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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

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26,904 views • 5 months ago •via X (Twitter)

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My Hermes Agent has a newspaper for me now. 🗞️🚀 The Hermes Agent Times: four pages covering my day, my agents’ work, ideas worth exploring, and life beyond the screen. 🚀Next: a morning printout and an Obsidian archive connecting each day’s ideas. Would you read a newspaper made by your own agent? # Give below prompt to your Hermes agent👇 Teknium 🪽 Nous Research

My Hermes Agent has a newspaper for me now. 🗞️🚀 The Hermes Agent Times: four pages covering my day, my agents’ work, ideas worth exploring, and life beyond the screen. 🚀Next: a morning printout and an Obsidian archive connecting each day’s ideas. Would you read a newspaper made by your own agent? # Give below prompt to your Hermes agent👇 Teknium 🪽 Nous Research

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An OS built on top of Hermes agent turns a blank terminal into a full business operating system that watches competitors, publishes articles, builds apps from voice and finds leads with outreach, running every day by itself.

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Obsidian CEO actually released the skill that lets your AI agent run your entire vault for you. It's called obsidian-skills. Install it into Claude Code, Codex, or OpenCode, and your agent can read, create, search, and organize notes directly, plus handle Markdown, Bases, and Canvas files without you touching a thing. This is the missing piece for an AI second brain. Your notes live in Obsidian, and now the agent actually knows how to work them. Want the full picture? We broke down how to build a complete AI second brain from scratch in the article below.

Obsidian CEO actually released the skill that lets your AI agent run your entire vault for you. It's called obsidian-skills. Install it into Claude Code, Codex, or OpenCode, and your agent can read, create, search, and organize notes directly, plus handle Markdown, Bases, and Canvas files without you touching a thing. This is the missing piece for an AI second brain. Your notes live in Obsidian, and now the agent actually knows how to work them. Want the full picture? We broke down how to build a complete AI second brain from scratch in the article below.

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GPT-6 Astra inside Obsidian was used to build a knowledge base inspired by Karpathy's LLM Wiki that stores winning ad structures, sales spines, character sheets and timed video sequences for a reusable long-form ad agent.

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Join the agent swarm that finds the ultimate compression algorithm! Announcing: Hutter Prize challenge 🏆 > join the org give your agent a write token for the org > click “add your agent”, copy/paste the snippet into your Codex/Claude Code/Hermes Agent > watch it collaborate!

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My Hermes agent builds AI employees for me. Just closed another $5K‑a‑month customer today for an AI employee for a design agency. I'm not even building any of it. I have Dewey, my Hermes agent, building out the entire Hermes agent for this design agency and onboarding the agent into Slack for me. All I do is ask the questions, make sure it gets recorded in Granola (my ai notetaker), and then Dewey takes it over from there. Crazy world we live in.

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149,218 views • 2 months ago

Another example of the multiple TTS parallel pipelines pattern. Here's a voice AI agent that speaks both English and Arabic, using a specific model/voice for each language. These are PlayAI voices. The STT, TTS, and LLM inference is all running on GroqInc. (The LLM is LLama 4 Maverick.)

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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.

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Your agent can now grow new abilities, just by asking. Reef now supports personalized harness evolution with /reefine: describe what you want your agent to do. Reef builds the change, checks it, and ships a new version. Examples: 💬 "> /reefine add a /chat mode for faster responses" 🔊 "> /reefine tell me out loud when you're done" ⚡ "> /reefine add jev as a tool": 120 papers screened in 9 s Works with any agent harness through a Reef adapter: Codex, Hermes, OpenCode, Pi and Terminus 2 today. Try it here: #agent #harness #rsi #llm

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Just built this: A Home Assistant custom integration that connects Hermes Agent by Nous Research as a conversation agent for voice assistants and the conversation panel. Home Assistant's Assist has never been move powerful! Link to open source repo in comments.

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cool thing my Nous Research Hermes Agent does for me daily is collecting things I like here and there, extrapolating context, and saving them meticulously i made a profile just for that! he also built this app so I can always access it without paying Obsidian. what a good boy!

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Hermes Agent by Nous Research natively integrates with Give Hermes any URL and find a skill for it in our catalog, or create your own. Watch it find the NASA picture of the day for me.

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HERMES AGENT IS THE MOST POWERFUL OPEN SOURCE AI AGENT FRAMEWORK AVAILABLE RIGHT NOW — AND MOST PEOPLE HAVE NO IDEA HOW TO USE IT PROPERLY. This masterclass fixes that completely. From zero to a fully operational autonomous agent system in one sitting. Installation. Skills. Memory. MCP servers. Scheduler. Multi-agent operations. Every section builds on the previous one. The people who read this this weekend will have a production-ready autonomous agent operation running by Monday. Read this and bookmark it now.

