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HERMES AGENT BUILT A SKILL THAT AUTOMATED AN 8-HOUR WORKFLOW INTO 80 MINUTES. THE AGENT BUILT IT FROM ITS OWN COMPLETED SESSIONS. one user ran their customer pipeline through Hermes repeatedly: meetings → recordings → product requirements → technical specs → development → delivery. after enough runs, Hermes identified... the pattern and created a skill that handles the full pipeline: → takes meeting recordings → extracts requirements automatically → runs research on the extracted data → generates product requirement documents → generates technical specifications → delegates the build to a coding agent → sends a link to the finished product what Hermes skills contain: → when to use (trigger conditions) → step-by-step procedure → known pitfalls to avoid → verification steps (how to confirm it worked) stored as markdown in ~/.hermes/skills/. readable, editable, permanent. agents with 20+ self-created skills finish similar future tasks ~40% faster. month 1 you explain everything. month 3 the agent runs your core workflows from the skills it built along the way. full breakdown of Hermes as a Personal AI OS in the article 👇show more

YanXbt

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HERMES AGENT CROSSED 140,000 GITHUB STARS IN 3 MONTHS AND JUST BECAME THE MOST USED AGENT IN THE WORLD. Most AI agents forget everything between sessions. Hermes writes its own skills from experience. Next time it runs the skill, improves it, and gets faster. Independent benchmarks show agents with 20+ self-created skills complete similar tasks 40% faster than fresh instances. Qwen 3.6 where the 35B version outperforms last year's 120B models at one third the memory footprint. DGX Spark with 128GB unified memory running everything locally at $0 per month after hardware. The setup takes 30 minutes. LM Studio plus Qwen 3.6 27B for the model server. One install script for Hermes. One config connecting them. Set context window to 65,536 tokens or nothing works. After one month of daily use your skills directory has 20 to 50 learned workflows. Your Hermes is genuinely different from anyone else's.

HERMES AGENT CROSSED 140,000 GITHUB STARS IN 3 MONTHS AND JUST BECAME THE MOST USED AGENT IN THE WORLD. Most AI agents forget everything between sessions. Hermes writes its own skills from experience. Next time it runs the skill, improves it, and gets faster. Independent benchmarks show agents with 20+ self-created skills complete similar tasks 40% faster than fresh instances. Qwen 3.6 where the 35B version outperforms last year's 120B models at one third the memory footprint. DGX Spark with 128GB unified memory running everything locally at $0 per month after hardware. The setup takes 30 minutes. LM Studio plus Qwen 3.6 27B for the model server. One install script for Hermes. One config connecting them. Set context window to 65,536 tokens or nothing works. After one month of daily use your skills directory has 20 to 50 learned workflows. Your Hermes is genuinely different from anyone else's.

Lummox

69,676 просмотров • 2 месяцев назад

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👇

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 просмотров • 1 месяц назад

You need to try Hermes RIGHT NOW. OpenClaw was the breakthrough. Hermes feels like the evolution. Here’s why AI power users are quietly switching: • Hermes learns from you over time • It creates its own reusable skills • Memory stays curated instead of bloated • Agents improve every 10 turns automatically • It actually feels stable on day 30 The wildest part: Hermes agents build workflows from your behavior. One user asked their agent to configure Twingate once. The agent: → learned the process → created a reusable skill → stored it for future tasks → improved its own workflow automatically That’s not prompt engineering anymore. That’s agent evolution. Meanwhile most people are still babysitting broken OpenClaw setups and manually importing marketplace skills. Hermes took a different path: Less clutter. Less tweaking. More autonomy. And it’s working. It already flipped OpenClaw in OpenRouter token usage and became one of the fastest-growing AI repos on GitHub. The bigger shift: We’re entering the era where the model matters less than the harness around it. GPT-5.5, Grok, Qwen: They’re already powerful enough. The real edge now is: • memory systems • self-improvement loops • skill creation • agent orchestration Hermes understands that. Most people still think AI agents are glorified chatbots. The people using Hermes are building AI teammates.

