正在加载视频...

视频加载失败

加载此视频时出现问题。这可能是由于临时网络问题，或视频可能不可用。

Hermes Agent now has a production-grade WhatsApp Business Cloud integration: use it as a private WhatsApp bot for yourself or your team, or configure it for customer-facing support. Connect an existing WhatsApp Business Cloud number or create one through Meta Business Manager, then run 'hermes whatsapp-cloud' to wire it... show more

Nous Research

248,655 subscribers

189,260 次观看 • 2 个月前 •via X (Twitter)

教育科学技术

Anya Rossi• Live Now

Private livecam show

0 条评论

暂无评论

原始帖子的评论将显示在这里

相关视频

most of you don't know how hard hermes agent is optimized for local AI at the system level. watch the full setup flow on screen. you paste an openai-compatible v1 endpoint, hermes auto-detects every model running behind it. doesn't matter if it's llama.cpp or vllm or any compatible server, all your models surface and become selectable in seconds. no config gymnastics, no manual model list. then it goes deeper. hermes ships with per model parsers, prompt template auto-handling, tool call format detection per model architecture, thinking mode awareness, all the small friction points other harnesses leak on. these were not built for cloud apis with one canonical model. they were built for builders running 10 different local models across 10 different stacks. cloud first harnesses bolt local support on top. hermes agent is local first from the architecture out. that's the system level gap. if you're getting started on local AI, this is the harness you start with. try for yourself and find out. anyone serious about local AI lands here eventually.

most of you don't know how hard hermes agent is optimized for local AI at the system level. watch the full setup flow on screen. you paste an openai-compatible v1 endpoint, hermes auto-detects every model running behind it. doesn't matter if it's llama.cpp or vllm or any compatible server, all your models surface and become selectable in seconds. no config gymnastics, no manual model list. then it goes deeper. hermes ships with per model parsers, prompt template auto-handling, tool call format detection per model architecture, thinking mode awareness, all the small friction points other harnesses leak on. these were not built for cloud apis with one canonical model. they were built for builders running 10 different local models across 10 different stacks. cloud first harnesses bolt local support on top. hermes agent is local first from the architecture out. that's the system level gap. if you're getting started on local AI, this is the harness you start with. try for yourself and find out. anyone serious about local AI lands here eventually.

Sudo su

14,407 次观看 • 3 个月前

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 ↓

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 ↓

marfin

26,654 次观看 • 3 个月前

THE EASIEST FACELESS BUSINESS TO START RIGHT NOW IS 100% RUN BY AN AI AGENT there's people making money with fully automated twitch clipping systems you flip streamer VODs into clips and build faceless pages on top, hands-off the hard part was always the editing. Midir (a Hermes agent on Telegram) does it for you: 1. drop a VOD 2. it clips the best moments to 9:16 3. you approve 4. auto-posts to TikTok via Postiz + Instagram cost to start: → Fable 5 → Postiz ($20/m) → a $50 Android → warmed up IG/TikTok accounts run your own pages or sell it to streamers. scales either way full playbook in the article 👇

THE EASIEST FACELESS BUSINESS TO START RIGHT NOW IS 100% RUN BY AN AI AGENT there's people making money with fully automated twitch clipping systems you flip streamer VODs into clips and build faceless pages on top, hands-off the hard part was always the editing. Midir (a Hermes agent on Telegram) does it for you: 1. drop a VOD 2. it clips the best moments to 9:16 3. you approve 4. auto-posts to TikTok via Postiz + Instagram cost to start: → Fable 5 → Postiz ($20/m) → a $50 Android → warmed up IG/TikTok accounts run your own pages or sell it to streamers. scales either way full playbook in the article 👇

gus

12,269 次观看 • 1 个月前

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 👇

ZEUS⚡️

21,710 次观看 • 2 个月前

Hermes Desktop does not have to stay exactly the way it shipped. You can build the tools you wish were already inside it. A project dashboard. A Bot control panel. A research tracker. A queue for work that needs your attention. A status board for scheduled jobs. A set of quick actions you use every day. That is what the Hermes Desktop Plugin SDK opens up. SDK is the technical name, but the idea is pretty simple: It gives you a way to add your own tools and interfaces directly inside Hermes Desktop. A plugin can add its own page, pane, sidebar item, status-bar element, keyboard shortcut, command-palette action, or composer extension. And it can work with live Hermes data, including things like sessions, config, Skills, and Cron. So if you keep asking Hermes to recreate the same dashboard, show the same information, or give you the same controls... you may be at the point where that workflow deserves to become an actual part of your Desktop. The starting point can be surprisingly lightweight too. A basic local plugin can be a single `plugin.js` file under: `$HERMES_HOME/desktop-plugins/ /` No Hermes repo clone. No separate build step. The bigger idea here is not “turn every prompt into an app.” It is that Hermes Desktop can become much more personal than the interface you downloaded. When a workflow proves useful enough, you can give it its own permanent place. Video via Brooklyn! — a good look at what this can actually become.

