Hermes meets SuperGrok! xAI just made every SuperGrok subscription... work inside Hermes Agent. One browser login, no API key, no separate billing. And it doesn't just unlock text chat with Grok 4.3. The same OAuth token gives the agent access to: → Grok Text-to-Speech for spoken responses → Grok Imagine for image and video generation → x_search for real-time X/Twitter search I just added a new X Research Agent profile to my Hermes. Now my agent watches X while I ship. Setup takes about 60 seconds: Available on every SuperGrok tier, no restrictions. I wrote a full deep dive covering Hermes agent's architecture, memory system, self-evolving skills, GEPA optimization, and setting up multiple specialized agents The article is quoted below.show more

This is bigger than YOU think. Hermes Agent now... works with xAI Grok Subscription. I just added a new X Research Agent profile to my Hermes. Now my agent watches X while I ship.show more

I found this last night and I have not... stopped thinking about it. HERMES JUST LAUNCHED HERMES DESKTOP. 100% FREE. It is a free desktop app that gives Hermes Agent a proper interface. One place for everything. What is inside: ↳ Auto install and setup, no terminal needed ↳ Streaming chat with token tracking ↳ Multiple agent profiles ↳ Memory you can actually see and edit ↳ 14 tool categories including web, browser, image gen, and voice ↳ Scheduler for automated tasks ↳ 16 messaging gateways including Telegram, WhatsApp, Discord, Slack, and Signal ↳ Full conversation history with search ↳ Backups and logs in one settings screen Works with Anthropic, OpenAI, Gemini, Grok, Groq, Ollama, and more. Hermes Agent is the brain. Hermes Desktop is the cockpit. Free. Open source. Mac, Windows, and Linux.show more

I built a 1-click deploy for Hermes Agent No... terminal, no Docker, no API keys. In one click it: → Spins up a dedicated cloud container → Configures Hermes with persistent memory & 70+ skills → Connects it to your Telegram bot → Goes live in under 60 seconds Your own AI agent that learns, creates skills, and gets smarter the longer it runs. Reply "HERMES" + RT and I'll send you the link (must be following so I can DM)show more

Grok Build can finally listen to you ramble. Speech-to-Text... is now live. Hit /voice or Ctrl + Space and just talk to your coding agent for up to 15 minutes!! Brainstorm. Explain the weird bug. Describe the change. Change your mind halfway through. Add “one more thing” six times. Grok transcribes it in real time and gets to work. Great news for people whose best ideas arrive before their fingers catch up. Grok xAI X Freeze / Writer: Annette, Designer: Jannéshow more

Two Hermes agents wrote code together on Slack. reviewed... each other's work. argued about architecture. one called the other's implementation "scattered." the other pushed back. then i opened Telegram and asked: "what code did you and Daedalus work on?" icarus remembered everything. the websocket broker. the missing methods. the critique. the rewrite. all from a completely different platform. cross-platform persistent memory between two independent agents. work happens on Slack. recall happens on Telegram. the memory carries. the relationship carries. the context carries. no vector database. no Redis. no infrastructure. just two agents that actually remember what they built together. every agent framework in 2026 talks about memory. single agent memory across sessions. but two agents sharing persistent memory across platforms? that's the gap. arxiv published a paper about it two weeks ago calling it "the most pressing open challenge" in multi-agent systems. it works now. only possible with Hermes Teknium 🪽 Nous Researchshow more

SpaceXai just made grok 4.5 FREE in your coding... agent starting today it's xAI's new coding model. 500k context. built for long agent sessions. no card. what you get for $0: -83.3% on terminal-bench 2.1 -64.7% on swe-bench pro - 4.2x more efficient than Opus 4.8 -500k context for big repos -$2/M in, $6/M out once it goes paid what this replaces: -Claude Opus 4.8: $15/M in, $75/M out -SuperGrok: $30-50/mo all for $0 how to set it up (2 min): >curl -fsSL | bash > grok → localhost:8000/v1 > point hermes / aider / opencode / cline to it > model: grok-4.5 Or API key at - base url Works in Hermes, Aider, OpenCode, Cline, Claude Code, and any OpenAI-compatible tool. Important: Free for a limited time. EU waits till mid-July. Rate limits apply. bookmark this before the free window closesshow more

