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> installed Hermes Agent > launched several skills > opened outputs folder > empty > checked the config > MEMORY_PATH was on ./data/memory.db > restarted the process > the folder was created anew > all records are gone > the memory was reset with each restart > the scheduler... was triggered at 3 a.m. > timezone was UTC > skills were not picked up without restarting > SKILLS_WATCH has been disabled > failed skill just dropped silently > SKILL_RETRY is disabled by default > outputs lived separately from obsidian > i had to carry it with my hands Hermes was not broken. The config was default. before you run Hermes as a 24/7 operation, do this: > set an absolute path for MEMORY_PATH > specify the correct SCHEDULER_TIMEZONE > turn on SKILLS_WATCH=true > configure CONTEXT_FILES for preload > increase MEMORY_RETRIEVAL_DEPTH to 20 > send OUTPUT_PATH to Obsidian vault > enable Telegram notifications > setting up chaining between skills > add nightly memory consolidator > enable SKILL_RETRY with alertsshow more

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HERMES AGENT + OBSIDIAN IS A COMBINATION NOBODY IS TALKING ABOUT. Hermes ships with a bundled Obsidian skill. read, search, and create notes in your vault out of the box. why this combination is powerful: Hermes built-in memory is capped. MEMORY.md: 2,200 chars (~800 tokens). USER.md: 1,375 chars (~500 tokens). Obsidian vault has no cap. your agent writes research, session summaries, project context, and learned patterns as linked markdown notes. unlimited depth. the agent creates indexed notes by design. timestamps, backlinks, tags. every note connects to the knowledge graph. three ways to integrate: 1. BUNDLED OBSIDIAN SKILL (simplest) ships with Hermes. reads, searches, creates notes in your vault directly. hermes skills list | grep obsidian 2. OBSIDIAN MCP SERVER (deepest) 30+ tools: full-text search, tag lookup, note management, vault analysis, link analysis, orphan detection. add it via: hermes mcp 3. TELEGRAM + CRON → VAULT (always-on) set a cron job that writes daily summaries, research findings, or task reports directly into your Obsidian vault. your agent feeds the vault while you sleep. you review in Obsidian when you're ready. the unlock: Hermes memory handles what the agent needs to know per session (capped, injected). Obsidian handles everything the agent has ever learned (uncapped, searchable). short-term in Hermes. long-term in Obsidian. both accessible. both persistent. keep the vault scope narrow at first. start with one /Hermes folder. expand once you trust the workflow. 8 Loops Indise Hermes Agent👇

HERMES AGENT + OBSIDIAN IS A COMBINATION NOBODY IS TALKING ABOUT. Hermes ships with a bundled Obsidian skill. read, search, and create notes in your vault out of the box. why this combination is powerful: Hermes built-in memory is capped. MEMORY.md: 2,200 chars (~800 tokens). USER.md: 1,375 chars (~500 tokens). Obsidian vault has no cap. your agent writes research, session summaries, project context, and learned patterns as linked markdown notes. unlimited depth. the agent creates indexed notes by design. timestamps, backlinks, tags. every note connects to the knowledge graph. three ways to integrate: 1. BUNDLED OBSIDIAN SKILL (simplest) ships with Hermes. reads, searches, creates notes in your vault directly. hermes skills list | grep obsidian 2. OBSIDIAN MCP SERVER (deepest) 30+ tools: full-text search, tag lookup, note management, vault analysis, link analysis, orphan detection. add it via: hermes mcp 3. TELEGRAM + CRON → VAULT (always-on) set a cron job that writes daily summaries, research findings, or task reports directly into your Obsidian vault. your agent feeds the vault while you sleep. you review in Obsidian when you're ready. the unlock: Hermes memory handles what the agent needs to know per session (capped, injected). Obsidian handles everything the agent has ever learned (uncapped, searchable). short-term in Hermes. long-term in Obsidian. both accessible. both persistent. keep the vault scope narrow at first. start with one /Hermes folder. expand once you trust the workflow. 8 Loops Indise Hermes Agent👇

YanXbt

20,617 Aufrufe • vor 2 Monaten

THIS CREATOR MADE HIS HERMES AGENT 10X FASTER WITHOUT CHANGING THE MODEL, JUST BY ADDING ONE FILE TO HIS OBSIDIAN VAULT 00:02 the screen shows a massive second brain with hundreds of connected notes, but without a clear map an AI agent still treats every file like it could be the answer Hermes used to open 7 different documents and spend nearly 2 minutes searching for the current brief, even though the correct file was already sitting inside the vault the fix was one index file inside each major folder, listing the important subfolders, canonical files, and the exact document the agent should open first after reorganizing the vault, the same search dropped from 2 minutes to around 10 seconds, while several tasks went from 5 or 6 opened files to just one the model never changed, the $30 agent stack never changed, only the structure around it did, because a powerful agent without a map is still just wandering through folders blindly

