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Meet Hermes Agent, the open source agent that grows with you. Hermes Agent remembers what it learns and gets more capable over time, with a multi-level memory system and persistent dedicated machine access.

3,910,130 Aufrufe • vor 6 Monaten •via X (Twitter)

46 Kommentare

Profilbild von Nous Research
Nous Researchvor 6 Monaten

Hermes Agent runs in your CLI and through messaging platforms like Telegram, WhatsApp, Slack, and Discord - picking up and transferring sessions wherever you go. It has advanced agentic capabilities: command over subagents, programmatic tool calling, advanced filesystem/terminal control, agent-managed skills, browser use, scheduled tasks, and more.

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Nous Researchvor 6 Monaten

Powered by @OpenRouter and Nous Portal subscriptions. The first 750 new sign-ups at get a free month with coupon code HERMESAGENT.

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Nous Researchvor 6 Monaten

Hermes Agent is open source and built in Python, so it's easy for developers to extend. It sits between a Claude Code style CLI and an OpenClaw style messaging platform agent, with a wide range of skills and extensibility. It also powers our agentic RL pipeline, expanding Atropos so you can run RL with Hermes Agent primitives, and it supports mass-scale data generation out of the box. Check out the GitHub repo:

Profilbild von Teknium 🪽
Teknium 🪽vor 6 Monaten

Hope everyone enjoys! Join our discord to discuss:

Profilbild von 𒐪
𒐪vor 6 Monaten

goodbye opencode, i met someone new

Profilbild von Nous Research
Nous Researchvor 6 Monaten

😏

Profilbild von PHD in Being Correct
PHD in Being Correctvor 6 Monaten

Okay but who tf is on this beat?!? Production is crazy

Profilbild von Nous Research
Nous Researchvor 6 Monaten

It’s a Nous original

Profilbild von SplitDaWig 🪴
SplitDaWig 🪴vor 6 Monaten

@GrayCarrots Drop the whole track

Profilbild von Nous Research
Nous Researchvor 6 Monaten

@GrayCarrots Maybe we will!

Profilbild von Nous Research
Nous Researchvor 6 Monaten

@GrayCarrots

Profilbild von dmayhem93
dmayhem93vor 6 Monaten

going to be some really exciting things coming out of our rl pipelines with this

Profilbild von nightwing
nightwingvor 6 Monaten

the nightwing research machine has been loving this one, and you all will too

Profilbild von Teng Yan
Teng Yanvor 6 Monaten

very nice - congrats. better than openclaw?

Profilbild von Nous Research
Nous Researchvor 6 Monaten

We think so

Profilbild von Parzival - ∞/89
Parzival - ∞/89vor 6 Monaten

Open sourced?

Profilbild von Nous Research
Nous Researchvor 6 Monaten

Always

Profilbild von SIGKITTEN
SIGKITTENvor 6 Monaten

wait what did u guys cook here

Profilbild von Gabriel
Gabrielvor 6 Monaten

incredible

Profilbild von ex Tenebris Lucet
ex Tenebris Lucetvor 6 Monaten

@grok since this is open source, can you go investigate and figure out how the multi level memory system works?

Profilbild von ejae dev
ejae devvor 6 Monaten

the multi-level memory is the most underrated part of this. everyone's building agents that can code, almost nobody is solving the memory degradation problem. agents that accumulate wrong memories over time get confidently worse, not better.

Profilbild von am.will
am.willvor 6 Monaten

Thanks for the free month!

Profilbild von 🌸 ellie 🌸
🌸 ellie 🌸vor 6 Monaten

@jicapal @robotson hits keep coming. monitoring the situation. mac mini thesis intensifies

Profilbild von Denis Skripnik (blind) (✱,✱)
Denis Skripnik (blind) (✱,✱)vor 6 Monaten

Well done! Congratulations on such an important launch. Add an easy migration tool from OpenClaw—then it will be easier for those who want to switch to your agent.