Hermes Desktop does not have to stay exactly the way it shipped. You can build the tools you wish were already inside it. A project dashboard. A Bot control panel. A research tracker. A queue for work that needs your attention. A status board for scheduled jobs. A set of quick actions you use every day. That is what the Hermes Desktop Plugin SDK opens up. SDK is the technical name, but the idea is pretty simple: It gives you a way to add your own tools and interfaces directly inside Hermes Desktop. A plugin can add its own page, pane, sidebar item, status-bar element, keyboard shortcut, command-palette action, or composer extension. And it can work with live Hermes data, including things like sessions, config, Skills, and Cron. So if you keep asking Hermes to recreate the same dashboard, show the same information, or give you the same controls... you may be at the point where that workflow deserves to become an actual part of your Desktop. The starting point can be surprisingly lightweight too. A basic local plugin can be a single `plugin.js` file under: `$HERMES_HOME/desktop-plugins/ /` No Hermes repo clone. No separate build step. The bigger idea here is not “turn every prompt into an app.” It is that Hermes Desktop can become much more personal than the interface you downloaded. When a workflow proves useful enough, you can give it its own permanent place. Video via Brooklyn! — a good look at what this can actually become.

Hermes Release Watch

15,035 次观看 • 11 天前

I'M SHOCKED – ALMOST NOBODY IS USING GROK BOT THE RIGHT WAY. A LEAD ENGINEER AT SPACEX AI JUST DROPPED A 1-HOUR COURSE ON HOW IT'S ACTUALLY DONE. HERE'S ALL OF IT IN 60 SECONDS. The mistake almost everyone makes: they hand Grok Bot random one-off tasks. That's it. That's the whole reason it still feels like a chatbot to you. Here's the system he teaches instead – five parts: → ROLE – stop assigning tasks, create permanent roles. Chief of Staff, Inbox Manager, Researcher, Developer, Reviewer. A bot with a job title beats a bot with a to-do list → TOOLS – connect each bot to what it actually needs: Gmail, Slack, Calendar, Notion, GitHub. It does the work on its own persistent cloud computer → SKILL – teach it your workflow. Write the instructions, or just record yourself doing the job once – Grok Bot turns that demonstration into a reusable skill → ROUTINE – anything you repeat becomes a routine. It runs on a schedule or fires off an event, with your laptop closed → TEAM – group the bots together. The lead bot delegates, the specialists work in parallel, and you set approval rules before anything sends an email, moves a calendar or pushes code The one honest catch: a new bot still needs context and some hand-holding on its first few runs. But that's the entire system. Role → Tools → Skill → Routine → Team. Everyone else is still typing one-off prompts into Grok Bot and wondering why nothing compounds. Bookmark this & read the full breakdown in the article below ↓

I'M SHOCKED – ALMOST NOBODY IS USING GROK BOT THE RIGHT WAY. A LEAD ENGINEER AT SPACEX AI JUST DROPPED A 1-HOUR COURSE ON HOW IT'S ACTUALLY DONE. HERE'S ALL OF IT IN 60 SECONDS. The mistake almost everyone makes: they hand Grok Bot random one-off tasks. That's it. That's the whole reason it still feels like a chatbot to you. Here's the system he teaches instead – five parts: → ROLE – stop assigning tasks, create permanent roles. Chief of Staff, Inbox Manager, Researcher, Developer, Reviewer. A bot with a job title beats a bot with a to-do list → TOOLS – connect each bot to what it actually needs: Gmail, Slack, Calendar, Notion, GitHub. It does the work on its own persistent cloud computer → SKILL – teach it your workflow. Write the instructions, or just record yourself doing the job once – Grok Bot turns that demonstration into a reusable skill → ROUTINE – anything you repeat becomes a routine. It runs on a schedule or fires off an event, with your laptop closed → TEAM – group the bots together. The lead bot delegates, the specialists work in parallel, and you set approval rules before anything sends an email, moves a calendar or pushes code The one honest catch: a new bot still needs context and some hand-holding on its first few runs. But that's the entire system. Role → Tools → Skill → Routine → Team. Everyone else is still typing one-off prompts into Grok Bot and wondering why nothing compounds. Bookmark this & read the full breakdown in the article below ↓