You need to try Hermes RIGHT NOW. OpenClaw was the breakthrough. Hermes feels like the evolution. Here’s why AI power users are quietly switching: • Hermes learns from you over time • It creates its own reusable skills • Memory stays curated instead of bloated • Agents improve every 10 turns automatically • It actually feels stable on day 30 The wildest part: Hermes agents build workflows from your behavior. One user asked their agent to configure Twingate once. The agent: → learned the process → created a reusable skill → stored it for future tasks → improved its own workflow automatically That’s not prompt engineering anymore. That’s agent evolution. Meanwhile most people are still babysitting broken OpenClaw setups and manually importing marketplace skills. Hermes took a different path: Less clutter. Less tweaking. More autonomy. And it’s working. It already flipped OpenClaw in OpenRouter token usage and became one of the fastest-growing AI repos on GitHub. The bigger shift: We’re entering the era where the model matters less than the harness around it. GPT-5.5, Grok, Qwen: They’re already powerful enough. The real edge now is: • memory systems • self-improvement loops • skill creation • agent orchestration Hermes understands that. Most people still think AI agents are glorified chatbots. The people using Hermes are building AI teammates.

Dami-Defi

17,062 просмотров • 2 месяцев назад

A CHINESE LAB VISUALIZED 2,000 NEURONS AND 1,191,000 SYNAPSES IN 3D. HERMES AGENT HIT 140,000 STARS RUNNING THE SAME NETWORK LOCALLY FOR $0 hermes is the first agent that writes its own skills from experience. complete a task once and it saves the procedure as a markdown file for next time agents with 20+ self-created skills complete similar tasks 40% faster than fresh instances. less time and less tokens to get the same result qwen 3.6 35b outperforms last year's 120b models and runs on 20gb of memory. the intelligence that needed a data center now fits on your desk setup takes 30 minutes. install lm studio, pull qwen 3.6, install hermes, point it at localhost. zero api fees, zero data leaving your machine most people pay for cloud agents that forget everything between sessions. the ones running hermes locally in 2026 will look very far ahead in 2028 bookmark this and read the article below

A CHINESE LAB VISUALIZED 2,000 NEURONS AND 1,191,000 SYNAPSES IN 3D. HERMES AGENT HIT 140,000 STARS RUNNING THE SAME NETWORK LOCALLY FOR $0 hermes is the first agent that writes its own skills from experience. complete a task once and it saves the procedure as a markdown file for next time agents with 20+ self-created skills complete similar tasks 40% faster than fresh instances. less time and less tokens to get the same result qwen 3.6 35b outperforms last year's 120b models and runs on 20gb of memory. the intelligence that needed a data center now fits on your desk setup takes 30 minutes. install lm studio, pull qwen 3.6, install hermes, point it at localhost. zero api fees, zero data leaving your machine most people pay for cloud agents that forget everything between sessions. the ones running hermes locally in 2026 will look very far ahead in 2028 bookmark this and read the article below

starmex

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Hermes Agent. Zero to full autonomous operation. One complete course. Installation. Skills. Memory. MCP. Scheduler. Multi-agent. Works while you sleep. The people who build this system will never manually operate a content, research, or business workflow again. The compounding starts from the first automated skill that runs. Read this and bookmark it now.

Hermes Agent. Zero to full autonomous operation. One complete course. Installation. Skills. Memory. MCP. Scheduler. Multi-agent. Works while you sleep. The people who build this system will never manually operate a content, research, or business workflow again. The compounding starts from the first automated skill that runs. Read this and bookmark it now.

CyrilXBT

80,668 просмотров • 2 месяцев назад

Hermes Agent. Zero to full autonomous operation. One complete course. Installation. Skills. Memory. MCP. Scheduler. Multi-agent. Works while you sleep. The people who build this system will never manually operate a content, research, or business workflow again. The compounding starts from the first automated skill that runs. Read this and bookmark it now.

Hermes Agent. Zero to full autonomous operation. One complete course. Installation. Skills. Memory. MCP. Scheduler. Multi-agent. Works while you sleep. The people who build this system will never manually operate a content, research, or business workflow again. The compounding starts from the first automated skill that runs. Read this and bookmark it now.

CyrilXBT

176,900 просмотров • 2 месяцев назад

Hermes Desktop Just Changed Everything Hermes just became way easier to use. No terminal, no complicated setup, no command-line stress. The new Hermes desktop app gives you a visual way to run a powerful AI agent. Here’s what it does: → Installs Hermes automatically. → Lets you choose OpenRouter, Anthropic, OpenAI, or local models. → Saves every chat session. → Creates separate profiles for different workflows. → Stores persistent memory. → Gives you access to 68 built-in tools. → Supports MCP connections. The biggest unlock? Hermes can learn skills from tasks and improve the more you use it.