THIS CREATOR MADE HIS HERMES AGENT 10X FASTER WITHOUT CHANGING THE MODEL, JUST BY ADDING ONE FILE TO HIS OBSIDIAN VAULT 00:02 the screen shows a massive second brain with hundreds of connected notes, but without a clear map an AI agent still treats every file like it could be the answer Hermes used to open 7 different documents and spend nearly 2 minutes searching for the current brief, even though the correct file was already sitting inside the vault the fix was one index file inside each major folder, listing the important subfolders, canonical files, and the exact document the agent should open first after reorganizing the vault, the same search dropped from 2 minutes to around 10 seconds, while several tasks went from 5 or 6 opened files to just one the model never changed, the $30 agent stack never changed, only the structure around it did, because a powerful agent without a map is still just wandering through folders blindly

Gipp 🦅

36,473 Aufrufe • vor 1 Monat

My Hermes Install Step by Step: 1. Install Ubuntu Linux on a machine – Once installed make sure you have the latest updates 2. Install both Google Chrome and Microsoft Edge browser and log in to your accounts to synch bookmarks/favorites 3. Set up an Ollama account at – I have the annual Pro Plan (if I can ever come up with the funds I will probably spring for the Max plan but Pro is simply awesome) 4. Install Ollama and then run “ollama run glm-5.1:cloud” – It will then have you authenticate to your account and add your machine 5. Install Hermes (watch my video for explanation around this as you may get interrupted during install) 6. Once Hermes is installed you will be prompted to configure. I chose the default quick configure. For model provider select Ollama, provide your Ollama API key, then for model choose desired model. At this point in time I recommend glm-5.1 7. Download Obsidian as your Hermes second brain, set up a vault then tell Hermes to integrate it and provide Hermes the vault location 8. Start building and have fun!

My Hermes Install Step by Step: 1. Install Ubuntu Linux on a machine – Once installed make sure you have the latest updates 2. Install both Google Chrome and Microsoft Edge browser and log in to your accounts to synch bookmarks/favorites 3. Set up an Ollama account at – I have the annual Pro Plan (if I can ever come up with the funds I will probably spring for the Max plan but Pro is simply awesome) 4. Install Ollama and then run “ollama run glm-5.1:cloud” – It will then have you authenticate to your account and add your machine 5. Install Hermes (watch my video for explanation around this as you may get interrupted during install) 6. Once Hermes is installed you will be prompted to configure. I chose the default quick configure. For model provider select Ollama, provide your Ollama API key, then for model choose desired model. At this point in time I recommend glm-5.1 7. Download Obsidian as your Hermes second brain, set up a vault then tell Hermes to integrate it and provide Hermes the vault location 8. Start building and have fun!

Mike Gannotti

109,010 Aufrufe • vor 4 Monaten

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 Aufrufe • vor 1 Monat

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 Aufrufe • vor 2 Monaten

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 Aufrufe • vor 2 Monaten

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 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 2 Monaten

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 Aufrufe • vor 2 Monaten

how to set up hermes agent step by step. built-in memory, 40+ tools, works on your phone, and what to think of hermes vs openclaw: 1. hermes is a personal AI agent that runs in your terminal. think of it like open claw but with built-in memory, 40+ tools out of the box, and 90% cheaper token costs. you install it with one command. 2. the 3 problems with open claw that hermes solves: no memory (you keep repeating yourself), constant gateway restarts, and zero visibility into what you're spending on tokens. 3. hermes remembers everything. every completed task gets saved to memory. it searches through past logs to find solutions. over time it literally gets smarter at your specific workflows. 4. connect it to open router. you see exact costs per model per task. free models rotate weekly. one founder went from $130 every five days on open claw to $10 on hermes. same output. 5. it comes preloaded with skills. apple notes, imessage, find my, browser, web search, image generation, cron jobs. no hunting for plugins. 6. connect it to obsidian so it reads your entire vault. connect it to gstack for your dev environment. create custom skills for your specific workflows. 7. the biggest money saver: have it write code once for recurring tasks. then it runs without burning tokens every time. stop paying an LLM to do the same scrape or report daily. 8. run it on android via telegram. name your agents. talk to them like coworkers. in this episode imran shows you how to set this up. 9. you can run it bare metal, in docker, or serverless on modal. pick your risk level. i begged imran to come on The Startup Ideas Podcast (SIP) 🧃 and walk through the full installation live. he made it impossibly clear. if you've heard of Hermes Agent and want the clearest explanation of how to get set up like a pro let me know what you want me to cover on the next ep this is the best personal agent setup video on the internet right now. watch