I told ClawdBot: "build me a 6-agent system for... Polymarket that works while I sleep"... 6 hours while i was asleep. Not a single question. Here's what it built: Monitoring agent - runs 24/7, watches Polymarket for mispriced markets. Spots an anomaly - writes to MEMORY md and pings me on Telegram instantly. Research agent - parses news, X, macro data via browser tool on a cron schedule. Every morning I have a full digest on all open positions before I even check my phone. Trading agent - reads the research agent's memory through Gateway, sees the market hasn't reacted yet, acts. Exec tool in gateway mode with a whitelist - no full access on a live server. Watchdog - HEARTBEAT md every 5 minutes: monitoring running, no errors, positions up to date. Something breaks - immediate Telegram message. All of this - one Gateway. One config.json. Isolation via dmScope: per-agent. The token trick: stopped dumping everything into AGENTS md. Critical rules - bootstrap. Try copytrade my bot here: Everything about markets, patterns, past trades - MEMORY md, semantic search pulls it when needed. Token spend dropped 3x, from $0.40/request to $0.13. First week running: - 47 mispriced markets caught before Polymarket adjusted - avg entry edge: 8-12¢ per position - watchdog fired 3 times, caught a broken RPC before it cost me anything The whole system is plain .md text files. Open an editor, change one line - agent behaves differently. No deploy. No build. A bot responds. An agent earns.show more

I still think Hermes agent is the most slept-on... AI tool of 2026. For literally $6/mo, you can launch multiple subagents that work for you 24/7. Most people don't know you can do this, but it's a complete game-changer. Instead of one Hermes assistant doing everything sequentially, you run specialized agents in parallel, each with its own job, its own context, and its own memory. Practical example: → Research agent: scans your watchlist and competitors overnight, delivers a morning brief → Content agent: drafts and schedules your posts based on what's trending in your niche → Ops agent: manages your inbox, flags anything urgent, drafts replies for your review All three can run simultaneously and improve over time. How to start: 1. Install Hermes Terminal command: curl -fsSL | bash (can also download desktop) 2. Prompting Simply tell Hermes directly: "I want to run separate subagents for [task 1], [task 2], and [task 3]. Set them up to run independently and report back to me." For the cheapest setup, you can use a $4/month VPS with Hostinger, plug in DeepSeek V4 Flash as your default model. There isn't another AI tool with this much value in 2026. Hermes is still so underrated.show more

OpenClaw is genuinely powerful. But I spent 3 days... just trying to get it running. Then I found PetClaw. One click. No API key. No setup. No debugging. A full AI agent on my desktop in under a minute. And the first thing I tested it on changed how I think about research forever.show more

HERMES AGENT NOW SUPPORTS COMPUTER USE ON WINDOWS AND... LINUX. CLICKS, TYPES, SCROLLS YOUR DESKTOP IN THE BACKGROUND WHILE YOU WORK. computer use was macOS only. now it works on Windows and Linux too via Cua. Nous Research HOW IT WORKS: cua-driver runs as an MCP server. Hermes takes a screenshot with numbered elements. clicks element #14 (the search field). types a query. submits. reads the result. during all of this: → your cursor stays where you left it → keyboard focus doesn't change → windows don't come to front → macOS doesn't switch Spaces you and the agent co-work on the same machine. WHAT IT CAN DO: → find your latest Stripe email and summarize it → fill forms in a web app that has no API → navigate desktop apps (Mail, browser, Finder) → interact with any GUI application → extract data from apps only accessible via screen WORKS WITH ANY VISION MODEL: not locked to Anthropic. | Provider | Works | |---|---| | Claude (Sonnet/Opus) | best overall | | GPT-4+, GPT-5.5 | full support | | Gemini (via OpenRouter) | full support | | Local vLLM / LM Studio | if model supports vision | | Text-only models | degraded (accessibility tree only) | SETUP: hermes computer-use install or: hermes tools → Computer Use → cua-driver grant permissions when prompted: → Accessibility (system settings) → Screen Recording (system settings) start a session: hermes -t computer_use chat or add to config.yaml / Desktop app settings to enable permanently. SAFETY: → destructive actions require your approval → blocked key combos: empty trash, force delete, lock screen, log out → blocked type patterns: curl | bash, sudo rm -rf /, fork bombs → agent cannot click permission dialogs → agent cannot type passwords → agent cannot follow instructions embedded in screenshots pair with approvals.mode: manual if you want every single click confirmed. TOKEN NOTE: screenshots are expensive. each one adds vision tokens to context. use computer_use for tasks where no API exists. if the tool has an API or MCP server, use that instead. 15 levels of Hermes Agent👇show more