Hermes Desktop Just Changed Everything Hermes just became way easier to use. No terminal, no complicated setup, no command-line stress. The new Hermes desktop app gives you a visual way to run a powerful AI agent. Here’s what it does: → Installs Hermes automatically. → Lets you choose OpenRouter, Anthropic, OpenAI, or local models. → Saves every chat session. → Creates separate profiles for different workflows. → Stores persistent memory. → Gives you access to 68 built-in tools. → Supports MCP connections. The biggest unlock? Hermes can learn skills from tasks and improve the more you use it.

Julian Goldie SEO

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HERMES JUST FIXED THE BIGGEST PROBLEM WITH BROWSER AGENTS Most AI agents still click around websites like confused interns. This new setup gives them the map. Hermes + → Hermes now connects to Browserbase’s new Browse hub → Browse launched with 100+ browser skills → Each skill is a plain-text playbook for a specific website or task → Your agent can search, preview, and install skills inside Hermes Why This Matters: ✓ Less random clicking ✓ Fewer timeouts ✓ Better form filling ✓ More reliable website navigation ✓ Skills can be edited, reused, bundled, and shared The Real Stack: → Hermes runs the agent → Browserbase handles cloud browser infrastructure → gives the agent site-specific skills → Vision helps when pages get weird → Bundles let you load repeat workflows faster The killer detail: If a website breaks, you don’t wait for the model to magically improve. You update the skill. Now your agent gets better forever. That’s the difference between an AI tool and an actual agent system.

HERMES JUST FIXED THE BIGGEST PROBLEM WITH BROWSER AGENTS Most AI agents still click around websites like confused interns. This new setup gives them the map. Hermes + → Hermes now connects to Browserbase’s new Browse hub → Browse launched with 100+ browser skills → Each skill is a plain-text playbook for a specific website or task → Your agent can search, preview, and install skills inside Hermes Why This Matters: ✓ Less random clicking ✓ Fewer timeouts ✓ Better form filling ✓ More reliable website navigation ✓ Skills can be edited, reused, bundled, and shared The Real Stack: → Hermes runs the agent → Browserbase handles cloud browser infrastructure → gives the agent site-specific skills → Vision helps when pages get weird → Bundles let you load repeat workflows faster The killer detail: If a website breaks, you don’t wait for the model to magically improve. You update the skill. Now your agent gets better forever. That’s the difference between an AI tool and an actual agent system.

Julian Goldie SEO

43,472 просмотров • 2 месяцев назад

MOST AI AGENTS RESET TO ZERO EVERY TIME YOU OPEN A NEW SESSION. Hermes Agent was built to do the opposite. Every task compounds. Every workflow becomes reusable. Every session teaches the next one. That is the core thesis behind Hermes, and it completely changes how AI agents work. Unlike most AI agents built by software tool companies, Hermes was created by the researchers training the Hermes model family itself. Meaning: The same system used internally to generate training data is now open source and available to everyone. One install gives you access to: Claude. GPT. Grok. Local models via Ollama. Telegram, Discord, Slack, iMessage integrations. Custom skills. Persistent memory. CLI control. But the real unlock is the compounding loop: You give Hermes a task. It records every tool call, decision, and result. Then it converts successful workflows into reusable skills automatically. A Hermes setup running for 3 months becomes fundamentally smarter than a fresh install. That’s the big idea. One of the coolest parts: You literally watch the agent evolve in real time from a blank install into a personalized AI operator. Instead of watching Netflix today, spend 28 mins with this. Follow Dami-Defi for more AI systems, agent workflows, and infrastructure alpha.

MOST AI AGENTS RESET TO ZERO EVERY TIME YOU OPEN A NEW SESSION. Hermes Agent was built to do the opposite. Every task compounds. Every workflow becomes reusable. Every session teaches the next one. That is the core thesis behind Hermes, and it completely changes how AI agents work. Unlike most AI agents built by software tool companies, Hermes was created by the researchers training the Hermes model family itself. Meaning: The same system used internally to generate training data is now open source and available to everyone. One install gives you access to: Claude. GPT. Grok. Local models via Ollama. Telegram, Discord, Slack, iMessage integrations. Custom skills. Persistent memory. CLI control. But the real unlock is the compounding loop: You give Hermes a task. It records every tool call, decision, and result. Then it converts successful workflows into reusable skills automatically. A Hermes setup running for 3 months becomes fundamentally smarter than a fresh install. That’s the big idea. One of the coolest parts: You literally watch the agent evolve in real time from a blank install into a personalized AI operator. Instead of watching Netflix today, spend 28 mins with this. Follow Dami-Defi for more AI systems, agent workflows, and infrastructure alpha.

