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Kimi track - First place: JumpFoundry by Ev A Hermes Agent plugin where the designer hand-draws one or two glyphs and Hermes Agent generates the rest, acting as coordinator that routes per-glyph revisions through parallel model calls before exporting an editable TTF.

Nous Research

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45,447 次观看 • 3 个月前 •via X (Twitter)

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China just made Hermes free forever 🚀 You can now run Hermes with Kimi K 2.6 through Ollama in one click. Just install the model, launch Hermes, select Kimi K 2.6 and suddenly you have a powerful AI agent running locally with zero API fees. This might be the easiest free Hermes setup yet.

China just made Hermes free forever 🚀 You can now run Hermes with Kimi K 2.6 through Ollama in one click. Just install the model, launch Hermes, select Kimi K 2.6 and suddenly you have a powerful AI agent running locally with zero API fees. This might be the easiest free Hermes setup yet.

Julian Goldie SEO

138,673 次观看 • 4 个月前

$Hermes agent doesn't need a frontier model to run your computer well. Kimi K2.6 or Qwen 3.6 can do the same job at a fraction of the cost, and both are available fully private through the Venice API. 🧵 Here's the full Hermes "computer_use" setup:$

Hermes agent doesn't need a frontier model to run your computer well. Kimi K2.6 or Qwen 3.6 can do the same job at a fraction of the cost, and both are available fully private through the Venice API. 🧵 Here's the full Hermes "computer_use" setup:

Venice

25,636 次观看 • 3 个月前

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 👇

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 👇

YanXbt

29,819 次观看 • 2 个月前

New in Hermes Agent: pull secrets from multiple vaults at once. Run Bitwarden and newly added vault provider 1Password side by side, or add any other secret source as a plugin with the new vault plugin API.

New in Hermes Agent: pull secrets from multiple vaults at once. Run Bitwarden and newly added vault provider 1Password side by side, or add any other secret source as a plugin with the new vault plugin API.

Nous Research

197,620 次观看 • 1 个月前

I built Caduceus for Hermes Desktop Nous Research Two snakes, one staff Caduceus runs parallel AI agents in perfect sync, on any model you already have It sizes up every task and picks the path: • Easy → answered instantly • Hard → a live to-do plan + agents fanned out in parallel, verified before it calls it done Caduceus has a UI right inside Hermes so you watch every agent build your project in real time Full demo 👇

I built Caduceus for Hermes Desktop Nous Research Two snakes, one staff Caduceus runs parallel AI agents in perfect sync, on any model you already have It sizes up every task and picks the path: • Easy → answered instantly • Hard → a live to-do plan + agents fanned out in parallel, verified before it calls it done Caduceus has a UI right inside Hermes so you watch every agent build your project in real time Full demo 👇

Terp

17,006 次观看 • 3 个月前

HERMES AGENT: 5 USEFUL COMMUNITY PLUGINS RIGHT NOW Hermes already ships with strong core features — Skills, MCP, Memory, Curator, and a plugin system. These extensions don’t replace anything in the core. They fill practical gaps. Here are the ones worth installing: 1. hermes-plugins by 42-evey Solid collection. Adds goal management, inter-agent communication, cost tracking, and easier model switching. Good for running Hermes autonomously. 2. web-search-plus Much stronger web search than the default. Supports multiple providers, smart routing, quality scoring, and a proper research mode. 3. super-hermes by Cranot Adds “Prisms” — structured analytical frameworks. Makes the agent noticeably better at deep analysis and catching its own blind spots. 4. Hermes Agent Self-Evolution (by Nous Research) Official companion that automatically improves skills and prompts using DSPy + GEPA. Useful if you want the agent to get better over time with minimal manual work. 5. Advanced Memory Providers When built-in memory isn’t enough for long projects, external providers give Hermes stronger long-term recall and context handling. All of these work cleanly on top of Hermes v0.16.0 without conflicting with core systems. Which plugins or extensions are you actually using with Hermes right now? Github links 👇

HERMES AGENT: 5 USEFUL COMMUNITY PLUGINS RIGHT NOW Hermes already ships with strong core features — Skills, MCP, Memory, Curator, and a plugin system. These extensions don’t replace anything in the core. They fill practical gaps. Here are the ones worth installing: 1. hermes-plugins by 42-evey Solid collection. Adds goal management, inter-agent communication, cost tracking, and easier model switching. Good for running Hermes autonomously. 2. web-search-plus Much stronger web search than the default. Supports multiple providers, smart routing, quality scoring, and a proper research mode. 3. super-hermes by Cranot Adds “Prisms” — structured analytical frameworks. Makes the agent noticeably better at deep analysis and catching its own blind spots. 4. Hermes Agent Self-Evolution (by Nous Research) Official companion that automatically improves skills and prompts using DSPy + GEPA. Useful if you want the agent to get better over time with minimal manual work. 5. Advanced Memory Providers When built-in memory isn’t enough for long projects, external providers give Hermes stronger long-term recall and context handling. All of these work cleanly on top of Hermes v0.16.0 without conflicting with core systems. Which plugins or extensions are you actually using with Hermes right now? Github links 👇