THIS DEVELOPER USED OPENCLAW AGENTS TO RUN HIS B2B... BUSINESS VIA TELEGRAM AND MADE $15,000/MONTH he doesn't write prompts from scratch or use generic browser interfaces. he runs a multi-agent framework through a mobile chat. the agents write code, test deployments, and update sites in real-time while he just hits approve the setup is straightforward: - spin up Coolify on a free cloud instance to host your own self-hosted agent panels - link the agent loop to a Telegram gateway to approve code edits from your phone - deploy specialized skill files directly to limit token waste and context decay - containerize the terminal execution using Docker to prevent security breaches if you are still running local agents without container safety, you are leaving money on the table. read the 30-day battle between OpenClaw and Hermes Agent to see who actually wins in production Full breakdown and migration playbook ↓show more

THESE 5 SKILLS TURN HERMES AGENT INTO A SELF-RUNNING... POWERHOUSE - ON NOUS RESEARCH’S #1 AGENT ON OPENROUTER. Hermes already writes its own skills and remembers across sessions. These 5 from the community ecosystem push it further - drop them in ~/.hermes/skills/ and go. ANTHROPIC-CYBERSECURITY-SKILLS (4K★) by mukul975 · production the most comprehensive security skill pack in the ecosystem. what it adds: → 753+ structured cybersecurity skills mapped to MITRE ATT&CK → also covers NIST CSF 2.0, MITRE ATLAS, D3FEND & NIST AI RMF → turns Hermes into a recon + defense analyst, not a guesser → install: hermes skills install from the hub the workhorse of the list - start here. CHAINLINK-AGENT-SKILLS by Chainlink - official · production low profile, highest trust: it’s first-party from Chainlink itself. what it adds: → oracle network data, CCIP, smart-contract interaction skills → built on the spec - portable across clients → teaches the agent correct on-chain calls instead of hallucinated ABIs → official source, security-scanned on install stop letting the model guess your contract reads. HERMES-SKILL-FACTORY by Romanescu11 · beta the meta-layer - a skill that makes more skills. what it adds: → point it at any repetitive task → it auto-generates a reusable skill → stacks on top of Hermes’s own learning loop → turns your workflows into a self-growing skill library → install from the awesome-hermes-agent list this is what compounds your setup over time. AGENTCASH by Merit-Systems · beta the connector that gives your agent a wallet. what it adds: → access to 300+ premium APIs through one skill → pays for them via x402 or MPP - free USDC to start testing → web scraping, image gen, email sending - all behind one auth → a fresh Hermes + AgentCash alone is already dangerous the cleanest way to plug in paid tools. X-TWITTER-SCRAPER by Xquik-dev · beta drives typed X access through 43 narrow SKILL.md folders. what it adds: → reads (search, timelines, mentions, trends, bookmarks, for-you) → writes (post, DM, follow, profile) + bulk extraction (followers, lists, spaces) → AI composition: write-tweets, write-threads, optimize → security-scanned before it’s trusted feed its output straight into your scheduled briefings. BONUS - the registry itself: HERMESHUB by amanning3390. Browse, search, and install community skills with a 65+ rule security scanner - blocks prompt injection and data exfiltration before anything runs. Creator marketplace with x402/Stripe payments. hermes skills browse to start. If you install nothing else, wire up the hub. the stack in one line: hermeshub + skill-factory build & manage the library → cybersecurity + chainlink + agentcash + x-scraper give it real-world reach → Hermes runs it all on a $5 VPS while you sleep. which of these are you running? FULL HERMES SKILL-STACK PLAYBOOK 👇show more

