agents on your machine 24/7. the article is quoted below.

I've started experimenting with gBrain + Hermes Agent it's a shared memory layer that sits underneath my Hermes Agent company. every specialist reads from the same brain before they do anything the architecture I'm currently testing: > inputs flow in: my ideas, strategy context, research, social signals, performance data > gBrain holds it all in typed folders: people/, companies/, concepts/, ideas/, media/, newsletter/, projects/, operations/ > the orchestrator (my main hermes agent) reads gBrain before every task and writes durable context back > specialists (research, socials, outbound, newsletter, engineering) get read-first access so they wake up with full context the flow goes like this: > 1. research agent → gBrain: enriches the brain with new findings > 2. gBrain → read-first context before any work > 3. orchestrator → gBrain: captures durable decisions > 4. tools → orchestrator uses fresh information from X, web, news > 5. orchestrator → I bring synthesized decision support so don´t think about gBrain as an agent, it's the shared memory layer that lets a company of agents act like a team, with cross reference and a centralized brain

BREAKING: Video shows UK police taking down the terrorist who stabbed two Jews in Golders Green.

Introducing GPT-5.5 A new class of intelligence for real work and powering agents, built to understand complex goals, use tools, check its work, and carry more tasks through to completion. It marks a new way of getting computer work done. Now available in ChatGPT and Codex.

society needs to grapple with the reality of a mythos-level model being open source in <12 months. i’m not sure we are prepared.

New in Cowork: scheduled tasks. Claude can now complete recurring tasks at specific times automatically: a morning brief, weekly spreadsheet updates, Friday team presentations.