how to set up hermes agent step by step. built-in memory, 40+ tools, works on your phone, and what to think of hermes vs openclaw: 1. hermes is a personal AI agent that runs in your terminal. think of it like open claw but with built-in memory, 40+ tools out of the box, and 90% cheaper token costs. you install it with one command. 2. the 3 problems with open claw that hermes solves: no memory (you keep repeating yourself), constant gateway restarts, and zero visibility into what you're spending on tokens. 3. hermes remembers everything. every completed task gets saved to memory. it searches through past logs to find solutions. over time it literally gets smarter at your specific workflows. 4. connect it to open router. you see exact costs per model per task. free models rotate weekly. one founder went from $130 every five days on open claw to $10 on hermes. same output. 5. it comes preloaded with skills. apple notes, imessage, find my, browser, web search, image generation, cron jobs. no hunting for plugins. 6. connect it to obsidian so it reads your entire vault. connect it to gstack for your dev environment. create custom skills for your specific workflows. 7. the biggest money saver: have it write code once for recurring tasks. then it runs without burning tokens every time. stop paying an LLM to do the same scrape or report daily. 8. run it on android via telegram. name your agents. talk to them like coworkers. in this episode imran shows you how to set this up. 9. you can run it bare metal, in docker, or serverless on modal. pick your risk level. i begged imran to come on The Startup Ideas Podcast (SIP) 🧃 and walk through the full installation live. he made it impossibly clear. if you've heard of Hermes Agent and want the clearest explanation of how to get set up like a pro let me know what you want me to cover on the next ep this is the best personal agent setup video on the internet right now. watch

GREG ISENBERG

621,164 Aufrufe • vor 4 Monaten

HERMES AGENT IS PULLING AHEAD OF OPENCLAW. 8 FEATURES THAT WILL MAKE YOU SWITCH. 1. HERMES GETS SMARTER EVERY RUN. Hermes updates its own skills after every completed task. what worked gets saved. what failed gets refined. the Curator runs in the background every 7 days. prunes unused skills. consolidates duplicates. archives stale procedures to .archive/ (recoverable). your skill library stays clean without manual work. agents with 20+ self-created skills finish similar tasks ~40% faster. 2. CHECKPOINTS BEFORE EVERY FILE CHANGE. before Hermes touches your files, it snapshots the working directory with a shadow git store. if anything breaks: /rollback # restore last checkpoint /rollback 3 # go back 3 checkpoints config: → max 20 snapshots per project → max 10MB per file, 500MB total store → auto-prune after 7 days → opt-in: set checkpoints.enabled: true you can also restore a single file without affecting the rest of the directory. 3. STABLE RELEASES. Hermes ships fewer updates. the ones it ships go through 500+ PRs per release with community testing before merge. v0.16.0 had 874 commits and 542 merged PRs. the update system runs syntax validation after every pull. if anything breaks, it auto-rolls back to the last working state. 4. 27+ MESSAGING PLATFORMS. Telegram, Discord, Slack, WhatsApp, Signal, iMessage, SMS, Email, Teams, Matrix, and 17 more. one gateway process covers all of them. 5. PROFILE ISOLATION. separate agents with their own model, memory, skills, cron jobs, and SOUL.md. run a researcher on GPT-5.5 and a coder on Fable 5 simultaneously on the same machine. 6. KANBAN + DISPATCHER. task orchestration with 60-second dispatch cycle, zombie detection, heartbeat tracking, retry budgets. assign tasks to agents from a visual board. 7. /GOAL WITH JUDGE MODEL. persistent objectives across turns. a judge evaluates after each turn: done or continue. runs for hours autonomously. 8. BUILT-IN MIGRATION FROM OPENCLAW. hermes claw migrate one command moves your OpenClaw setup to Hermes. supports --dry-run to preview before changing anything. also migrates legacy Clawdbot and Moldbot setups. OpenClaw still has the bigger ecosystem and more community integrations. both tools are open source. both are actively developed. this is about which architecture compounds better over months of use. full Hermes SOUL . MD guide 👇

