Hermes Agent Has 237 Real Use Cases Now

0:00In this video, I'm going to be talking about Hermes Agent and why I think the conversation around it just changed. Because for the last couple weeks, Hermes has been this thing where people either love it, hate it, or immediately compare it to Open Claw. And that's fine. Competition is good, but there is a big difference between a tool being loud on the internet and a tool having actual user receipts. And Hermes just crossed into the receipt stage. The official Hermes Agent docs now have a user stories page with 237 real stories across 15 categories and 11 different source types. X posts, GitHub issues, Reddit threads, Hacker News, YouTube, blogs, podcasts, LinkedIn, Discord. And

0:46the page literally says these are real posts, issues, videos, or gists where people describe how they use Hermes. That matters because once a tool gets enough real use cases, the argument stops being is this thing legit? The argument becomes where is it actually useful? And that is the level Hermes is at right now. I checked the repo this morning, too. News research/hermes.agent is sitting around 160,000 GitHub stars, over 26,000 forks, more than 12,000 open issues, and it was pushed today. So, this is not some abandoned weekend project. It is moving fast. And if you're an Open Claw user or you're

1:31building any kind of personal AI agent system, you should pay attention. Not panic, not switch everything overnight, pay attention. Because the best builders don't pick teams like sports fans. They steal the best patterns. So, let's talk about what these stories actually show. The first thing that jumps out is that Hermes is not only being used for coding. That is important because most AI agent tools get trapped in the developer bubble. The demos are always fix this bug, make this PR, write this test, run this command. Cool. Useful, but normal Real quick, before we keep going, if you're watching this and you want to actually build with some of these tools, not just watch videos about them, then you're going to want to check out our community down below, Shipping

2:16School. We have a full Claude code course, a full open Claude course, and four live bootcamps every single week, where we actually help you get set up from scratch. Like actually set this thing up, not just watch a tutorial and figure it out by yourself. And we also provide one-on-one coaching, so you could book a call with me. We can share screens, and I can help you get Claude code or open Claude running on your machine. That's it, no fluff. I built this community because watching YouTube's only gets you so far. We launched it just 3 days ago, and we have over 55 members. You need people around you who are actually building, people who hold you accountable, and coaches who can help you when you get stuck. I'll put the link in the description down below. Get in now before the price goes up. Normal people don't wake up

3:02thinking about pull requests. They wake up thinking about email, calendar, notes, research, customers, files, marketing, boring business stuff. And Hermes has a lot of stories in that lane. One person told Hermes to Google them, build a landing page based on what it found, SSH into a VPS, upload the page, and text them when it was done. That is a full loop. Research, build, deploy, notify. That is what normal people think an AI agent should do. Not just answer a question, do the thing. Another story is a user running Hermes every weekday at 9:00 a.m. to summarize their inbox and post the result to Slack. Again, not glamorous, but that is

3:49the kind of workflow that actually survives. Nobody needs a cinematic demo of an agent ordering 14 pizzas with a fake browser. They need an agent that does the annoying daily thing before they sit down at the desk. Hermes has stories around daily journaling into Obsidian, managing tasks across Obsidian, Apple Calendar, and Signal. Running on a Raspberry Pi 5 24/7, running on a mini PC while Claude handles the deeper thinking. Running on a Kubernetes cluster for a daily cybersecurity and AI briefing. That's the pattern. Hermes is becoming a persistent worker. Not a chatbot, not a code auto-complete toy, a worker.

4:34And that is exactly why Open Claw users should care. Because Open Claw has always been strongest when you treat it like an operating layer for your life or business. Telegram, cron, skills, memory, tools, sub-agents, approvals, files, voice, browser, all of it. Hermes is attacking that same mental model. It wants to be the agent that learns you, remembers your workflows, and gets better as it runs. So yes, Hermes is a threat, but not in the lazy way people say threat. It is not a threat because it has a cooler logo or because someone posted a big star count. It is a threat because it is collecting real workflows from real builders, and those workflows teach the market what to expect from agents.