Dami-Defi

11,668 просмотров • 2 месяцев назад

HERMES AGENT SHIPS WITH A BUNDLED SKILL FOR ANDREJ KARPATHY'S LLM WIKI PATTERN. A SELF-IMPROVING KNOWLEDGE BASE THAT GROWS EVERY TIME YOU FEED IT. mentioned this briefly in the overnight workflow article. here is the full breakdown. what it is: a self-improving knowledge base built as interlinked markdown files. unlike RAG (which rediscovers knowledge from scratch every query), the wiki compiles knowledge once and keeps it current. cross-references stay linked. contradictions get flagged automatically. synthesis reflects everything ingested so far. why this matters for Hermes memory: Hermes built-in memory knows YOU. it remembers your conversations, your preferences, your business context across sessions. but it doesn't know your inbox. or your meeting transcripts. or that article you saved last week. or the expert framework you want it to learn. the LLM Wiki solves that. THE DIVISION OF LABOR human curates sources and directs analysis. agent summarizes, cross-references, files, and maintains consistency. you drop in articles, transcripts, notes. Hermes indexes them, links related concepts, flags contradictions, updates affected pages. your knowledge base grows itself. SETUP IS ONE COMMAND the skill ships with Hermes. enable it. set WIKI_PATH in ~/.hermes/.env: WIKI_PATH=/Users/you/wiki defaults to ~/wiki if unset. then drop anything into it: "index this article into my wiki: [paste URL or text]" Hermes reads it, builds a source page, updates related entries, flags contradictions. THE OBSIDIAN ANGLE set OBSIDIAN_VAULT_PATH to the same directory. now your wiki is visible in Obsidian's graph view. nodes, links, backlinks. all built by Hermes. for headless servers: install obsidian-headless. syncs vaults without a GUI. agent writes from the server, you read on your laptop. THE COMPOUND EFFECT Hermes knows you. the wiki knows your world. combine them and the agent answers questions using BOTH contexts at once. month 1: you explain things twice. month 3: the agent references the wiki on its own. answers get sharper because the knowledge base got sharper. AUTOMATIONS THAT FEED THE WIKI set cron jobs to ingest automatically: "every day at 9am, check Granola for new meetings. add any new transcripts to my wiki under meeting notes." "every morning, scan my Gmail starred items. add anything worth keeping to the wiki." "every week, check arXiv for new papers in [your niche]. summarize and file." your wiki grows while you sleep. Hermes never forgets what gets indexed. THE LIMITATION TO KNOW unlike Hermes memory (which is conversational and lives across sessions), the wiki is a separate knowledge layer. Hermes won't pull from the wiki automatically unless you reference it or save it as a skill. best setup: build an LLM Wiki personality that tells Hermes to consult the wiki when answering strategy questions or domain-specific queries. full HERMES AGENT OVERNIGHT WORKFLOW👇