YanXbt

19,573 Aufrufe • vor 2 Monaten

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

30,804 Aufrufe • vor 2 Monaten

HERMES AGENT CAN CREATE VIDEOS. NOT WITH AN API CALL. IT WRITES THE CODE, RENDERS THE SCENES, AND STITCHES THEM INTO AN MP4. the video attached to this post was generated by Hermes Agent using manim-video skill. three bundled video skills most people skip: 1. MANIM VIDEO 3Blue1Brown-style animated explainers. algorithm visualizations, equation derivations, architecture diagrams, data stories. the pipeline: PLAN → CODE → RENDER → STITCH → AUDIO → REVIEW Hermes writes a plan.md with narrative arc and scene list. then codes a Python script with one class per scene. renders each scene through Manim CE. stitches clips with ffmpeg. adds voiceover if you want it. requirements: → Python 3.10+ → Manim Community Edition v0.20+ → LaTeX (texlive-full) → ffmpeg → no GPU needed draft quality: manim -ql production quality: manim -qh 2. HYPERFRAMES complement to manim-video. use manim for math and algorithms. use hyperframes for everything else: motion graphics, talking-head with captions, product tours, social overlays, shader transitions. HTML is the source of truth. GSAP timeline for animation. CSS for appearance. HyperFrames engine captures frame-by-frame and encodes to MP4 or WebM with ffmpeg. 3. KANBAN VIDEO ORCHESTRATOR this is the advanced play. a multi-agent video production pipeline backed by Hermes Kanban. it creates profiles for each video role. a director profile decomposes the project into kanban tasks. renderer profiles pick up scenes and produce them. the orchestrator decides which skill fits each scene: manim-video for math, hyperframes for motion graphics, p5js for generative art, blender-mcp for 3D, ascii-video for terminal aesthetics. one prompt. multiple agents. one final video. HOW TO USE: enable any of these: /skills search manim /skills search hyperframes /skills search video or ask directly: "create a 60-second explainer video about how the self-improvement loop works in Hermes Agent. use manim style. dark background, amber and teal accents." Hermes writes the plan, codes every scene, renders, stitches, and delivers an MP4. you review and publish. comment MANIM and I'll send you the exact prompt I used to generate the video in this post. full Hermes NIGHT MODE WORKFLOW 👇

YanXbt

33,371 Aufrufe • vor 2 Monaten

THIS GUY CONNECTED HIS AI AGENTS TO HIS OBSIDIAN AND BUILT A BRAIN THAT LEARNS ON ITS OWN. HERE'S HOW TO BUILD IT Obsidian is just markdown files sitting in a folder. That turns out to be the perfect memory for an AI agent, because an agent can read and write those files directly. He wired his agents into the vault so they pull context from it, do the work, and write what they learned back. The notes aren't the point. The loop is, and it gets sharper every cycle How to build it: 1. Point an agent at your vault. The fastest way, no plugins, no API keys: open a terminal and run npx obsidian-mcp /path/to/your/vault. That exposes your Obsidian folder to Claude as a tool it can read, search, and write to. Add it to your Claude Code or Cowork config and restart 2. Confirm it can see the brain. Ask it: "list the notes in my vault and summarize what's in them." If it reads them back, the connection is live. Now it starts every task with everything the vault already holds instead of from zero 3. Give each agent one job and a write-back rule. Tell it: "research this, then save what you found as a new note in /brain with links to related notes." One agent researches, one summarizes, one plans. Each writes its output back into the vault 4. Close the loop. Add one line to every agent's instructions: "read /brain before starting, write your result back when done." Now each task leaves the vault richer, and the next run reads that before it works. It compounds instead of resetting 5. You only steer. Review what the brain produces, point it at the next thing. The agents handle the reading, writing, and connecting The edge isn't better notes. It's a brain that feeds itself, so the work gets sharper every cycle instead of starting over Bookmark this

THIS GUY CONNECTED HIS AI AGENTS TO HIS OBSIDIAN AND BUILT A BRAIN THAT LEARNS ON ITS OWN. HERE'S HOW TO BUILD IT Obsidian is just markdown files sitting in a folder. That turns out to be the perfect memory for an AI agent, because an agent can read and write those files directly. He wired his agents into the vault so they pull context from it, do the work, and write what they learned back. The notes aren't the point. The loop is, and it gets sharper every cycle How to build it: 1. Point an agent at your vault. The fastest way, no plugins, no API keys: open a terminal and run npx obsidian-mcp /path/to/your/vault. That exposes your Obsidian folder to Claude as a tool it can read, search, and write to. Add it to your Claude Code or Cowork config and restart 2. Confirm it can see the brain. Ask it: "list the notes in my vault and summarize what's in them." If it reads them back, the connection is live. Now it starts every task with everything the vault already holds instead of from zero 3. Give each agent one job and a write-back rule. Tell it: "research this, then save what you found as a new note in /brain with links to related notes." One agent researches, one summarizes, one plans. Each writes its output back into the vault 4. Close the loop. Add one line to every agent's instructions: "read /brain before starting, write your result back when done." Now each task leaves the vault richer, and the next run reads that before it works. It compounds instead of resetting 5. You only steer. Review what the brain produces, point it at the next thing. The agents handle the reading, writing, and connecting The edge isn't better notes. It's a brain that feeds itself, so the work gets sharper every cycle instead of starting over Bookmark this