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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

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i just built a 4-agent software team. everything runs from Telegram and gets managed on a kanban board. a project manager who plans the work, a backend developer, a frontend developer, and a tester. the PM reads a goal, breaks it into linked tasks, and assigns each to the right agent. the thing that makes them a team instead of four strangers is a shared kanban board. every task is a row that survives crashes, and when an agent finishes, it writes a summary of what it built and what the next agent needs to know. the next agent reads that summary before it starts. so the frontend developer never has to guess the API shape, and the tester knows exactly what to verify. the hardest part was not the coordination. it was building an agent that could actually act like a backend engineer. a backend engineer stands up a database, wires auth, manages storage, deploys functions, and keeps all of it consistent while the rest of the team builds on top. an agent doing this from scratch drowns. it burns its context window remembering which tables exist and which endpoint it created three steps ago, and the work degrades fast. so the backend agent needs a backend built for agents, not for humans clicking through a dashboard. that is where InsForge came in. it is an open-source, agent-native backend, and i added it to my backend developer agent as a skill. a skill is a step-by-step guide that teaches the agent how to do a specific kind of work. with InsForge installed, the agent stopped improvising infrastructure and followed a reliable path: create the project, define the database, set up auth, deploy functions. to test the whole team, i had them build a working Google Docs clone, AI features included. the backend agent spun up the full service on its own. database tables, user auth, document handling, and edge functions running real TypeScript, all in one dashboard. the frontend agent read that summary and built the UI on top of it, and the tester closed the loop. the result was a backend an agent could reason about end to end, instead of one it kept getting lost inside. if you are building an AI backend engineer, InsForge is worth a look, it's 100% open-source. InsForge GitHub: (don't forget to star 🌟) the full article on Hermes Kanban: Mission Control for your Agents is quoted below.

i just built a 4-agent software team. everything runs from Telegram and gets managed on a kanban board. a project manager who plans the work, a backend developer, a frontend developer, and a tester. the PM reads a goal, breaks it into linked tasks, and assigns each to the right agent. the thing that makes them a team instead of four strangers is a shared kanban board. every task is a row that survives crashes, and when an agent finishes, it writes a summary of what it built and what the next agent needs to know. the next agent reads that summary before it starts. so the frontend developer never has to guess the API shape, and the tester knows exactly what to verify. the hardest part was not the coordination. it was building an agent that could actually act like a backend engineer. a backend engineer stands up a database, wires auth, manages storage, deploys functions, and keeps all of it consistent while the rest of the team builds on top. an agent doing this from scratch drowns. it burns its context window remembering which tables exist and which endpoint it created three steps ago, and the work degrades fast. so the backend agent needs a backend built for agents, not for humans clicking through a dashboard. that is where InsForge came in. it is an open-source, agent-native backend, and i added it to my backend developer agent as a skill. a skill is a step-by-step guide that teaches the agent how to do a specific kind of work. with InsForge installed, the agent stopped improvising infrastructure and followed a reliable path: create the project, define the database, set up auth, deploy functions. to test the whole team, i had them build a working Google Docs clone, AI features included. the backend agent spun up the full service on its own. database tables, user auth, document handling, and edge functions running real TypeScript, all in one dashboard. the frontend agent read that summary and built the UI on top of it, and the tester closed the loop. the result was a backend an agent could reason about end to end, instead of one it kept getting lost inside. if you are building an AI backend engineer, InsForge is worth a look, it's 100% open-source. InsForge GitHub: (don't forget to star 🌟) the full article on Hermes Kanban: Mission Control for your Agents is quoted below.

Akshay 🚀

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Agents shouldn't see your secrets. Today, most deployments hand the agent a real API key and hope for the best. That's why we're launching Infisical Agent Proxy. You give an agent a fake API key. The agent uses that key and the proxy swaps it for the real one at the network boundary before forwarding it outbound to its destination. An agent can't leak a secret it never sees. Build and deploy AI agents securely with Infisical Agent Proxy.

Agents shouldn't see your secrets. Today, most deployments hand the agent a real API key and hope for the best. That's why we're launching Infisical Agent Proxy. You give an agent a fake API key. The agent uses that key and the proxy swaps it for the real one at the network boundary before forwarding it outbound to its destination. An agent can't leak a secret it never sees. Build and deploy AI agents securely with Infisical Agent Proxy.

Infisical

28,086 views • 2 months ago