HERMES AGENT SHIPS WITH A BUNDLED SKILL FOR ANDREJ KARPATHY'S LLM WIKI PATTERN. A SELF-IMPROVING KNOWLEDGE BASE THAT GROWS EVERY TIME YOU FEED IT. mentioned this briefly in the overnight workflow article. here is the full breakdown. what it is: a self-improving knowledge base built as interlinked markdown files. unlike RAG (which rediscovers knowledge from scratch every query), the wiki compiles knowledge once and keeps it current. cross-references stay linked. contradictions get flagged automatically. synthesis reflects everything ingested so far. why this matters for Hermes memory: Hermes built-in memory knows YOU. it remembers your conversations, your preferences, your business context across sessions. but it doesn't know your inbox. or your meeting transcripts. or that article you saved last week. or the expert framework you want it to learn. the LLM Wiki solves that. THE DIVISION OF LABOR human curates sources and directs analysis. agent summarizes, cross-references, files, and maintains consistency. you drop in articles, transcripts, notes. Hermes indexes them, links related concepts, flags contradictions, updates affected pages. your knowledge base grows itself. SETUP IS ONE COMMAND the skill ships with Hermes. enable it. set WIKI_PATH in ~/.hermes/.env: WIKI_PATH=/Users/you/wiki defaults to ~/wiki if unset. then drop anything into it: "index this article into my wiki: [paste URL or text]" Hermes reads it, builds a source page, updates related entries, flags contradictions. THE OBSIDIAN ANGLE set OBSIDIAN_VAULT_PATH to the same directory. now your wiki is visible in Obsidian's graph view. nodes, links, backlinks. all built by Hermes. for headless servers: install obsidian-headless. syncs vaults without a GUI. agent writes from the server, you read on your laptop. THE COMPOUND EFFECT Hermes knows you. the wiki knows your world. combine them and the agent answers questions using BOTH contexts at once. month 1: you explain things twice. month 3: the agent references the wiki on its own. answers get sharper because the knowledge base got sharper. AUTOMATIONS THAT FEED THE WIKI set cron jobs to ingest automatically: "every day at 9am, check Granola for new meetings. add any new transcripts to my wiki under meeting notes." "every morning, scan my Gmail starred items. add anything worth keeping to the wiki." "every week, check arXiv for new papers in [your niche]. summarize and file." your wiki grows while you sleep. Hermes never forgets what gets indexed. THE LIMITATION TO KNOW unlike Hermes memory (which is conversational and lives across sessions), the wiki is a separate knowledge layer. Hermes won't pull from the wiki automatically unless you reference it or save it as a skill. best setup: build an LLM Wiki personality that tells Hermes to consult the wiki when answering strategy questions or domain-specific queries. full HERMES AGENT OVERNIGHT WORKFLOW👇

YanXbt

30,734 просмотров • 1 месяц назад

You can now connect Hermes Agent directly to your browser as a side panel. It's called Hermes Browser Extension. It reads your active tab and sends the context straight into a live Hermes session. > Summarize, explain, or extract action items from any page > Connects to a local gateway, Hermes Cloud, or a self-hosted server > Works with Chrome, Edge, Brave, and other Chromium browsers > Full Hermes runtime: tools, skills, sessions, and memory included 100% Free. Open Source.

You can now connect Hermes Agent directly to your browser as a side panel. It's called Hermes Browser Extension. It reads your active tab and sends the context straight into a live Hermes session. > Summarize, explain, or extract action items from any page > Connects to a local gateway, Hermes Cloud, or a self-hosted server > Works with Chrome, Edge, Brave, and other Chromium browsers > Full Hermes runtime: tools, skills, sessions, and memory included 100% Free. Open Source.

Simplifying AI

43,450 просмотров • 1 месяц назад

I didn't touch TouchDesigner myself. Hermes agent learned it from scratch and built this: → navigated my desktop with computer use → figured out how to connect to TouchDesigner → read my reference images → iterated on the art with me in a self-learning loop → then saved what it learned as a reusable skill for the next image all powered by MiniMax (official) M3 × Hermes Desktop Agent Nous Research Here's a full breakdown 📽️

I didn't touch TouchDesigner myself. Hermes agent learned it from scratch and built this: → navigated my desktop with computer use → figured out how to connect to TouchDesigner → read my reference images → iterated on the art with me in a self-learning loop → then saved what it learned as a reusable skill for the next image all powered by MiniMax (official) M3 × Hermes Desktop Agent Nous Research Here's a full breakdown 📽️

Amber Shen

115,054 просмотров • 1 месяц назад

This guy literally tested Hermes Agent vs OpenClaw side by side. Hermes won. And it wasn't close. Here's what made the difference: → Hermes built the website faster → Hermes gave live updates the whole time. OpenClaw went silent. → Hermes designed a cleaner page using the exact same AI model → And then Hermes did something OpenClaw can't do at all. It learned from the task. Every mistake gets logged. Every win gets saved as a reusable skill. The more you use it, the smarter it gets. OpenClaw doesn't do this unless you manually set up a learning file. Hermes does it automatically. Every single time. Other wins: → Runs free with Ollama + MiniMax → Works on Telegram, Discord, Slack, WhatsApp, Signal, and Email → Supports 200+ AI models → Built-in migration tool from OpenClaw — one command to switch 11,600 GitHub stars. 142 contributors. If you're already on OpenClaw, you don't have to start over. Just ask Hermes to import everything.