Yarchi

58,186 Aufrufe • vor 2 Monaten

Meet Hermes3D A live 3D command center for Hermes Agents Some of you might remember Claw3D It went viral, but it was built around OpenClaw. After moving all my workflows to Hermes, continuing to build it no longer made sense So I rebuilt the entire idea for Hermes Hermes Bot Mode already gives every agent its own role, model, memory, skills, tools, and personality. Hermes3D gives that team an office See which agents are working See who is blocked Inspect their tasks Open the Kanban board Walk up and talk to them And when agents communicate, delegate work, or hand tasks to each other, you will be able to watch it happen inside the office in real time Your AI team should not feel like ten invisible processes hiding inside terminal tabs. It should feel like a workplace you can actually see and control. Claw3D was the prototype Hermes3D is the real vision And of course, it is Open Source Demo below. Repo link in the first comment

Meet Hermes3D A live 3D command center for Hermes Agents Some of you might remember Claw3D It went viral, but it was built around OpenClaw. After moving all my workflows to Hermes, continuing to build it no longer made sense So I rebuilt the entire idea for Hermes Hermes Bot Mode already gives every agent its own role, model, memory, skills, tools, and personality. Hermes3D gives that team an office See which agents are working See who is blocked Inspect their tasks Open the Kanban board Walk up and talk to them And when agents communicate, delegate work, or hand tasks to each other, you will be able to watch it happen inside the office in real time Your AI team should not feel like ten invisible processes hiding inside terminal tabs. It should feel like a workplace you can actually see and control. Claw3D was the prototype Hermes3D is the real vision And of course, it is Open Source Demo below. Repo link in the first comment

Luke The Dev

35,520 Aufrufe • vor 2 Tagen

HERMES AGENT HAS 5 SYSTEMS RUNNING UNDER THE HOOD. UNDERSTAND THEM AND YOU USE THE AGENT 10X BETTER. In this video Alejandro AO 🤗 explained: 1. THE AGENT LOOP every message triggers the same cycle: → you send a message → Hermes builds context (SOUL.md + memory.md + user.md + skills + tools + message history) → sends everything to the LLM → LLM decides: call a tool or respond → if tool call: execute, return result, loop back → if response: deliver to you → after response: memory update (agent checks if anything is worth remembering, writes to memory.md or user.md) this loop is why Hermes gets better over time. the memory update after every response means the agent learns from every conversation. 2. CONTEXT ASSEMBLY what the LLM sees on every turn: → SOUL.md (your agent's personality and rules) → memory.md (facts the agent learned over time) → user.md (facts about you, auto-updated) → AGENTS.md and .hermes.md (project context files) → skill descriptions (loaded on demand) → tool schemas (available actions) → message history (current conversation) if SOUL.md is empty, Hermes falls back to a default system prompt. write your own SOUL.md and the agent becomes yours, not generic. CONTEXT COMPRESSION: conversations hit context limits. Hermes handles this at two checkpoints: preflight: before each turn. if conversation exceeds 50% of context window, compression fires. older messages get summarized. last 20 messages stay intact (protect_last_n). gateway auto-compression: between turns. fires at 85%. more aggressive. prevents API errors before the agent even starts processing your message. after compression, a new session lineage ID is generated. the agent can trace back to the original conversation through SQLite. three things break prompt cache: switching models mid-session, changing memory files, or changing context files. 3. THE GATEWAY the system that keeps Hermes reachable on 27+ messaging platforms. an async loop runs continuously. listens for incoming messages from Telegram, Discord, Slack, WhatsApp, email, SMS, and every other adapter. when a message arrives: → gateway identifies which session it belongs to → queries SQLite for the full message history (session ID = platform prefix + chat ID) → builds the context from scratch → sends everything into the agent loop → delivers the response back to the platform the gateway also runs the session manager. when you send a message while the agent is busy: → default: queued for next turn → /steer: injected without interrupting → /interrupt: stops current work without the gateway, Hermes is a CLI tool. with the gateway, Hermes is an always-on agent you reach from your phone. 4. MEMORY (THREE LAYERS) LAYER 1 — MARKDOWN FILES SOUL.md (identity), memory.md (learned facts), user.md (facts about you). injected into context after the system prompt. updated by the agent after every response. LAYER 2 — SQLITE full transcripts of every session stored locally. FTS5 full-text search across all past conversations. session lineage tracking across compressions. the agent can recall what you discussed weeks ago using /recall or session search. LAYER 3 — EXTERNAL PROVIDERS (optional) 8 supported providers: Mem0, SuperMemory, Honcho, Zep, and more. each works differently (semantic search, LLM extraction, similarity matching). queried after the first message in each session. the agent processes your topic first, then checks external memory for related context from past conversations. not enabled by default. enable for significantly better long-term recall. 5. CRON ENGINE a loop inside the gateway ticks every 60 seconds. each tick checks ~/.hermes/cron/jobs.json for scheduled tasks. if a job is due: → fresh session (no chat history, no memory pollution) → execute the prompt with assigned tools → store the run output as markdown in ~/.hermes/cron/output/[job-id]/ → deliver result to your home messaging platform cron does NOT use the send_message tool. delivery happens at the system level, not the agent level. a cron session cannot create more cron jobs. prevents runaway loops. WHY THIS MATTERS: the agent loop teaches it. the context assembly focuses it. the gateway reaches it. the memory remembers it. the cron engine automates it. five systems. one agent. understanding how they connect changes how you configure every level. full 15 levels breakdown in the article 👇