YanXbt

34,564 次观看 • 2 个月前

Second place: Ambien by give me a sec A daydreaming agent running inside Hermes Agent that samples a curated Obsidian corpus for resonant idea collisions and synthesizes them into published essays, leveraging the harness for iterative voice calibration that keeps the prose from reading like an LLM.

Second place: Ambien by give me a sec A daydreaming agent running inside Hermes Agent that samples a curated Obsidian corpus for resonant idea collisions and synthesizes them into published essays, leveraging the harness for iterative voice calibration that keeps the prose from reading like an LLM.

Nous Research

26,904 次观看 • 3 个月前

$a regular laptop with just 8GB VRAM can now run a LOCAL AI AGENT directly on your device what you need: 1/ 8 GB VRAM 2/ 16 GB RAM 3/ $600+ laptop method: Kimi K2 + Hermes Agent Dekstop App what agent can do: 1/ read and write files 2/ patch code, open PRs on GitHub 3/ browse the web like a human 4/ work with Notion 5/ run scripts, debug, refactor this isn't 'ask a question, get an answer.' this is an agent that drives a task from start to finish on its own. before: local agent = either the cloud and $$$, or an RTX now: any gaming laptop from the last 3 years p.s. MoE is the key. Kimi K2 activates only a fraction of its params per token - that's why a 1T-param model runs on hardware where a dense 26B would already be choking did you try Hermes Dekstop?$

a regular laptop with just 8GB VRAM can now run a LOCAL AI AGENT directly on your device what you need: 1/ 8 GB VRAM 2/ 16 GB RAM 3/ $600+ laptop method: Kimi K2 + Hermes Agent Dekstop App what agent can do: 1/ read and write files 2/ patch code, open PRs on GitHub 3/ browse the web like a human 4/ work with Notion 5/ run scripts, debug, refactor this isn't 'ask a question, get an answer.' this is an agent that drives a task from start to finish on its own. before: local agent = either the cloud and $$$, or an RTX now: any gaming laptop from the last 3 years p.s. MoE is the key. Kimi K2 activates only a fraction of its params per token - that's why a 1T-param model runs on hardware where a dense 26B would already be choking did you try Hermes Dekstop?

kaize

58,760 次观看 • 2 个月前

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 次观看 • 2 个月前

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 次观看 • 2 个月前

OpenClaw and Hermes agent are INCREDIBLE together It's not about using one or the other. It's about learning how to use them as an AI agent team In this video I go over the strengths and weaknesses of each, plus show you 4 workflows that will skyrocket your productivity:

OpenClaw and Hermes agent are INCREDIBLE together It's not about using one or the other. It's about learning how to use them as an AI agent team In this video I go over the strengths and weaknesses of each, plus show you 4 workflows that will skyrocket your productivity:

Alex Finn

120,551 次观看 • 4 个月前

HERMES AGENT VS OPENCLAW. a local ai onboarding flow test. a 3.9gb bonsai served on localhost, both agents upstream and latest, i point each one at the endpoint and watch which one even finds it. > hermes opens a provider menu, thirty plus options, local servers sitting right there next to the cloud ones, i hand it 127.0.0.1:8899, it verifies the endpoint, one model visible, auto-detects the model by name, bonsai-27b-q1_0, reads the context length straight off the server, saves it, and starts reasoning and firing real tool calls on my local model. no key. no friction. > openclaw has no menu. it goes hunting for a codex login, an openai key, finds none because there are none, prints no models available three times, defaults to openai/gpt-5.5, a cloud model it cannot reach, and dead ends on run auth login --provider openai. read that back. it asked me for an openai key. to run a model already running on my own machine. it never once looked at localhost. to be fair, openclaw can run local if you hand wire endpoint yourself. what it will not do is find the model already sitting on your box. hermes agent found it in one line. now the part i owe you. the auto-detect that just won, the model name read, the .gguf strip, the context length probe off the server, that is my code, it is in hermes agent main right now, authorship preserved, #2051 and #4218. the wizard fix that stops an agent from silently routing you to someone else's creds, the exact trap openclaw still falls into, mine too, #4210. i contribute to hermes agent, i told you that going in. one agent is built to talk to whatever you are running, the other is built to talk to a cloud api, so one found my model and ran it and the other asked me to log into openai. onboarding flow of both, mapped, below.