This guy literally tested Hermes Agent vs OpenClaw side by side. Hermes won. And it wasn't close. Here's what made the difference: → Hermes built the website faster → Hermes gave live updates the whole time. OpenClaw went silent. → Hermes designed a cleaner page using the exact same AI model → And then Hermes did something OpenClaw can't do at all. It learned from the task. Every mistake gets logged. Every win gets saved as a reusable skill. The more you use it, the smarter it gets. OpenClaw doesn't do this unless you manually set up a learning file. Hermes does it automatically. Every single time. Other wins: → Runs free with Ollama + MiniMax → Works on Telegram, Discord, Slack, WhatsApp, Signal, and Email → Supports 200+ AI models → Built-in migration tool from OpenClaw — one command to switch 11,600 GitHub stars. 142 contributors. If you're already on OpenClaw, you don't have to start over. Just ask Hermes to import everything.

Julian Goldie SEO

40,877 просмотров • 4 месяцев назад

WTF, THIS CHINESE FOUNDER RUNS HIS $10,000+ STARTUP'S ENTIRE WORKFLOW THROUGH HERMES AGENT ON FOUR MACHINES SIMULTANEOUSLY A studio founder just broke down why Hermes is different from every other AI tool right now: → Long-term memory. Most LLMs forget everything after the chat ends. Hermes remembers your work habits and gets sharper the more you use it. → Real execution, not suggestions. This is the core difference from Claude. Claude tells you what to do – you still do it. Hermes takes the instruction and finishes the task itself. → Scheduled tasks that just work. No complicated setup. Set the plan once, it runs on its own. This is what actual "hands-off" looks like. He's not running this on one machine. He's got FOUR laptops running Hermes simultaneously – each one handling a different part of his workflow at the same time. This is what it looks like when one person operates like a full team. He's dropping a full workflow build tutorial next – built for founders and operators trying to lighten their workload. Bookmark this, you'll want to come back to it later.

WTF, THIS CHINESE FOUNDER RUNS HIS $10,000+ STARTUP'S ENTIRE WORKFLOW THROUGH HERMES AGENT ON FOUR MACHINES SIMULTANEOUSLY A studio founder just broke down why Hermes is different from every other AI tool right now: → Long-term memory. Most LLMs forget everything after the chat ends. Hermes remembers your work habits and gets sharper the more you use it. → Real execution, not suggestions. This is the core difference from Claude. Claude tells you what to do – you still do it. Hermes takes the instruction and finishes the task itself. → Scheduled tasks that just work. No complicated setup. Set the plan once, it runs on its own. This is what actual "hands-off" looks like. He's not running this on one machine. He's got FOUR laptops running Hermes simultaneously – each one handling a different part of his workflow at the same time. This is what it looks like when one person operates like a full team. He's dropping a full workflow build tutorial next – built for founders and operators trying to lighten their workload. Bookmark this, you'll want to come back to it later.

SCOTTY BEAM

11,654 просмотров • 1 месяц назад

Finally, a proper chat UI for Hermes Agent (open-source)! Hermes ships an official dashboard, but it's primarily built for management, and its chat is just a terminal piped into a browser tab. Hermes Web UI is an open-source chat-first alternative. It's self-hosted and points at your existing ~/.hermes state, so there's nothing new to configure. - It's a native web chat, not a terminal in a tab - Sessions group by date with a context ring - Kanban renders the agent's task board - Spaces manages your workspaces - Skills panel lists the full catalog - Tasks panel shows cron jobs - Insights show usage and activity - Memory shows MEMORY and SOUL files - Logs tails the agent, gateway, and error logs The whole setup runs 100% locally, binds to localhost by default, and you reach it over an SSH tunnel or Tailscale from your phone. I have shared the Hermes Web UI GitHub repo in the replies. Do note that it's a community project, not official, so expect occasional rough edges (concurrent profile runs are blocked for now). To dive deeper into Hermes Agent, my co-founder wrote a full masterclass about it, covering the learning loop, the memory tiers, self-evolving skills, GEPA, and running multiple isolated agents. Read it below.