HERMES AGENT HAS 5 SYSTEMS RUNNING UNDER THE HOOD. UNDERSTAND THEM AND YOU USE THE AGENT 10X BETTER. In this video Alejandro AO 🤗 explained: 1. THE AGENT LOOP every message triggers the same cycle: → you send a message → Hermes builds context (SOUL.md + memory.md + user.md + skills + tools + message history) → sends everything to the LLM → LLM decides: call a tool or respond → if tool call: execute, return result, loop back → if response: deliver to you → after response: memory update (agent checks if anything is worth remembering, writes to memory.md or user.md) this loop is why Hermes gets better over time. the memory update after every response means the agent learns from every conversation. 2. CONTEXT ASSEMBLY what the LLM sees on every turn: → SOUL.md (your agent's personality and rules) → memory.md (facts the agent learned over time) → user.md (facts about you, auto-updated) → AGENTS.md and .hermes.md (project context files) → skill descriptions (loaded on demand) → tool schemas (available actions) → message history (current conversation) if SOUL.md is empty, Hermes falls back to a default system prompt. write your own SOUL.md and the agent becomes yours, not generic. CONTEXT COMPRESSION: conversations hit context limits. Hermes handles this at two checkpoints: preflight: before each turn. if conversation exceeds 50% of context window, compression fires. older messages get summarized. last 20 messages stay intact (protect_last_n). gateway auto-compression: between turns. fires at 85%. more aggressive. prevents API errors before the agent even starts processing your message. after compression, a new session lineage ID is generated. the agent can trace back to the original conversation through SQLite. three things break prompt cache: switching models mid-session, changing memory files, or changing context files. 3. THE GATEWAY the system that keeps Hermes reachable on 27+ messaging platforms. an async loop runs continuously. listens for incoming messages from Telegram, Discord, Slack, WhatsApp, email, SMS, and every other adapter. when a message arrives: → gateway identifies which session it belongs to → queries SQLite for the full message history (session ID = platform prefix + chat ID) → builds the context from scratch → sends everything into the agent loop → delivers the response back to the platform the gateway also runs the session manager. when you send a message while the agent is busy: → default: queued for next turn → /steer: injected without interrupting → /interrupt: stops current work without the gateway, Hermes is a CLI tool. with the gateway, Hermes is an always-on agent you reach from your phone. 4. MEMORY (THREE LAYERS) LAYER 1 — MARKDOWN FILES SOUL.md (identity), memory.md (learned facts), user.md (facts about you). injected into context after the system prompt. updated by the agent after every response. LAYER 2 — SQLITE full transcripts of every session stored locally. FTS5 full-text search across all past conversations. session lineage tracking across compressions. the agent can recall what you discussed weeks ago using /recall or session search. LAYER 3 — EXTERNAL PROVIDERS (optional) 8 supported providers: Mem0, SuperMemory, Honcho, Zep, and more. each works differently (semantic search, LLM extraction, similarity matching). queried after the first message in each session. the agent processes your topic first, then checks external memory for related context from past conversations. not enabled by default. enable for significantly better long-term recall. 5. CRON ENGINE a loop inside the gateway ticks every 60 seconds. each tick checks ~/.hermes/cron/jobs.json for scheduled tasks. if a job is due: → fresh session (no chat history, no memory pollution) → execute the prompt with assigned tools → store the run output as markdown in ~/.hermes/cron/output/[job-id]/ → deliver result to your home messaging platform cron does NOT use the send_message tool. delivery happens at the system level, not the agent level. a cron session cannot create more cron jobs. prevents runaway loops. WHY THIS MATTERS: the agent loop teaches it. the context assembly focuses it. the gateway reaches it. the memory remembers it. the cron engine automates it. five systems. one agent. understanding how they connect changes how you configure every level. full 15 levels breakdown in the article 👇