SCOTTY BEAM

97,697 次观看 • 17 天前

This new skill for Hermes Agent wipes your personal data off hundreds of broker sites for free, hands-off. It's called Unbroker. I’ve been testing it this week and it's incredible. Here is the full setup: 1. Install it by typing: hermes skills install official/security/unbroker 2. Connect browser automation: Wire up Browserbase so the agent can drive real broker opt-out forms. 3. Do the intake: Give consent, then feed it your info. 4. Fire one prompt: "Use the unbroker skill to remove my data from data brokers. Here is my consent. Run it hands-off." Hundreds of data brokers publish your name, addresses, phone, email, even your relatives. Anyone can find where you live in about ten seconds. The law says brokers have to delete your data if you ask. There's just no easy bulk button for it. Services charge $100’s a year to file the exact requests you could submit yourself for free. Unbroker does the same thing locally, and it's free. It fans out sub-agents, scans every broker site, drafts or sends opt-out emails, and only comes back to you for the ones that need a human. The best part is it loops. Brokers re-list you over time, so it schedules rechecks and re-files on its own. Set it once, it keeps working. One skill, one prompt, dozens of broker sites handled.

This new skill for Hermes Agent wipes your personal data off hundreds of broker sites for free, hands-off. It's called Unbroker. I’ve been testing it this week and it's incredible. Here is the full setup: 1. Install it by typing: hermes skills install official/security/unbroker 2. Connect browser automation: Wire up Browserbase so the agent can drive real broker opt-out forms. 3. Do the intake: Give consent, then feed it your info. 4. Fire one prompt: "Use the unbroker skill to remove my data from data brokers. Here is my consent. Run it hands-off." Hundreds of data brokers publish your name, addresses, phone, email, even your relatives. Anyone can find where you live in about ten seconds. The law says brokers have to delete your data if you ask. There's just no easy bulk button for it. Services charge $100’s a year to file the exact requests you could submit yourself for free. Unbroker does the same thing locally, and it's free. It fans out sub-agents, scans every broker site, drafts or sends opt-out emails, and only comes back to you for the ones that need a human. The best part is it loops. Brokers re-list you over time, so it schedules rechecks and re-files on its own. Set it once, it keeps working. One skill, one prompt, dozens of broker sites handled.

Alvaro Cintas

29,848 次观看 • 1 个月前

All our pioneers community are actively respond to CT call to take video to support project by #WhatIDoForPi .What pioneers can do ? 1. Pass KYC and migrate yourself 2.Become validator to expedite the process of other pioneers KYC. 3. Invite your referral team pass KYC. 4. If you have software program skills,you can develop Pi apps. 5. You can become Ecosystem Ambassador which means use your own network to invite your contacts who has technical skills to build useful Apps. 6. Become a local Business Ambassador which means contact with your local shops, stores or even enterprise, logistics to submit business proposal on or they can integrate Pi as payment. 7. If you can't do all above, you can use Pi apps to provide feedback to Pi Eco system builders. Or anything you contribute to Pi Network you can share! The video is 10 second and use #WhatIDoForPi hashtag. I post three from business or business owner who accept Pi as payment by GCV $314,159! And one video from Chinese pioneers community who support GCV as Barter start price! Thanks to all community hard work! Eco systems mature need more local business integrated. That means not only online eco but also offline eco will be more prosperous. It needs all pioneers contribute in it . I see a lot Chinese pioneers did this already and has created a big influence! Also we strongly support GCV price which can protect all business who makes decisions to accept Pi Payment. All business request united price so that they can do business marketing research and business risk analysis before they jump in ! That's the reason our GCV community are actively working on it 🙏🙏🙏 Pi Network #PiGCV