Avi Chawla

77,513 просмотров • 2 месяцев назад

HERMES AGENT WITHOUT TOOLS IS A CHATBOT. WITH THEM IT BUILDS 3D TOWERS IN BLENDER, CHECKS STOCK PRICES, AND DRIVES VS CODE. tonbi JUST DROPPED THE FULL GUIDE. module 6 of his 10-part Hermes masterclass. best breakdown of the tool layer anyone has published. what you need to know: TOOLS vs SKILLS vs MCP skills = instructions (markdown, loaded into context) tools = callable functions (Python, agent emits call, Hermes executes) MCP = adapters to external systems (Blender, Stripe, Linear, Notion) every tool has three parts: → the function (does the real work) → the schema (what the model sees to decide when to call it) → the registry (makes the tool exist in the agent) the model never runs the function directly. it emits a structured request (tool name + JSON args). Hermes executes and returns the result. if the tool fails, the error goes back as JSON. the agent recovers instead of crashing. TOOL SETS CONTROL THE SURFACE hermes chat --tool-sets web # only web tools loaded. no files, no terminal. hermes chat --tool-sets safe # read-only: web search, vision, image gen. # no file writes. no terminal. no code execution. mid-session: /tools enable video /tools disable terminal or toggle in the dashboard: hermes dashboard → Skills → Tool Sets MCP SERVERS two transport types: STDIO (local subprocess) or HTTP (remote endpoint). add a server: hermes mcp # or ask: "add the MCP server for Blender" filter tools with include/exclude per server. keep only what you trust. security: → OAuth 2.1 PKCE (no long-lived tokens in config) → package scanning via api.osv. dev before launch → all MCP calls go through approval gates HERMES AS MCP SERVER hermes mcp serve exposes 10 tools via FastMCP. connect VS Code Copilot or Cursor to your running Hermes instance. BUILD YOUR OWN TOOL He built a stock price tool live: → Python function calling Finnhub API → schema with name, description, parameters → registered in tool_sets.py → agent calls it automatically when relevant any repeating API call in your workflow can become a native tool. full Hermes architecture deep-dive in the article 👇

HERMES AGENT WITHOUT TOOLS IS A CHATBOT. WITH THEM IT BUILDS 3D TOWERS IN BLENDER, CHECKS STOCK PRICES, AND DRIVES VS CODE. tonbi JUST DROPPED THE FULL GUIDE. module 6 of his 10-part Hermes masterclass. best breakdown of the tool layer anyone has published. what you need to know: TOOLS vs SKILLS vs MCP skills = instructions (markdown, loaded into context) tools = callable functions (Python, agent emits call, Hermes executes) MCP = adapters to external systems (Blender, Stripe, Linear, Notion) every tool has three parts: → the function (does the real work) → the schema (what the model sees to decide when to call it) → the registry (makes the tool exist in the agent) the model never runs the function directly. it emits a structured request (tool name + JSON args). Hermes executes and returns the result. if the tool fails, the error goes back as JSON. the agent recovers instead of crashing. TOOL SETS CONTROL THE SURFACE hermes chat --tool-sets web # only web tools loaded. no files, no terminal. hermes chat --tool-sets safe # read-only: web search, vision, image gen. # no file writes. no terminal. no code execution. mid-session: /tools enable video /tools disable terminal or toggle in the dashboard: hermes dashboard → Skills → Tool Sets MCP SERVERS two transport types: STDIO (local subprocess) or HTTP (remote endpoint). add a server: hermes mcp # or ask: "add the MCP server for Blender" filter tools with include/exclude per server. keep only what you trust. security: → OAuth 2.1 PKCE (no long-lived tokens in config) → package scanning via api.osv. dev before launch → all MCP calls go through approval gates HERMES AS MCP SERVER hermes mcp serve exposes 10 tools via FastMCP. connect VS Code Copilot or Cursor to your running Hermes instance. BUILD YOUR OWN TOOL He built a stock price tool live: → Python function calling Finnhub API → schema with name, description, parameters → registered in tool_sets.py → agent calls it automatically when relevant any repeating API call in your workflow can become a native tool. full Hermes architecture deep-dive in the article 👇

