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Hermes Agent vs OpenClaw using Qwen 35B Local Model We asked agents to scrape GitHub star history for both tools, find what caused the growth spikes, build a live dashboard in the browser. MacBook Pro M5 Max 64Gb OpenClaw: 203k tokens, 12m 01s - wrote a bash script Hermes:...

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604,081 görüntüleme • 1 ay önce •via X (Twitter)

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Atomic Bot put Hermes and OpenClaw head-to-head on the exact same task, running the same model (Qwen 3.6 35B) with the same goal: analyzing GitHub history, mapping growth spikes, and shipping a live dashboard in the browser. Key metrics to watch for 👀 > Time to complete the task > Tokens spent > Quality of the final result (dashboard in browser)
0:15

Atomic Bot put Hermes and OpenClaw head-to-head on the exact same task, running the same model (Qwen 3.6 35B) with the same goal: analyzing GitHub history, mapping growth spikes, and shipping a live dashboard in the browser. Key metrics to watch for 👀 > Time to complete the task > Tokens spent > Quality of the final result (dashboard in browser)

🚨 AI News | TestingCatalog

141,898 görüntüleme • 1 ay önce

asked Hermes Agent and OpenClaw to scrape our site and send a report. using DeepSeek V4 from our API. OpenClaw: 15k token, 2min 48 sec. wrote a bash script. Hermes: 36 token, 8 min 06 sec. wrote a SKILL.md. runs itself next time.
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asked Hermes Agent and OpenClaw to scrape our site and send a report. using DeepSeek V4 from our API. OpenClaw: 15k token, 2min 48 sec. wrote a bash script. Hermes: 36 token, 8 min 06 sec. wrote a SKILL.md. runs itself next time.

GMI Cloud

49,471 görüntüleme • 1 ay önce

Introducing agent-browser chat agent-browser is now a browser agent. → One-shot: agent-browser chat "open google, search for dogs" → Interactive: agent-browser chat → Built-in AI chat in the dashboard → Execute any agent-browser command → Use agent-browser as a sub-agent
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Introducing agent-browser chat agent-browser is now a browser agent. → One-shot: agent-browser chat "open google, search for dogs" → Interactive: agent-browser chat → Built-in AI chat in the dashboard → Execute any agent-browser command → Use agent-browser as a sub-agent

Chris Tate

90,926 görüntüleme • 2 ay önce

Hermes Agents aren’t making it easy for OpenClaw. the reason Hermes took off needs to be studied, some personal thoughts: > Hermes won the lottery for timing. OpenClaw proved the demand but took so much hit for being the first. the take-off was huge but it went down just as fast. > the development seems more disciplined than 100s of commits made for OpenClaw. and in general the roadmap looks nicer. > Hermes seems to lock in the “continuity” of the agents best. it searches past sessions, creates skills and updates them.
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Hermes Agents aren’t making it easy for OpenClaw. the reason Hermes took off needs to be studied, some personal thoughts: > Hermes won the lottery for timing. OpenClaw proved the demand but took so much hit for being the first. the take-off was huge but it went down just as fast. > the development seems more disciplined than 100s of commits made for OpenClaw. and in general the roadmap looks nicer. > Hermes seems to lock in the “continuity” of the agents best. it searches past sessions, creates skills and updates them.

ℏεsam

29,288 görüntüleme • 22 gün önce

Hermes Agent can now scrape, search, and interact with the web using Firecrawl Nous Research Enable it during setup to give Hermes the complete web toolkit 🔥
0:13

Hermes Agent can now scrape, search, and interact with the web using Firecrawl Nous Research Enable it during setup to give Hermes the complete web toolkit 🔥