All our pioneers community are actively respond to CT call to take video to support project by #WhatIDoForPi .What pioneers can do ? 1. Pass KYC and migrate yourself 2.Become validator to expedite the process of other pioneers KYC. 3. Invite your referral team pass KYC. 4. If you have software program skills,you can develop Pi apps. 5. You can become Ecosystem Ambassador which means use your own network to invite your contacts who has technical skills to build useful Apps. 6. Become a local Business Ambassador which means contact with your local shops, stores or even enterprise, logistics to submit business proposal on or they can integrate Pi as payment. 7. If you can't do all above, you can use Pi apps to provide feedback to Pi Eco system builders. Or anything you contribute to Pi Network you can share! The video is 10 second and use #WhatIDoForPi hashtag. I post three from business or business owner who accept Pi as payment by GCV $314,159! And one video from Chinese pioneers community who support GCV as Barter start price! Thanks to all community hard work! Eco systems mature need more local business integrated. That means not only online eco but also offline eco will be more prosperous. It needs all pioneers contribute in it . I see a lot Chinese pioneers did this already and has created a big influence! Also we strongly support GCV price which can protect all business who makes decisions to accept Pi Payment. All business request united price so that they can do business marketing research and business risk analysis before they jump in ! That's the reason our GCV community are actively working on it 🙏🙏🙏 Pi Network #PiGCV

Doris Yin 东方紫莲🪷

23,917 次观看 • 3 年前

Karpathy's Agentic Engineering finally has proper tooling! (built by Google) Karpathy defined agentic engineering as the discipline that separates production agent work from vibe coding. The core skills he listed were spec design, eval loops, and security oversight. The problem has been that practicing this still requires a different tool for every phase: - editor for code - a terminal for scaffolding - a browser for testing - a cloud console for deployment - and a separate framework for evals. Every transition is a context switch. The solution to production-grade Agentic Engineering is now actually implemented in Google’s Agents CLI. It covers the entire workflow in one place for scaffolding, evaluating, and deploying ADK agents. One setup command injects 7 ADK-specific skills into a coding agent's context, which lets it handle scaffolding, evals, deployment, and enterprise registration through natural language. I tested this end-to-end by building a RAG agent from scratch using Claude Code. It scaffolded the full project from the ADK agentic_rag template, generated 20 eval scenarios with LLM-as-judge scoring, and returned a quantitative scorecard. Finally, it also deployed everything to Agent Runtime and registered the agent to Gemini Enterprise, so the entire org can discover and use it. The video below shows this in action, and I worked with the Google Cloud team to put this together. Agents CLI GitHub repo → (don't forget to star it ⭐ ) I wrote up the full build covering all six steps from install to enterprise registration. It includes the eval scorecard, the instruction loophole the eval caught before deployment, and what the deployment process actually looks like end-to-end. Read it below.

Karpathy's Agentic Engineering finally has proper tooling! (built by Google) Karpathy defined agentic engineering as the discipline that separates production agent work from vibe coding. The core skills he listed were spec design, eval loops, and security oversight. The problem has been that practicing this still requires a different tool for every phase: - editor for code - a terminal for scaffolding - a browser for testing - a cloud console for deployment - and a separate framework for evals. Every transition is a context switch. The solution to production-grade Agentic Engineering is now actually implemented in Google’s Agents CLI. It covers the entire workflow in one place for scaffolding, evaluating, and deploying ADK agents. One setup command injects 7 ADK-specific skills into a coding agent's context, which lets it handle scaffolding, evals, deployment, and enterprise registration through natural language. I tested this end-to-end by building a RAG agent from scratch using Claude Code. It scaffolded the full project from the ADK agentic_rag template, generated 20 eval scenarios with LLM-as-judge scoring, and returned a quantitative scorecard. Finally, it also deployed everything to Agent Runtime and registered the agent to Gemini Enterprise, so the entire org can discover and use it. The video below shows this in action, and I worked with the Google Cloud team to put this together. Agents CLI GitHub repo → (don't forget to star it ⭐ ) I wrote up the full build covering all six steps from install to enterprise registration. It includes the eval scorecard, the instruction loophole the eval caught before deployment, and what the deployment process actually looks like end-to-end. Read it below.

Akshay 🚀

258,436 次观看 • 2 个月前

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 👇

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 👇

YanXbt

34,987 次观看 • 2 个月前

Grok Bot just turned X into a research database for you Connect your X account and it can now: • Read your timeline, posts, mentions, likes + Spaces • Search X with advanced operators • Run full-archive searches • Pull any public account’s recent posts • See who liked, reposted + quoted a post • Track trends + news • Count conversation volume around a topic • Read + organize your bookmarks • Save/unsave bookmarks • Create + manage Lists • Read blocks + mutes • Block/unblock accounts • Check your X API credits And paid Grok Bot users get starter X API credits. Try asking Grok Bot this for some useful info: "What did people mention me about this week?" "What's everyone saying about [topic] right now?" "Pull Min Choi’s recent posts and brief me." "Find the biggest conversations around this product." "Organize all my saved posts by topic." "Tell me who quoted this post and what they said." Important: It still CANNOT post, reply, like, repost, follow or DM for you. So this isn't an autonomous social media spam bot. It's basically an always-on listener + researcher for X. For anyone whose business, audience, research or news lives on X... this is a pretty massive Grok Bot upgrade.