YanXbt

51,670 Aufrufe • vor 2 Monaten

$HERMES AGENT RUNS MONITORING, RESEARCH, LEAD DETECTION, AND COMPETITIVE ANALYSIS ON AUTOPILOT. AND KNOWS WHEN NOT TO SPEND YOUR TOKENS. the biggest unlock most people skip: Hermes cron jobs can decide ON THEIR OWN whether the LLM should wake up. WAKE AGENT — THE $0 GATE every cron job can run a Python script first. the script checks: did anything actually change? nothing changed: → script outputs {"wakeAgent": false} → LLM stays asleep → zero tokens spent something changed: → script outputs {"wakeAgent": true} → agent wakes up and handles it three gate patterns from official docs: → file-change: compare file mtime to last run. no change? sleep. → external-flag: another process drops a ready file. no flag? sleep. → HTTP-check: ping a URL, diff the response. same as last time? sleep. real example: monitor AWS costs every hour. script pulls current spend from AWS API. no spike? agent sleeps. zero cost. costs jump 40%? agent wakes, reports to Slack, takes action through Stripe MCP. you run 20 monitoring jobs a day. 18 of them find nothing. you pay for 2. NO AGENT — PURE SCRIPT, ZERO LLM some jobs don't need reasoning at all. TLS checks. uptime pings. disk alerts. heartbeats. hermes cron edit --no-agent --script check_health.py script runs. stdout goes straight to Telegram, Discord, or Slack. no LLM involved. flip any job between modes: hermes cron edit --agent # add LLM hermes cron edit --no-agent # remove LLM free monitoring that lives inside the same ecosystem as your agent. 4 MORE USE CASES THIS UNLOCKS: COMPETITIVE ANALYSIS weekly cron with script that diffs competitor pages. agent only analyzes actual changes. updates your tracking file and PRD skill automatically. PRD AS A SKILL save product requirements as a skill, not a document. skills load on demand into fresh context. documents drift. skills stay sharp. CONTENT REPURPOSING hand a video script to the agent. it drafts X and LinkedIn posts in your voice. writes to a review folder. you approve via Telegram. LEAD DETECTION webhook monitors inbox. agent spots potential leads. drafts responses using your business context. schedules meetings from your calendar. the pattern across all of these: scripts handle the mechanical work for free. the agent only spends tokens on reasoning that requires judgment. comment CRON and I'll send you 5 ready-to-paste cron configs with wakeAgent and no_agent patterns. full Hermes SOUL.MD guide 👇$

HERMES AGENT RUNS MONITORING, RESEARCH, LEAD DETECTION, AND COMPETITIVE ANALYSIS ON AUTOPILOT. AND KNOWS WHEN NOT TO SPEND YOUR TOKENS. the biggest unlock most people skip: Hermes cron jobs can decide ON THEIR OWN whether the LLM should wake up. WAKE AGENT — THE $0 GATE every cron job can run a Python script first. the script checks: did anything actually change? nothing changed: → script outputs {"wakeAgent": false} → LLM stays asleep → zero tokens spent something changed: → script outputs {"wakeAgent": true} → agent wakes up and handles it three gate patterns from official docs: → file-change: compare file mtime to last run. no change? sleep. → external-flag: another process drops a ready file. no flag? sleep. → HTTP-check: ping a URL, diff the response. same as last time? sleep. real example: monitor AWS costs every hour. script pulls current spend from AWS API. no spike? agent sleeps. zero cost. costs jump 40%? agent wakes, reports to Slack, takes action through Stripe MCP. you run 20 monitoring jobs a day. 18 of them find nothing. you pay for 2. NO AGENT — PURE SCRIPT, ZERO LLM some jobs don't need reasoning at all. TLS checks. uptime pings. disk alerts. heartbeats. hermes cron edit --no-agent --script check_health.py script runs. stdout goes straight to Telegram, Discord, or Slack. no LLM involved. flip any job between modes: hermes cron edit --agent # add LLM hermes cron edit --no-agent # remove LLM free monitoring that lives inside the same ecosystem as your agent. 4 MORE USE CASES THIS UNLOCKS: COMPETITIVE ANALYSIS weekly cron with script that diffs competitor pages. agent only analyzes actual changes. updates your tracking file and PRD skill automatically. PRD AS A SKILL save product requirements as a skill, not a document. skills load on demand into fresh context. documents drift. skills stay sharp. CONTENT REPURPOSING hand a video script to the agent. it drafts X and LinkedIn posts in your voice. writes to a review folder. you approve via Telegram. LEAD DETECTION webhook monitors inbox. agent spots potential leads. drafts responses using your business context. schedules meetings from your calendar. the pattern across all of these: scripts handle the mechanical work for free. the agent only spends tokens on reasoning that requires judgment. comment CRON and I'll send you 5 ready-to-paste cron configs with wakeAgent and no_agent patterns. full Hermes SOUL.MD guide 👇