Someone told ClawdBot to build a 6-agent Polymarket trading... system while they slept. 6 hours. Not a single question asked. Here’s what it built on its own: Monitoring agent — runs 24/7, spots mispriced markets, writes to memory, sends Telegram alerts instantly Research agent — parses news, X, and macro data every morning before you check your phone Trading agent — reads research memory and executes before the market catches up All on one Gateway, one config file, isolated per agent Copytrade → First week results: 47 mispriced markets captured before Polymarket adjusted 8–12¢ avg edge per position Token cost dropped 3×, from $0.40 → $0.13 per request The entire system is just plain .md text files. Change one line, the agent behaves differently. No deploy. No build. A BOT RESPONDS. AN AGENT EARNS. THIS IS WHAT AGENTIC TRADING ACTUALLY LOOKS LIKE.show more

STOP WASTING TOKENS ON OPENCLAW (I DID IT FOR... WEEKS) thought my agent was "optimized" - turns out it was just a token burning machine this guide exposed my setup: no workspace config = 3x spend on every call key insight: bootstrap memory ( etc) loads EVERY time - stuff it wisely or pay forever semantic search pulls facts on-demand from - no constant token drain after tweaks: > token usage: down 70% > agent recall: flawless across sessions gateway handles the pipeline: message -> context inject -> LLM loop -> tools -> response miss this? your agent's half-baked If you're running OpenClaw🦞 vanilla, you're leaking cash and potential dive into this breakdown and don't forget to bookmark it - it's agent building gold imoshow more

I stack Hermes agents with OpenClaw for financial research,... and the results should be illegal. I track every politician, insider trader, and I know EXACTLY what moves they're making. If you can't beat them, join them. The exact playbook for printing money from insider trading (copy me): Requirements: • OpenClaw setup • Hermes Agent setup Step 1. Define your research thesis Before you send any prompts to either tool, you'll need to clarify exactly what you're trying to research. This could be: a specific industry, asset class, market sector, and so on. Examples: • Tracking smart money buys in the semiconductor industry • Tracking smart money buys in crypto • Tracking a specific politician and where they're bidding (like Nancy Pelosi) Step 2. Deploy Hermes agents to track the smart money (in parallel) Hermes is your data layer. Spin up 5 agents at the same time, each with one job: Agent 1: Track every politician's disclosed trades from the last 30 days (House and Senate stock disclosures) Agent 2: Pull insider transactions (Form 4 filings, CEO/CFO buys and sells) Agent 3: Scrape X sentiment from top 50 accounts on the topic Agent 4: Pull on-chain data (whale wallets, TVL, exchange flows) *if applicable* Agent 5: Monitor news, regulatory filings, and announcements from the last 30 days Each agent runs independently. You're not waiting for one to finish before the next starts. Step 3. Consolidate the output Once your Hermes agents finish, dump every output into a single document. (don't filter or summarize) - you want OpenClaw to see the raw data. Step 4. Feed it all into OpenClaw Open OpenClaw and paste the consolidated research file with this prompt: "Act as an elite macro analyst. Below is raw data gathered from multiple sources on [thesis], including politician disclosures and insider transactions. Synthesize the findings, identify the strongest signals and contradictions, flag any unusual smart-money activity, and give me a clear directional view with conviction levels. Flag any data gaps that need follow-up." OpenClaw will go deep, run its own reasoning chain, and produce a synthesized report. Done. Now you're literally tapping into the financial data they don't want you to see (it's all public - you just had to find it). Make sure to save this playbook so you don't lose it!show more