Grok Bot just turned X into a research database for you Connect your X account and it can now: • Read your timeline, posts, mentions, likes + Spaces • Search X with advanced operators • Run full-archive searches • Pull any public account’s recent posts • See who liked, reposted + quoted a post • Track trends + news • Count conversation volume around a topic • Read + organize your bookmarks • Save/unsave bookmarks • Create + manage Lists • Read blocks + mutes • Block/unblock accounts • Check your X API credits And paid Grok Bot users get starter X API credits. Try asking Grok Bot this for some useful info: "What did people mention me about this week?" "What's everyone saying about [topic] right now?" "Pull Min Choi’s recent posts and brief me." "Find the biggest conversations around this product." "Organize all my saved posts by topic." "Tell me who quoted this post and what they said." Important: It still CANNOT post, reply, like, repost, follow or DM for you. So this isn't an autonomous social media spam bot. It's basically an always-on listener + researcher for X. For anyone whose business, audience, research or news lives on X... this is a pretty massive Grok Bot upgrade.

Min Choi

39,307 次观看 • 10 天前

Sharing my new skill! It keeps track of high-signal X accounts for top AI news, papers, projects, etc. Total gamechanger for me. Built with X MCP tools. Give your agent the skill and tell it to generate the artifact with top stories. Works for Codex, Claude, Hermes, OpenClaw, or whatever you use. 3 steps: 1. Set up X MCP - X API: 2. Install skill here: 3. Run prompt: "Use the x-agent-intelligence skill to build a self-contained local feed from my X MCP connection; ask for my source handles if needed, save feed.html, and validate it." It should generate a nice, beautiful HTML artifact like the one shown in the clip. You can tune it however you want. You can then set a schedule/automation to do this daily or whatever cadence you prefer. I have it every 4 hours. You will need to curate the X accounts yourself, but I have shared a few good ones under the assets. You can ask your agent to tune it to however you like. I have also shared my personal feed with our community here: I understand if it gets tricky to set up. Please reach out to me in the community forum. I plan to do a little tutorial or live session soon to help others reproduce the process. You can also store the feed as a wiki, as I have in my own implementation, but that's optional. If you encounter any issues or have ideas on how to improve it, please open a PR.

Sharing my new skill! It keeps track of high-signal X accounts for top AI news, papers, projects, etc. Total gamechanger for me. Built with X MCP tools. Give your agent the skill and tell it to generate the artifact with top stories. Works for Codex, Claude, Hermes, OpenClaw, or whatever you use. 3 steps: 1. Set up X MCP - X API: 2. Install skill here: 3. Run prompt: "Use the x-agent-intelligence skill to build a self-contained local feed from my X MCP connection; ask for my source handles if needed, save feed.html, and validate it." It should generate a nice, beautiful HTML artifact like the one shown in the clip. You can tune it however you want. You can then set a schedule/automation to do this daily or whatever cadence you prefer. I have it every 4 hours. You will need to curate the X accounts yourself, but I have shared a few good ones under the assets. You can ask your agent to tune it to however you like. I have also shared my personal feed with our community here: I understand if it gets tricky to set up. Please reach out to me in the community forum. I plan to do a little tutorial or live session soon to help others reproduce the process. You can also store the feed as a wiki, as I have in my own implementation, but that's optional. If you encounter any issues or have ideas on how to improve it, please open a PR.

elvis

72,234 次观看 • 1 个月前

Building AI agents is finally simple — and Airia is leading the way. I’ve been testing Airia AI , enterprise AI orchestration platform that unifies every model, workflow, and data source into one secure environment. Whether you’re a developer, analyst, creator, or enterprise leader, Airia makes it incredibly easy to build powerful AI agents — without wrestling with multiple tools or complex integrations. Using the no-code builder, you can drag-and-drop actions, connect data, choose your LLM, and launch an agent in minutes. Then run it live, publish it, and even share it with the Airia Community, home to 2,500+ pre-built agents you can use or remix. If you want to automate workflows, prototype faster, or explore real enterprise AI use cases, Airia is the place to start. 👉 Build your first agent today: 👉 Explore the community: #Airia #AgenticAI #AIOrchestration #AIAgents #AIWorkflow #DigitalTransformation