YanXbt

95,946 Aufrufe • vor 2 Monaten

Bradley Cooper says he was ready to quit acting before The Hangover changed his career “I was going to quit. I remember I was doing a play, and I was like, ‘It's just not happening.’ I really wanted to be an actor. I loved it so much. I was making a living, which was a miracle. For the first three years, I was like, ‘This is amazing.’ Then I was like I just want to be three days on a movie, then you’re not, and then you're gone” “I wasn't really getting any other roles that were substantial. I met with Todd Phillips six months before for The Hangover, and then it was gone. The truth is, I think they had a cast, but the budget was too high. They said if you make it with a smaller budget, we'll do the movie” “Then I was doing a play in Williamstown called The Understudy by Theresa Rebeck. I remember I got an email from Todd Phillips, and I was like, ‘Whoa, how'd he get my email?’ He was like, ‘Let's do this, bitches’” “Then we went from there and started shooting. We went to Vegas that fall. I never would have gotten Limitless if I wasn't part of The Hangover. That changed everything”

Bradley Cooper says he was ready to quit acting before The Hangover changed his career “I was going to quit. I remember I was doing a play, and I was like, ‘It's just not happening.’ I really wanted to be an actor. I loved it so much. I was making a living, which was a miracle. For the first three years, I was like, ‘This is amazing.’ Then I was like I just want to be three days on a movie, then you’re not, and then you're gone” “I wasn't really getting any other roles that were substantial. I met with Todd Phillips six months before for The Hangover, and then it was gone. The truth is, I think they had a cast, but the budget was too high. They said if you make it with a smaller budget, we'll do the movie” “Then I was doing a play in Williamstown called The Understudy by Theresa Rebeck. I remember I got an email from Todd Phillips, and I was like, ‘Whoa, how'd he get my email?’ He was like, ‘Let's do this, bitches’” “Then we went from there and started shooting. We went to Vegas that fall. I never would have gotten Limitless if I wasn't part of The Hangover. That changed everything”

dank

323,138 Aufrufe • vor 1 Monat

I have been seeing this video for days and tried to not comment on it but my guy here has a following and was on Richie’s podcast as well. First of all, none of what he said is true and it is verifiable By the context he presented it, it is fair to say the NLM was not necessarily ‘Asantes’ even though the party was set up by Baffour Osei Akoto who was the Asantehene’s Okyeame and some Asante chiefs and prominent men. The NLM (or Asantes) were asking for federal system because they felt a central government could mess up the riches/resources in their territory. You have to remember they were the leading producers of cocoa in the Gold Coast at the time…together with the Eastern territory. They also feared a central government could become authoritarian and take ‘rogue’ decisions (which eventually happened). The northern (region) supported this also for their own reasons and there prominent people from other tribes that supported it too… It had nothing to do with regions. How would not getting a region (that was essentially existent by then) be a problem for independence anyway?…Makes no sense, no correlation whatsoever

I have been seeing this video for days and tried to not comment on it but my guy here has a following and was on Richie’s podcast as well. First of all, none of what he said is true and it is verifiable By the context he presented it, it is fair to say the NLM was not necessarily ‘Asantes’ even though the party was set up by Baffour Osei Akoto who was the Asantehene’s Okyeame and some Asante chiefs and prominent men. The NLM (or Asantes) were asking for federal system because they felt a central government could mess up the riches/resources in their territory. You have to remember they were the leading producers of cocoa in the Gold Coast at the time…together with the Eastern territory. They also feared a central government could become authoritarian and take ‘rogue’ decisions (which eventually happened). The northern (region) supported this also for their own reasons and there prominent people from other tribes that supported it too… It had nothing to do with regions. How would not getting a region (that was essentially existent by then) be a problem for independence anyway?…Makes no sense, no correlation whatsoever

CHIEF

107,873 Aufrufe • vor 6 Monaten