HERMES AGENT VS OPENCLAW. a local ai onboarding flow test. a 3.9gb bonsai served on localhost, both agents upstream and latest, i point each one at the endpoint and watch which one even finds it. > hermes opens a provider menu, thirty plus options, local servers sitting right there next to the cloud ones, i hand it 127.0.0.1:8899, it verifies the endpoint, one model visible, auto-detects the model by name, bonsai-27b-q1_0, reads the context length straight off the server, saves it, and starts reasoning and firing real tool calls on my local model. no key. no friction. > openclaw has no menu. it goes hunting for a codex login, an openai key, finds none because there are none, prints no models available three times, defaults to openai/gpt-5.5, a cloud model it cannot reach, and dead ends on run auth login --provider openai. read that back. it asked me for an openai key. to run a model already running on my own machine. it never once looked at localhost. to be fair, openclaw can run local if you hand wire endpoint yourself. what it will not do is find the model already sitting on your box. hermes agent found it in one line. now the part i owe you. the auto-detect that just won, the model name read, the .gguf strip, the context length probe off the server, that is my code, it is in hermes agent main right now, authorship preserved, #2051 and #4218. the wizard fix that stops an agent from silently routing you to someone else's creds, the exact trap openclaw still falls into, mine too, #4210. i contribute to hermes agent, i told you that going in. one agent is built to talk to whatever you are running, the other is built to talk to a cloud api, so one found my model and ran it and the other asked me to log into openai. onboarding flow of both, mapped, below.

Sudo su

23,816 次观看 • 1 个月前

Hermes keeps finding ways to make agent work cost fewer tokens. And the latest cuts are automatic. Recent changes reduced recurring context overhead across several parts of Hermes: • Desktop’s model-facing UI tool schema dropped 41% • Memory and Skills guidance went from 537 to 255 tokens • Desktop’s always-served guidance was trimmed again • roughly another 727 tokens were removed from recurring platform and steering instructions That matters whether you use Hermes for coding, research, content, automations, business workflows, or long-running agent tasks. Every token spent explaining tools, Skills, memory, or platform behavior is context that isn’t being spent on your actual work. Hermes was already notably lean here. Composio recently put that to the test using the same K3 model across competing agent harnesses. Hermes came out among the strongest on completion while also posting the lowest average cost per task in their comparison. And the Hermes team clearly isn’t treating that as good enough. They continue cutting token waste across tools, Skills, memory, platform instructions, compression, and other parts of the agentic process. The goal is simple: more of your context goes toward the work you actually asked Hermes to do. Clip via Tom

Hermes keeps finding ways to make agent work cost fewer tokens. And the latest cuts are automatic. Recent changes reduced recurring context overhead across several parts of Hermes: • Desktop’s model-facing UI tool schema dropped 41% • Memory and Skills guidance went from 537 to 255 tokens • Desktop’s always-served guidance was trimmed again • roughly another 727 tokens were removed from recurring platform and steering instructions That matters whether you use Hermes for coding, research, content, automations, business workflows, or long-running agent tasks. Every token spent explaining tools, Skills, memory, or platform behavior is context that isn’t being spent on your actual work. Hermes was already notably lean here. Composio recently put that to the test using the same K3 model across competing agent harnesses. Hermes came out among the strongest on completion while also posting the lowest average cost per task in their comparison. And the Hermes team clearly isn’t treating that as good enough. They continue cutting token waste across tools, Skills, memory, platform instructions, compression, and other parts of the agentic process. The goal is simple: more of your context goes toward the work you actually asked Hermes to do. Clip via Tom

Hermes Release Watch

19,276 次观看 • 2 天前

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 次观看 • 2 个月前

small local model that falls apart in bloated agents like openclaw just runs like a wild horse in hermes agent. and that's not even my line, someone else called it that, i've just been quietly pointing people at this harness for months because it held up on everything i threw at it, 3b models all the way to one trillion params. watch this happen on my own machine. i pointed hermes agent at a local http endpoint, gemma 4 12b on my 3090 llama.cpp server, and it auto-detected the model and started working immediately. no config wrestling, no broken tool calls, no babysitting the output format, i typed in a url and it just went. the whole clip is exactly that, start to finish, no errors, no retries, butter smooth. and the tool calling, the one thing that quietly breaks most local setups, works here like it's nothing. it's not the model that's flaky, it's the harness around it. hermes agent is the first agent i've run that actually gets that right. one url, one local model on one card, and it runs like a wild horse.