Building AI agents is finally simple — and Airia is leading the way. I’ve been testing Airia AI , enterprise AI orchestration platform that unifies every model, workflow, and data source into one secure environment. Whether you’re a developer, analyst, creator, or enterprise leader, Airia makes it incredibly easy to build powerful AI agents — without wrestling with multiple tools or complex integrations. Using the no-code builder, you can drag-and-drop actions, connect data, choose your LLM, and launch an agent in minutes. Then run it live, publish it, and even share it with the Airia Community, home to 2,500+ pre-built agents you can use or remix. If you want to automate workflows, prototype faster, or explore real enterprise AI use cases, Airia is the place to start. 👉 Build your first agent today: 👉 Explore the community: #Airia #AgenticAI #AIOrchestration #AIAgents #AIWorkflow #DigitalTransformation

Adarsh Chetan

269,292 次观看 • 9 个月前

OpenClaw, but built for normal people. Sim is an open-source platform that lets you build AI agent workflows on a drag-and-drop canvas. Connect them to channels like Telegram and WhatsApp and deploy without writing a single line of code. They also have a built-in Copilot that generates entire workflows from plain English, which you can then tweak and customize in the UI. Key features: - Free and open-source (Apache 2.0) - Vector store integration for RAG-grounded agents - Self-host with one command (`npx simstudio`) - Run fully local with Ollama, no API keys needed - Supports vLLM for production-grade self-hosted inference The thing I really like about Sim is the level of control you get. You can add conditional branching, parallel execution, human-in-the-loop approval gates, and even nest workflows inside other workflows. Everything is visible on the canvas, so you know exactly what your agent is doing at every step. And you can build a workflow in Sim, deploy it as an MCP server, and plug it into any agent, including OpenClaw. I've shared the link to Sim's GitHub repo in the next tweet.

OpenClaw, but built for normal people. Sim is an open-source platform that lets you build AI agent workflows on a drag-and-drop canvas. Connect them to channels like Telegram and WhatsApp and deploy without writing a single line of code. They also have a built-in Copilot that generates entire workflows from plain English, which you can then tweak and customize in the UI. Key features: - Free and open-source (Apache 2.0) - Vector store integration for RAG-grounded agents - Self-host with one command (`npx simstudio`) - Run fully local with Ollama, no API keys needed - Supports vLLM for production-grade self-hosted inference The thing I really like about Sim is the level of control you get. You can add conditional branching, parallel execution, human-in-the-loop approval gates, and even nest workflows inside other workflows. Everything is visible on the canvas, so you know exactly what your agent is doing at every step. And you can build a workflow in Sim, deploy it as an MCP server, and plug it into any agent, including OpenClaw. I've shared the link to Sim's GitHub repo in the next tweet.

Akshay 🚀

52,426 次观看 • 6 个月前

CA: 0x172ae9e9b46770a70f479404d76e2f6561507011ef77a247fe3f58e7a5840a0d::manny::MANNY Your smart, hands-free edge tool in the crypto market. This powerful automated bot is designed to buy low and sell high with precision. It scans hundreds of coins in real-time, waiting for the right indicators—trend strength, volume spikes, price momentum, and bullish patterns—before entering a trade. Once in, it manages risk with dynamic stop-loss and take-profit levels, so your capital is always protected. Every trade is backed by a multi-layer confluence strategy, ensuring only high-confidence setups are executed. ✅ Advanced entry logic ✅ Fully automated buy/sell execution ✅ Built-in profit protection and cooldown filters ✅ Real-time alerts (Telegram/Twitter ready) ✅ JSON-based state memory for continuity ✅ Minimal setup, maximum performance ✅ Excludes low-quality coins automatically (e.g., BTC/ETH filters optional) ✅ Plug-and-play friendly — run it locally or integrate it into your system. ✅ Clean, professional trade alerts with price and PnL details ✅ Recovers automatically from connection issues or downtime Whether you’re a pro or just getting started, this bot helps you stay ahead of the market—24/7, emotion-free with pure mathematics. This bot has been in development for the last 6 months. I, Chronos, the developer behind it, have been testing for a while for the best configuration for a trading bot. I believe I have something good going on here. The bot automatically posts all the trades via IFTTT and X integration to its X account. Everything is automated. So how can people rent it, and how will it bring value to the project? Soon, the bot can be rented out via a cloud server. A customer must buy 30 USD worth of Memecoin_MANNY token (CA:0x172ae9e9b46770a70f479404d76e2f6561507011ef77a247fe3f58e7a5840a0d::manny::MANNY). After buying it and depositing it into a special wallet, he will be granted access to the bot. . The bot runs only on the backend — users interact with it via an interface (web app, Telegram bot, or API). A web dashboard and Telegram bot interface will be created. This lets users Start/stop their bot session See trade logs or results. Connect their API keys securely. Get alerts and updates The idea of all this is to offer a service but also bring value to the project. More bots will be developed. This is only the beginning. Cheers Chronos #python #memecoin_manny #spot #trading #bitcoin #eth #Binance #bybit #memecoin #VALHALLA