Profilbild von BOOTOSHI 👑
BOOTOSHI 👑vor 6 Monaten

GORGEOUS TRAILER

Profilbild von jimmy
jimmyvor 6 Monaten

👀🫵

Profilbild von Brian Cheong
Brian Cheongvor 6 Monaten

Multi-level memory for persistent context is the right direction. The gap between 'I told it once' and 'it actually remembers' is where most agent workflows fall apart.

Profilbild von λux
λuxvor 6 Monaten

banger release!! loved parallelism + multi-level memory system ⚡️

Profilbild von subho ghosh
subho ghoshvor 6 Monaten

Cooked

Profilbild von jonny
jonnyvor 6 Monaten

been using hermes agent for a few weeks. It can cook fr 😎

Profilbild von Jobless ☉
Jobless ☉vor 6 Monaten

this is exactly what I needed!

Profilbild von scoopy trooples
scoopy trooplesvor 6 Monaten

let people look at the site before having to put in personal information

Profilbild von Anglo Sigma
Anglo Sigmavor 6 Monaten

I need music like this on a playlist. What genre called?

Profilbild von Nous Research
Nous Researchvor 6 Monaten

We haven't named it yet!

Profilbild von Anglo Sigma
Anglo Sigmavor 6 Monaten

Similar to Stardew Valley soundtrack but better. More bass. More cyber.

Profilbild von Varun
Varunvor 6 Monaten

very original work guys. good job.

Profilbild von Nous Research
Nous Researchvor 6 Monaten

Bro invented green terminal output

Profilbild von Varun
Varunvor 6 Monaten

it felt like deja nous

Profilbild von Agent 23: The Patriot
Agent 23: The Patriotvor 6 Monaten

Would 100% make this my primary agent if it played this on startup every morning

Profilbild von homanp
homanpvor 6 Monaten

the agent memory problem is mostly a curation problem. what you choose NOT to remember matters as much as what you do.

Profilbild von sxcpc
sxcpcvor 6 Monaten

10/10 on the aesthetics

Profilbild von Thomas Ip
Thomas Ipvor 6 Monaten

Nous on X news 👀

Profilbild von Allora
Alloravor 6 Monaten

I love how fast AI is moving currently.

Profilbild von gr33nsilky
gr33nsilkyvor 6 Monaten

cool music

Profilbild von Tom Lynch
Tom Lynchvor 6 Monaten

Nice!!

Profilbild von Dushyant
Dushyantvor 6 Monaten

Sweet! Have to give this a go.. openclaw with codex is really dumb and openclaw with Claude.. not feasible