Met my girlfriend's parents for the first time. Her... dad asked what I do for work. I said I build trading systems. He said like Wall Street? I said no. 6 AI agents. They work while I sleep. He laughed. So robots are making you money? I did not argue. I opened my laptop. Showed him the terminal. 6 agents running. 47 mispriced markets caught in the first week alone. His face changed. That is not gambling. That is automation? Exactly. Then I showed him how it works. Built the whole thing in 6 hours. Agent 1: Monitoring Runs 24/7. Watches Polymarket for mispriced markets. Spots an anomaly. Writes to memory and pings me on Telegram instantly. Agent 2: Research Parses news, X, macro data via browser tool on a cron schedule. Every morning I have a full digest on all open positions before I check my phone. Agent 3: Trading Reads the research agent memory. Sees the market has not reacted yet. Acts. Execution tool in gateway mode with a whitelist. No full access on a live server. Agent 4: Watchdog Heartbeat every 5 minutes. Monitoring running. No errors. Positions up to date. Something breaks. Immediate Telegram message. All of this. One Gateway. One config file. Isolation via per-agent scope. The token trick: stopped dumping everything into one file. Critical rules in bootstrap. Markets, patterns, past trades in memory. Semantic search pulls it when needed. Token spend dropped 3x. From $0.40 per request to $0.13. First week running: → 47 mispriced markets caught before Polymarket adjusted → Average entry edge 8 to 12 cents per position → Watchdog fired 3 times and caught a broken RPC before it cost me anything The whole system is plain text files. Open an editor. Change one line. Agent behaves differently. No deploy. No build. Her dad went quiet. Then he asked can you teach this? Her mom asked for the setup guide. I built the entire framework. Six agents. Full deployment. Memory architecture. Telegram alerts. You only need Claude + device + 1 hour per day. Giving this free for 24 hours. To get it: 1. Comment the word "Claude" 2. Like and retweet this 3. Follow me Himanshu Kumar so I can DM you Save this post. Deploy the 6-agent system this week. Start with $200. Scale on evidence.show more

Most people see a Mac Mini as a home... computer. He saw a $300 invoice waiting to happen. A guy in Shenzhen figured out that every early-stage startup, every founder, every small business owner needs the same thing, someone to tell them what their competitors are doing and where the gaps are. Nobody wants to pay $2,000 for a research firm. Nobody wants to wait a week. He set up Hermes on a laptop. Local model. No API costs. First report took 15 minutes. He charged $300 and delivered same day. Then he bought another machine. Then another. Now there are 65 Mac Minis on metal shelves in his apartment. Each one runs its own agent. Each agent has its own skills folder that grows every time it completes a task. Month one: $3,200. Month three: $9,600. The tool: Hermes Agent. Free on GitHub. The model: Qwen 3.6 27B. Also free. Total monthly cost: $2 in electricity. The hardware paid for itself in week two. The shelves haven't changed. He just keeps adding machines.show more

This broke my mental model of game dev 💀... 2.5 hours → fully playable ‘Worms’ clone. Built with Hermes agent by Nous Research Here’s what made that speed possible: Hermes used ‘Persistent Shell’ mode, which ensured it didn't forget its current folder or active tools. This allowed it to work smoothly, without the distraction of constantly having to recall where it left off last time. To optimize the workflow, the agent moved beyond linear execution and parallelized the workload. It spawned isolated subagents while executing multiple independent tool calls via ThreadPoolExecutor. Like, one subagent wrote Python RPC scripts for the projectile physics while another utilized vision tools for character sprites. When the complex terrain logic required debugging, the agent used filesystem checkpoints and the /rollback command to instantly return to a stable state. To fix UI bugs, it attached to a live Chrome instance via CDP (/browser connect), fixing rendering issues in real-time. The agent’s built-in learning loop was active from the very beginning. By the time the game was finished, this continuous process allowed the agent to autonomously convert the physics logic into a custom skill. This logic is now a permanent plugin file in the agent's plugin architecture, making the physics engine a native capability that the agent can reuse for future projects. Follow War_v3_FINALE.exe for updates!show more