CA: 0x172ae9e9b46770a70f479404d76e2f6561507011ef77a247fe3f58e7a5840a0d::manny::MANNY Your smart, hands-free edge tool in the crypto market. This powerful automated bot is designed to buy low and sell high with precision. It scans hundreds of coins in real-time, waiting for the right indicators—trend strength, volume spikes, price momentum, and bullish patterns—before entering a trade. Once in, it manages risk with dynamic stop-loss and take-profit levels, so your capital is always protected. Every trade is backed by a multi-layer confluence strategy, ensuring only high-confidence setups are executed. ✅ Advanced entry logic ✅ Fully automated buy/sell execution ✅ Built-in profit protection and cooldown filters ✅ Real-time alerts (Telegram/Twitter ready) ✅ JSON-based state memory for continuity ✅ Minimal setup, maximum performance ✅ Excludes low-quality coins automatically (e.g., BTC/ETH filters optional) ✅ Plug-and-play friendly — run it locally or integrate it into your system. ✅ Clean, professional trade alerts with price and PnL details ✅ Recovers automatically from connection issues or downtime Whether you’re a pro or just getting started, this bot helps you stay ahead of the market—24/7, emotion-free with pure mathematics. This bot has been in development for the last 6 months. I, Chronos, the developer behind it, have been testing for a while for the best configuration for a trading bot. I believe I have something good going on here. The bot automatically posts all the trades via IFTTT and X integration to its X account. Everything is automated. So how can people rent it, and how will it bring value to the project? Soon, the bot can be rented out via a cloud server. A customer must buy 30 USD worth of Memecoin_MANNY token (CA:0x172ae9e9b46770a70f479404d76e2f6561507011ef77a247fe3f58e7a5840a0d::manny::MANNY). After buying it and depositing it into a special wallet, he will be granted access to the bot. . The bot runs only on the backend — users interact with it via an interface (web app, Telegram bot, or API). A web dashboard and Telegram bot interface will be created. This lets users Start/stop their bot session See trade logs or results. Connect their API keys securely. Get alerts and updates The idea of all this is to offer a service but also bring value to the project. More bots will be developed. This is only the beginning. Cheers Chronos #python #memecoin_manny #spot #trading #bitcoin #eth #Binance #bybit #memecoin #VALHALLA

Ex Machina

24,488 次观看 • 1 年前

CHINA JUST LEAKED THE FUTURE OF WEB APPS. Alibaba open-sourced PageAgent and 99% of SaaS founders are sleeping on this. It's a JavaScript AI agent that lives INSIDE your webpage. Users control your entire interface with natural language. ↳ No browser extensions needed, screenshots or multi-modal LLMs, headless browser setup, and also no backend rewrite required Just drop it in your HTML with ONE line of code. What took 20 clicks now takes one sentence. "Click login, fill in my credentials, submit the form" Done. This is not a demo, it is production-ready. ↳ Turn any SaaS into an AI copilot in minutes ↳ Smart form filling for ERP, CRM, admin systems ↳ Voice commands and accessibility built in ↳ Multi-page agent tasks via Chrome extension ↳ MCP server support for external control ↳ Bring your own LLM (Qwen, GPT, Claude, anything) Every founder building AI features just got a shortcut. Every developer manually building copilots just got replaced. The integration looks like this: That's it. Your app now has an AI agent.