Firecrawl

161,239 görüntüleme • 2 ay önce

Day 35 of speed running AI and becoming an expert as a noob ✅ Migrated OpenClaw → Hermes ✅ Shipped a video content agent ✅ Worked on Real Estate startup Hermes Agent + GPT 5.5 is a big upgrade from my old OpenClaw setup. Let’s run it up again and learn more today gang 🫡
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Day 35 of speed running AI and becoming an expert as a noob ✅ Migrated OpenClaw → Hermes ✅ Shipped a video content agent ✅ Worked on Real Estate startup Hermes Agent + GPT 5.5 is a big upgrade from my old OpenClaw setup. Let’s run it up again and learn more today gang 🫡

BentoBoi

58,768 görüntüleme • 1 ay önce

We built the best codebase search to give any agent grounded information from GitHub repos. Introducing Sandbox Search. Point it at any repo, and we’ll spin up a secure coding agent in its own sandbox to do research for you. Use inside claude code, openclaw, cursor, and more.
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We built the best codebase search to give any agent grounded information from GitHub repos. Introducing Sandbox Search. Point it at any repo, and we’ll spin up a secure coding agent in its own sandbox to do research for you. Use inside claude code, openclaw, cursor, and more.

Arlan

12,412 görüntüleme • 2 ay önce

Crazy...Web search is now free for every AI agent. I now use TinyFish my primary search for my OpenClaw and Hermes Agents. And I pay $0 for that.
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Crazy...Web search is now free for every AI agent. I now use TinyFish my primary search for my OpenClaw and Hermes Agents. And I pay $0 for that.

Shubham Saboo

69,583 görüntüleme • 1 ay önce

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.
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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.

Akshay 🚀

143,942 görüntüleme • 1 ay önce

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.
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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.

Kanika

59,580 görüntüleme • 25 gün önce

You can now delegate tasks to GitHub Copilot coding agent from any page on GitHub 🤖 Open the new Agents panel in one click, write a simple prompt, then hit Enter. GitHub Copilot works in the background, and opens a PR for your review. No interruptions to your workflow required. ✅
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You can now delegate tasks to GitHub Copilot coding agent from any page on GitHub 🤖 Open the new Agents panel in one click, write a simple prompt, then hit Enter. GitHub Copilot works in the background, and opens a PR for your review. No interruptions to your workflow required. ✅

GitHub

112,727 görüntüleme • 10 ay önce

spent the whole night coding a live feed for Believe launches see all latest tokens, creators and creator stats powered by pro x api⚡️ Featured tokens, token creation dashboard like pump.fun coming soon! try it out 👈
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spent the whole night coding a live feed for Believe launches see all latest tokens, creators and creator stats powered by pro x api⚡️ Featured tokens, token creation dashboard like pump.fun coming soon! try it out 👈

Halo

72,885 görüntüleme • 1 yıl önce

This Quant bot turned $1.4K → $203K in 3 months using a self-trained ML model i traced his 55K predictions → uploaded into Codex 5.5 → connected Hermes agent installed it on a VPS + connected Binance + Synth ML models API 3 days → 343% ROI run trading agent in 5 steps: • rent a VPS on Hetzner - $5.99 • install Hermes CLI using one-liner code - free • connect Codex 5.5 + TG bot + Polymarket API • provide Synth Data API's for crypto predictions • sent Hermes step-by-step prompts from article start small 1-2$ give Hermes least {50-100} trades to build self-learning skills based on Synth ML models self-learning agent + crypto predictions models = best combination for building algo-trading setup bot profile: s tart copy-trading it with even with $5 using Ares: read full article below to build your first trading agent ↓
0:10

This Quant bot turned $1.4K → $203K in 3 months using a self-trained ML model i traced his 55K predictions → uploaded into Codex 5.5 → connected Hermes agent installed it on a VPS + connected Binance + Synth ML models API 3 days → 343% ROI run trading agent in 5 steps: • rent a VPS on Hetzner - $5.99 • install Hermes CLI using one-liner code - free • connect Codex 5.5 + TG bot + Polymarket API • provide Synth Data API's for crypto predictions • sent Hermes step-by-step prompts from article start small 1-2$ give Hermes least {50-100} trades to build self-learning skills based on Synth ML models self-learning agent + crypto predictions models = best combination for building algo-trading setup bot profile: s tart copy-trading it with even with $5 using Ares: read full article below to build your first trading agent ↓