YanXbt

32,680 просмотров • 2 месяцев назад

Hermes agent just left the terminal. 𝗛𝗲𝗿𝗺𝗲𝘀 𝗗𝗲𝘀𝗸𝘁𝗼𝗽 dropped yesterday. native app for macOS, Windows, and Linux. for months Hermes was the agent that learned your projects, wrote its own skills, and built a model of who you are. all of it buried in terminal logs. now it has a window. the important part is that it's not a wrapper. it runs the same agent core, the same sessions, memory, and skills as the CLI. you can start a task in the terminal and finish it in the app without anything resetting. the state is shared across every interface, not copied between them. what the GUI actually adds: → streaming chat that shows live tool calls and inline reasoning instead of a spinner → a preview rail that renders pages, code, and images right beside the conversation → an artifacts panel that collects every file the agent has ever produced → remote gateway mode, so you can point the app at a VPS and run the heavy work elsewhere → skills, cron, profiles, and gateways managed point-and-click instead of through YAML → voice mode, drag-drop files, and inline image generation remote gateway mode is the one worth slowing down on. the agent runs 24/7 on a $5 server while you control it from your laptop like a local app. other agent UIs are chatboxes with a logo. this one shows the autonomy instead of hiding it, so you watch the skills load, the tools fire, and the artifacts pile up as it works. it was teased in Jensen's GTC keynote. MIT licensed, local-first, no telemetry. if you already run Hermes, download it and everything is already there. your chats, memory, and skills carry straight over. i wrote a full masterclass on Hermes Agent that walks through the SOUL. md identity layer, the three-tier memory system, the self-evolving skills loop, and how to run three specialized agents 24/7. desktop is the interface that finally does all of it justice. the article is quoted below.

Akshay 🚀

51,540 просмотров • 2 месяцев назад

Hermes Agent can use Autobrowse to make better browser skills. In this HN example, 2 iterations take us from: 102 seconds -> 35 23 turns -> 8 $1.46 -> $0.28 Instead of clicking step by step it decides to eval JS directly on the page and save that workflow to a skill.

Hermes Agent can use Autobrowse to make better browser skills. In this HN example, 2 iterations take us from: 102 seconds -> 35 23 turns -> 8 $1.46 -> $0.28 Instead of clicking step by step it decides to eval JS directly on the page and save that workflow to a skill.

Kyle Jeong

319,804 просмотров • 3 месяцев назад

Tried out stripe projects this week! built a customer support bot with hermes from Nous Research + supermemory. bot remembers every customer across sessions. the piece worth highlighting, Stripe projects ships a hermes skill that lets the agent auto-provision supermemory itself. ask hermes to build the bot, it runs stripe projects add supermemory/memory. stripe creates the supermemory account, syncs the api key to .env, and bills it on your stripe invoice. and supermemory is one of 30+ providers. databases ( Neon Postgres, Supabase), hosting ( Vercel , Cloudflare), auth ( Clerk), search ( Exa), analytics ( PostHog). one CLI for the whole stack.

Tried out stripe projects this week! built a customer support bot with hermes from Nous Research + supermemory. bot remembers every customer across sessions. the piece worth highlighting, Stripe projects ships a hermes skill that lets the agent auto-provision supermemory itself. ask hermes to build the bot, it runs stripe projects add supermemory/memory. stripe creates the supermemory account, syncs the api key to .env, and bills it on your stripe invoice. and supermemory is one of 30+ providers. databases ( Neon Postgres, Supabase), hosting ( Vercel , Cloudflare), auth ( Clerk), search ( Exa), analytics ( PostHog). one CLI for the whole stack.

Muskan Jain

20,335 просмотров • 1 месяц назад

HERMES AGENT CAN MAKE YOU MONEY. HERE ARE 3 SETUPS YOU CAN START TODAY. 1. automated lead generation one Hermes profile scans for gigs and contracts in your niche every morning. drafts personalized applications. sends to Telegram for your approval before sending. → SOUL. md defines your niche, skills, rate → cron job runs every morning at 8am → xurl + web search find the opportunities → you review and send from your phone 2. content at scale Hermes remembers your niche, your style, your keywords. it researches and drafts articles on a cron schedule. traffic turns into ad revenue, affiliate income, or leads. → SOUL. md defines your topics and tone → cron job drafts 1-2 articles per day → each draft gets sharper because Hermes saves what performed and what didn't as skills 3. selling AI ops to local businesses restaurants, clinics, agencies want automation. they can't build it. you can. → one Hermes profile per client, fully isolated → each client gets their own SOUL. md, memory, cron → charge $497/month per client to manage their workflows → 5 clients = $2,485/month recurring → Hermes runs the work. you keep the margin. all three share the same foundation: → separate Hermes profile per operation → SOUL. md defines the job → cron jobs run the work on schedule → Telegram approval before anything goes live → skills compound after every run full setup guide for Hermes Agent from installation to advanced use cases in the article 👇 comment OPS and I'll send you the full SOUL. md template for whichever setup fits your situation.

YanXbt

30,540 просмотров • 2 месяцев назад