small local model that falls apart in bloated agents like openclaw just runs like a wild horse in hermes agent. and that's not even my line, someone else called it that, i've just been quietly pointing people at this harness for months because it held up on everything i threw at it, 3b models all the way to one trillion params. watch this happen on my own machine. i pointed hermes agent at a local http endpoint, gemma 4 12b on my 3090 llama.cpp server, and it auto-detected the model and started working immediately. no config wrestling, no broken tool calls, no babysitting the output format, i typed in a url and it just went. the whole clip is exactly that, start to finish, no errors, no retries, butter smooth. and the tool calling, the one thing that quietly breaks most local setups, works here like it's nothing. it's not the model that's flaky, it's the harness around it. hermes agent is the first agent i've run that actually gets that right. one url, one local model on one card, and it runs like a wild horse.

Sudo su

27,339 次观看 • 2 个月前

A lot of people are calling Hermes Agent the end of OpenClaw. BRUH! It's not... Nous Research trains actual models and they built an agent around that expertise. The local model routing is solid, but the part that matters for your business is that your conversations become fine-tuning data. You can train a model on how you actually work. 00:00 The Problem with Local AI Models 00:25 Introduction to Nous Research 01:04 Cross-Platform Agent Capabilities 01:44 Deep Local Model Integration 02:30 Routing Tasks to Different Models 03:06 Conversations as Training Data 03:50 Hermes Agent vs. OpenClaw 04:15 Future Plans and Series Overview

A lot of people are calling Hermes Agent the end of OpenClaw. BRUH! It's not... Nous Research trains actual models and they built an agent around that expertise. The local model routing is solid, but the part that matters for your business is that your conversations become fine-tuning data. You can train a model on how you actually work. 00:00 The Problem with Local AI Models 00:25 Introduction to Nous Research 01:04 Cross-Platform Agent Capabilities 01:44 Deep Local Model Integration 02:30 Routing Tasks to Different Models 03:06 Conversations as Training Data 03:50 Hermes Agent vs. OpenClaw 04:15 Future Plans and Series Overview

Ray Fernando

42,398 次观看 • 5 个月前

🔊 SOUND ON: Introducing: Suno CLI/Claude Code Skill/OpenClaw🦞 and Hermes skill from the Printing Press 🥁🖨️ •Suno has no API. Your agent doesn't care - make songs from Claude Code, Codex, Nous Research Hermes, OpenClaw, or your workflows •One prompt -> two takes back -> winner picked and shipped as mp3 + cover + lyrics + json in one command •2,000-clip library synced to local SQLite, searchable offline •Budget caps that actually refuse before your agent burns your credits •Much more 🔊 "AI vs Human Beatbox Battle" by Neon Sardine Orchestra:

🔊 SOUND ON: Introducing: Suno CLI/Claude Code Skill/OpenClaw🦞 and Hermes skill from the Printing Press 🥁🖨️ •Suno has no API. Your agent doesn't care - make songs from Claude Code, Codex, Nous Research Hermes, OpenClaw, or your workflows •One prompt -> two takes back -> winner picked and shipped as mp3 + cover + lyrics + json in one command •2,000-clip library synced to local SQLite, searchable offline •Budget caps that actually refuse before your agent burns your credits •Much more 🔊 "AI vs Human Beatbox Battle" by Neon Sardine Orchestra:

Matt Van Horn

18,020 次观看 • 2 个月前

IF YOU HAVE BEEN HOLDING OFF ON HERMES AGENT BECAUSE OF API COSTS, READ THIS FIRST. Four real ways to run it for free. Local, through Ollama, complete privacy and no rate limits. Cloud, through free tiers from Groq, OpenRouter, or NVIDIA NIM, no card required. A subscription you already have, GitHub Copilot connects natively. A fallback configuration so a rate limit on one provider does not stop your whole session. Hermes Agent is free and open source. Now there is no excuse on the model side either. Bookmark this. Follow CyrilXBT

IF YOU HAVE BEEN HOLDING OFF ON HERMES AGENT BECAUSE OF API COSTS, READ THIS FIRST. Four real ways to run it for free. Local, through Ollama, complete privacy and no rate limits. Cloud, through free tiers from Groq, OpenRouter, or NVIDIA NIM, no card required. A subscription you already have, GitHub Copilot connects natively. A fallback configuration so a rate limit on one provider does not stop your whole session. Hermes Agent is free and open source. Now there is no excuse on the model side either. Bookmark this. Follow CyrilXBT

CyrilXBT

28,802 次观看 • 2 个月前

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 次观看 • 3 个月前

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

80,822 次观看 • 2 个月前