HERMES AGENT HAS A SECOND BRAIN. 1,100+ KNOWLEDGE FILES.... AUTO-LINKED. SELF-IMPROVING. GROWING EVERY NIGHT. THIS IS THE OBSIDIAN GRAPH BEHIND IT. every dot = one knowledge file (markdown) every line = one wiki-link between files every color = one category (skills, notes, decisions, sources, entities) HOW IT BUILDS ITSELF: Hermes ships with a bundled LLM Wiki skill. based on Andrej Karpathy's pattern. unlike RAG (rediscovers knowledge from scratch every query), the wiki compiles knowledge once and keeps it current. when you feed the agent a source: → it reads the content → writes a structured markdown page → auto-links to every related existing page → flags contradictions with previous entries → updates all affected pages one source in. multiple connections created. the graph grows denser with every entry. WHAT FEEDS THE WIKI: → articles and URLs you find interesting → meeting transcripts → PDF documents and research papers → conversation history from Hermes sessions → Claude Code and Codex session history → Slack logs, email threads, saved notes → YouTube transcripts → raw text dropped into a _raw/ folder the obsidian-wiki package supports multi-agent ingest from Hermes, Claude Code, Codex, OpenClaw, Pi, Windsurf, and ChatGPT exports. install: pip install obsidian-wiki obsidian-wiki setup --vault ~/wiki AUTOMATE THE GROWTH: set cron jobs to feed the wiki overnight: "every day at 9am, check for new meetings. ingest transcripts into the wiki." "every week, check arXiv for new papers in [niche]. summarize and file into the wiki." "every day, ingest today's Hermes sessions into the wiki under session-history." month 1: 50 entries. scattered. month 3: 300+ entries. cross-referenced. month 6: 1,000+ entries. the agent surfaces patterns you never searched for. WHY OBSIDIAN: the wiki is plain markdown files. no database. no lock-in. open it in Obsidian for graph view: → nodes show knowledge density → links show how ideas connect → clusters reveal your strongest domains → orphan nodes reveal gaps Hermes writes from a VPS. Obsidian reads on your laptop. obsidian-headless syncs without a GUI. agent writes from the server, you browse on your device. FOUR MEMORY LAYERS: Layer 1: memory.md + user.md (~2,200 + 1,375 chars. short-term.) Layer 2: SQLite with FTS5 (full session transcripts. searchable.) Layer 3: external providers (Mem0, SuperMemory, Honcho. optional.) Layer 4: Obsidian wiki via LLM Wiki skill (unlimited. compounding. the long-term brain.) layers 1-3 handle memory. layer 4 handles knowledge. the graph in this post is layer 4. SETUP: set in Desktop app, Dashboard, or config.yaml: WIKI_PATH=~/wiki OBSIDIAN_VAULT_PATH=~/wiki first run: Hermes asks for your domain. answer with your niche. the skill builds SCHEMA.md with tag taxonomy. after that: "index this into my wiki: [URL or text]" the wiki grows. the graph densifies. the agent gets smarter because the knowledge base got smarter. full 15 levels breakdown in the article 👇show more

AI agent usage on SQD Portal is up ~200%... in recent weeks. A dev from our community chat was scraping a wallet UI with Hermes. Mid-task, DeepSeek reasoned its way out of it: "I can use SQD Portal's Hyperliquid fills data directly — much more complete than scraping a UI with infinite scroll." No prompt engineering. The model just chose the better and faster path. This is the loop we wanted: Agents pick SQD because it's faster → devs see agents picking SQD → devs ship faster → more agents pick SQD The picks-and-shovels moment for AI x onchain is here.show more