CHINA JUST LEAKED THE FUTURE OF WEB APPS. Alibaba open-sourced PageAgent and 99% of SaaS founders are sleeping on this. It's a JavaScript AI agent that lives INSIDE your webpage. Users control your entire interface with natural language. ↳ No browser extensions needed, screenshots or multi-modal LLMs, headless browser setup, and also no backend rewrite required Just drop it in your HTML with ONE line of code. What took 20 clicks now takes one sentence. "Click login, fill in my credentials, submit the form" Done. This is not a demo, it is production-ready. ↳ Turn any SaaS into an AI copilot in minutes ↳ Smart form filling for ERP, CRM, admin systems ↳ Voice commands and accessibility built in ↳ Multi-page agent tasks via Chrome extension ↳ MCP server support for external control ↳ Bring your own LLM (Qwen, GPT, Claude, anything) Every founder building AI features just got a shortcut. Every developer manually building copilots just got replaced. The integration looks like this: That's it. Your app now has an AI agent.

Kanika

333,049 次观看 • 2 个月前

The Visual Studio Code insiders version that just shipped and will ship in the next few days will come with an insane amount of new capabilities. A few highlights: - You can now run sub-agents in parallel. Yes, really. I even attached a video. - Major UX improvements for sub agents, especially visible in the chat window - A new search tool wrapped as a sub-agent that iteratively runs multiple search tools: semantic_search, file_search, grep_search Which connects nicely to the point above: multiple searches running in parallel, efficiently and fast - Anthropic’s Message API is now enabled by default - You can choose the model for the cloud agent (three available, all premium) - Extended thinking support when using the Claude cloud agent This is part of the broader multi-vendor cloud support under AgentsHQ I wrote about a few weeks ago - Tasks sent to the background agent (basically the CLI tool) now always run in isolation, each with its own git worktree - In a multi-repo workspace, assigning a task to a cloud agent prompts you to choose the target repo Same behavior when opening an empty workspace with no repo - Support for building an external index for files not supported by GitHub’s default indexing - UI/UX improvements for starting new sessions and switching between local / background / cloud agents - Skills are now first-class citizens, just like prompt files, with better UX indicating when a skill is loaded - Improved API for dynamic contribution of prompt files New V2 includes skills as part of the model. Curious to see the extensions that will leverage this - Finally, initial support for showing context usage percentage per session - Skills are enabled by default - Resizable chat window and session view. Small thing, but it was driving me crazy 😁 - A new integrated browser meant to replace the old simple browser Maybe the beginning of real browser use? - Better UI/UX for token streaming in chat - Ability to index external files not supported by GitHub There’s a lot more. Some of it hasn’t fully landed yet, but everything that has is already in Insiders. The next stable release should drop in early February. As usual, I’m just shocked by the volume of features this team ships every month. After the holiday slowdown, this one is shaping up to be a wild release.

The Visual Studio Code insiders version that just shipped and will ship in the next few days will come with an insane amount of new capabilities. A few highlights: - You can now run sub-agents in parallel. Yes, really. I even attached a video. - Major UX improvements for sub agents, especially visible in the chat window - A new search tool wrapped as a sub-agent that iteratively runs multiple search tools: semantic_search, file_search, grep_search Which connects nicely to the point above: multiple searches running in parallel, efficiently and fast - Anthropic’s Message API is now enabled by default - You can choose the model for the cloud agent (three available, all premium) - Extended thinking support when using the Claude cloud agent This is part of the broader multi-vendor cloud support under AgentsHQ I wrote about a few weeks ago - Tasks sent to the background agent (basically the CLI tool) now always run in isolation, each with its own git worktree - In a multi-repo workspace, assigning a task to a cloud agent prompts you to choose the target repo Same behavior when opening an empty workspace with no repo - Support for building an external index for files not supported by GitHub’s default indexing - UI/UX improvements for starting new sessions and switching between local / background / cloud agents - Skills are now first-class citizens, just like prompt files, with better UX indicating when a skill is loaded - Improved API for dynamic contribution of prompt files New V2 includes skills as part of the model. Curious to see the extensions that will leverage this - Finally, initial support for showing context usage percentage per session - Skills are enabled by default - Resizable chat window and session view. Small thing, but it was driving me crazy 😁 - A new integrated browser meant to replace the old simple browser Maybe the beginning of real browser use? - Better UI/UX for token streaming in chat - Ability to index external files not supported by GitHub There’s a lot more. Some of it hasn’t fully landed yet, but everything that has is already in Insiders. The next stable release should drop in early February. As usual, I’m just shocked by the volume of features this team ships every month. After the holiday slowdown, this one is shaping up to be a wild release.

Oren Melamed

29,555 次观看 • 7 个月前