Movez

28,459 görüntüleme • 1 ay önce

UnifAI Skills are now live on OpenClaw!! Traders and Developers can now integrate UnifAI-powered skills directly into their agents, unlocking more powerful and composable capabilities within the OpenClaw ecosystem. UnifAI skills are automatically pre-installed for users who deploy their OpenClaw🦞 AI Agents with UniClaw Build smarter agents. Ship faster. 🤖 GitHub repo -
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UnifAI Skills are now live on OpenClaw!! Traders and Developers can now integrate UnifAI-powered skills directly into their agents, unlocking more powerful and composable capabilities within the OpenClaw ecosystem. UnifAI skills are automatically pre-installed for users who deploy their OpenClaw🦞 AI Agents with UniClaw Build smarter agents. Ship faster. 🤖 GitHub repo -

UnifAI Network

102,987 görüntüleme • 3 ay önce

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)
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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)

Chris

34,473 görüntüleme • 2 ay önce

Stop searching, start asking. 💡 The new GitHub Copilot search experience is live on GitHub Docs! 🎉 Ask a question, and Copilot will guide you to the solution. ✅ Get answers faster and build sooner. 🚀 Find out more.👇
0:12

Stop searching, start asking. 💡 The new GitHub Copilot search experience is live on GitHub Docs! 🎉 Ask a question, and Copilot will guide you to the solution. ✅ Get answers faster and build sooner. 🚀 Find out more.👇

GitHub

46,650 görüntüleme • 11 ay önce

Compared Qwen3.6 35B and 27B in the same conditions with Google TurboQuant Device: MacBook Pro M5Max 64GB RAM Outputs characteristics: Qwen3.6 35B: 6672 tokens, 2m 10s, 65 tok/s Qwen3.6 27B: 7344 tokens, 5m 22s, 24 tok/s Conclusion: Both models were asked to draw waves using HTML, 35B responded quickly but the result feels weak and messy, while 27B took more time and delivered a much cleaner and more consistent result, because it is built for thinking and planning, so it works better on tasks that need structure, overall 27B is a better choice for tasks where planning matters, while 35B is more suitable for everyday use when you just need a fast response
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Compared Qwen3.6 35B and 27B in the same conditions with Google TurboQuant Device: MacBook Pro M5Max 64GB RAM Outputs characteristics: Qwen3.6 35B: 6672 tokens, 2m 10s, 65 tok/s Qwen3.6 27B: 7344 tokens, 5m 22s, 24 tok/s Conclusion: Both models were asked to draw waves using HTML, 35B responded quickly but the result feels weak and messy, while 27B took more time and delivered a much cleaner and more consistent result, because it is built for thinking and planning, so it works better on tasks that need structure, overall 27B is a better choice for tasks where planning matters, while 35B is more suitable for everyday use when you just need a fast response

atomic.chat

55,417 görüntüleme • 2 ay önce

Do you know what your OpenClaw agents are actually doing? If not, bookmark this. Here is a complete 3D neural command center for monitoring agents, nodes, logs, and live activity in real time you can build yourself with this prompt. FULL PROMPT: I’ll upload a GitHub soon with the working files for all the projects I’ve shared so far. Notis on.
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Do you know what your OpenClaw agents are actually doing? If not, bookmark this. Here is a complete 3D neural command center for monitoring agents, nodes, logs, and live activity in real time you can build yourself with this prompt. FULL PROMPT: I’ll upload a GitHub soon with the working files for all the projects I’ve shared so far. Notis on.