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HERMES AGENT LEARNS FROM ITS OWN MISTAKES. UPDATES ITS MEMORY. CREATES ITS OWN SKILLS. NO CLOUD. EVERYTHING STORED LOCALLY. THIS IS HOW THE SELF-IMPROVING LOOP WORKS. most agents start from zero every session. Hermes carries forward what it learned. THREE MEMORY SYSTEMS: 1. PROCEDURAL MEMORY (how to act) stored in ~/.hermes/skills/ as SKILL.md files. when the agent repeats a complex workflow, it saves the procedure as a reusable skill. next time the same task comes up, it follows the skill instead of figuring it out again. you can also create skills explicitly: "create a skill called video-prep that captures how I format my video scripts. spoken english, define jargon inline, no em-dashes, close with a catchphrase." the agent writes the SKILL.md. available as a slash command from that moment. Hermes ships with 90+ skills. the number grows the longer you use it. 2. SEMANTIC MEMORY (durable facts about you) stored in ~/.hermes/memory/memory.md the agent scans conversations for facts worth remembering. preferences, habits, corrections, project details. real example from the video: agent tried to scrape a YouTube channel. URL was wrong. it failed. it updated memory.md with the correct URL pattern so it never makes the same mistake again. you can also save explicitly: "save to memory that my favorite testing framework is pytest" the agent updates memory.md immediately. this file loads into context on every session. the agent knows you better every week. 3. EPISODIC MEMORY (chat history) stored in ~/.hermes/state.db (local SQLite). every conversation. every tool call. every result. searchable with FTS5 full-text search. "search our past sessions. what was the first thing I ever said to you?" the agent queries state.db and finds it. over time, auxiliary models consolidate episodic memory into semantic memory. distilling recurring patterns into durable facts. THE SELF-IMPROVING LOOP: every agent run follows this cycle: → you send a prompt → working memory loads: SOUL.md + memory.md + relevant skills + chat history → agent calls tools (terminal, browser, delegate_task) → agent completes the task, replies to you → AFTER the reply: agent checks "did I learn something worth saving?" → if yes: updates memory.md or creates a new skill → next session starts smarter than the last this happens automatically. you don't ask the agent to learn. it decides what to remember on its own. WHAT MAKES THIS DIFFERENT FROM CLAUDE CODE: Claude Code has memory too. but Hermes stores everything locally. no cloud. your data never leaves your machine. Claude Code doesn't auto-create skills from experience. Hermes turns repeated workflows into reusable procedures. Claude Code memory is instruction-based. Hermes memory is conversational and self-updating. over months of usage, Hermes builds a knowledge base of your preferences, your projects, your mistakes, and the procedures that work for your specific workflow. the agent that remembers your birthday also remembers why your last deploy failed. NO EMBEDDINGS. PLAIN TEXT. Hermes does not use embeddings or RAG for memory. skill and memory search runs on plain text keyword matching. simpler. faster. no vector database to maintain. works entirely offline on your local machine. DELEGATE TO CLAUDE CODE: Hermes can spawn a sub-agent that runs Claude Code in headless mode: "spawn a sub-agent using Claude CLI to build a Python script that fetches the top 5 Hacker News stories to markdown." Hermes delegates. Claude Code writes the code. result returns to Hermes. Hermes runs the script and delivers the output. use Hermes for orchestration. use Claude Code for heavy coding. both tools. not competitors. WHAT HERMES DOES NOT HAVE: no built-in eval or LMOps system. no LangSmith, no LangFuse integration out of the box. trajectory export and logs exist but there is no automated quality tracking. if you need eval, build it yourself or connect external tools. the loop is self-improving. measuring how well it improves is on you. comment LOOP and I'll send you the configs that control how fast Hermes learns and what it remembers. memory limits, skill auto-creation triggers, and the auxiliary model that runs the learning. Replace your entire team with 8 hermes agents👇

YanXbt

22,720 Aufrufe • vor 2 Monaten

HERMES AGENT WITHOUT THESE 3 FILES IS A CHATBOT. WITH THEM IT KNOWS WHO IT IS, WHO YOU ARE, AND WHAT IT LEARNED. SOUL.md — who the agent is. first thing in the system prompt. defines personality, voice, values, how it operates, what it can and can't do. structure yours like this: → identity (name, role, relationship to you) → values (what matters, what principles guide decisions) → voice (how it communicates, tone, style) → operations (autonomy level, ground rules) → restrictions (what it never does) → failure protocol (how to operate when things break) lives in ~/.hermes/SOUL.md. auto-seeded on first install. edit anytime. scanned for prompt injection on every load. keep it concise. SOUL.md injects into every turn. a 200-line soul burns tokens on every message. aim for 50-80 lines. one paragraph per section. MEMORY.md — what the agent remembers. persistent facts, insights, preferences. survives across sessions and restarts. capped at ~800 tokens by default: memory: memory_char_limit: 2200 the agent writes to this automatically as it learns about your work. USER.md — who you are. your profile, preferences, context. capped at ~500 tokens by default: memory: user_char_limit: 1375 injected every turn so the agent always knows who it's working for. bonus: AGENTS.md — project-specific instructions. drop one in any project folder. subdirectory AGENTS.md files load lazily during tool calls, not at startup. keeps your system prompt light. prompt stack order on every turn: SOUL.md → tool guidance → MEMORY.md + USER.md → skills index → AGENTS.md → platform hints skills come preloaded. 60+ built-in tools. the agent creates more skills from completed work. you focus on these 3 files. each profile gets its own copy: ~/.hermes/SOUL.md (default profile) ~/.hermes/profiles/researcher/SOUL.md ~/.hermes/profiles/ops/SOUL.md different agent, different soul, different memory, same machine. full breakdown of Hermes as a Personal AI OS in the article 👇

YanXbt

28,924 Aufrufe • vor 3 Monaten