Jayden ⛩️

51,321 görüntüleme • 3 ay önce

I just built a Claude Cowork skill that turns your Google Ads data into a visual performance dashboard in 60 seconds 🤯 One prompt → campaign breakdowns, CPA trends, spend vs conversions charts, and hourly conversion patterns, all rendered as an interactive HTML dashboard you open in Chrome. All inside Claude Cowork. Perfect for DTC brands and agencies who are pulling Google Ads data into spreadsheets every week, manually building charts, and spending an hour formatting a report that's outdated by the time you send it. If you're managing Google Ads and your weekly reporting workflow looks like this — export a CSV, open Google Sheets, build a pivot table, copy the numbers into a slide deck, manually create charts, format everything, realize you forgot a campaign, start over ... This skill does the whole thing in one prompt: → Connects to your live Google Ads data via MCP → Pulls spend, conversions, CPA, ROAS, CTR across every campaign → Builds an interactive HTML dashboard → Summary cards at the top: total spend, total conversions, avg CPA, avg ROAS → Bar chart comparing spend vs conversions by campaign → CPA trend line over the last 30 days → Campaign table ranked by performance, color-coded green/yellow/red → Opens in Chrome: hover over charts, compare campaigns, screenshot for your team No spreadsheets. No manual chart building. No hour-long formatting sessions. What you get: → A visual dashboard from live data in under 60 seconds → Campaign performance you can actually see, not just read in a table → CPA trends that show you where things are heading, not just where they are → A dashboard you can screenshot and drop into Slack, a client report, or a team standup → Reusable — run it weekly and the data updates automatically One prompt. Live data. A finished dashboard you open in your browser. I put together a playbook with the full skill file, the setup, and the exact prompts to customize the dashboard for your account. Want it for free? > Like this post > Comment "DASH" And I'll send it over (must be following so I can DM)
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I just built a Claude Cowork skill that turns your Google Ads data into a visual performance dashboard in 60 seconds 🤯 One prompt → campaign breakdowns, CPA trends, spend vs conversions charts, and hourly conversion patterns, all rendered as an interactive HTML dashboard you open in Chrome. All inside Claude Cowork. Perfect for DTC brands and agencies who are pulling Google Ads data into spreadsheets every week, manually building charts, and spending an hour formatting a report that's outdated by the time you send it. If you're managing Google Ads and your weekly reporting workflow looks like this — export a CSV, open Google Sheets, build a pivot table, copy the numbers into a slide deck, manually create charts, format everything, realize you forgot a campaign, start over ... This skill does the whole thing in one prompt: → Connects to your live Google Ads data via MCP → Pulls spend, conversions, CPA, ROAS, CTR across every campaign → Builds an interactive HTML dashboard → Summary cards at the top: total spend, total conversions, avg CPA, avg ROAS → Bar chart comparing spend vs conversions by campaign → CPA trend line over the last 30 days → Campaign table ranked by performance, color-coded green/yellow/red → Opens in Chrome: hover over charts, compare campaigns, screenshot for your team No spreadsheets. No manual chart building. No hour-long formatting sessions. What you get: → A visual dashboard from live data in under 60 seconds → Campaign performance you can actually see, not just read in a table → CPA trends that show you where things are heading, not just where they are → A dashboard you can screenshot and drop into Slack, a client report, or a team standup → Reusable — run it weekly and the data updates automatically One prompt. Live data. A finished dashboard you open in your browser. I put together a playbook with the full skill file, the setup, and the exact prompts to customize the dashboard for your account. Want it for free? > Like this post > Comment "DASH" And I'll send it over (must be following so I can DM)

Mike Futia

38,672 görüntüleme • 2 ay önce

we built an extremely good code search agent. it’s called tracer, and it can search across the entire github in less than 5 minutes and come back with a clean report. you can try it by running 'bunx nia-wizard'
0:12

we built an extremely good code search agent. it’s called tracer, and it can search across the entire github in less than 5 minutes and come back with a clean report. you can try it by running 'bunx nia-wizard'

Arlan

91,382 görüntüleme • 3 ay önce