5:21Once people see one builder run a Hermes agent on a mini PC to handle email, browsing, forms, calendar updates, and cron jobs, they stop being impressed by a chatbot that writes a decent paragraph. The bar goes up. That helps Open Claw too, by the way. A rising bar is good if you're actually building serious systems. It is bad if you're selling wrapper demos. Another thing I noticed is how many Hermes stories are about connecting tools together. There is a self-hosted Google Drive replacement using Nextcloud and LibreOffice. There's a Turkish local skill pack with market data, Turkish news sources, daily briefing cards, and Telegram cron automation.

6:07There's a team using Hermes with Sourcegraph to index repos, Tenderly MCP to debug on-chain transactions, and protocol docs for internal support. There is a person who got tired of paying Perplexity API costs and built a low-cost research stack with seven MCPs, Sear XNG, and custom source selection. That is where agents become valuable. Not when they are smart in isolation, when they sit between tools. This is why I keep saying the money is not in generic chat. The money is in workflows. The money is in the agent knowing which tool to use, when to use it, what to remember, when to ask you, and when to stop. Hermes is clearly leaning into

6:52that. The official use case page even breaks stories into categories like dev workflow, personal assistant, integrations, business ops, cost optimization, content creation, enterprise, research, messaging, privacy, trading, and marketing. That category spread matters more than any single demo. A single viral demo can be fake or cherry-picked. A big pile of weird specific workflows is harder to fake. And honestly, the weird ones are the most useful. A user building a local Sear XNG container shared across Hermes agents tells me more than a polished launch video. A user asking for DM-based approval gates for kid-facing Discord bots tells me more than a homepage

7:38headline. A user measuring that 73% of an API call was fixed overhead tells me builders are actually operating this thing hard enough to find the ugly parts. If you're struggling to keep up with content, what I'm about to save you about 40 days worth of work. I built something [music] called content machine. It's 10 AI agents that run on the open claw orchestration and they handle everything. Scripts, thumbnails, X posts, blogs, outreach, clips, news leaders, all of it. So, I went from 1,000 subscribers to 4,000 subscribers on YouTube in 7 days using this exact system. Every single morning I wake up and the content's already done. I spend maybe 15, 20 minutes reviewing and

8:23approving them and I move on with my day. [music] It works for any niche, fitness, finance, real estate, marketing, whatever you're building and it is 100% completely customizable to your [music] use case. So, you get the mission control dashboard, all of the cron jobs, everything I've built over the last 40 days helping me gain more and more people to subscribe and join the community. So, you plug in your own thing and it molds it to you, it learns how you talk and it writes so it doesn't sound like AI slop. $97 one time, it's not a subscription. [music] I'll put the link down below and you'll thank me later. That is a sign of a real tool. Real tools produce ugly feedback. Fake tools only produce perfect screenshots. Now, let's talk about the flashier

9:08examples because they are still useful. There is the weather trading bot story. A user said they turned $100 into $216 in less than 48 hours with a self-learning weather trading bot. Hermes scanned weather markets every 60 minutes, compared three forecast sources per location, bought undervalued temperature buckets, flipped for profit, reviewed what worked, wrote strategy notes, and adjusted next time. Do I think everyone should go build a weather trading bot today? No, absolutely not. The point is not the trade. The point is the loop. Observe, compare sources, act, review, write strategy notes, improve next time. That is the agent pattern.

9:54You can apply that to lead generation, content research, inventory pricing, customer support, ad testing, school community management, real estate listings, anything where the same repeats over and over and the agent can get better with memory. There is also the Higgs Field marketing studio story. Paste a product URL, Hermes scrapes the landing page, pulls winning ad hooks from Meta Ads Library and TikTok Creative Center in the same niche, and writes the brief in about 4 minutes. That one is directly relevant to builders because marketing is where a lot of vibe coders get stuck. They can ship the product now, they can make the app, they can connect Stripe, but then they freeze when they need ad angles, UGC scripts, landing page positioning,

10:40outreach, or social proof. If Hermes can reliably turn product pages into creative briefs, that is a serious business workflow. Open Claw can do that kind of thing, too, and that is why this should become a comparison point. Take the same product, run the workflow in Hermes, run the workflow in Open Claw, compare output quality, tool reliability, setup friction, cost, memory, approvals, and how easy it is to repeat tomorrow. That is the video I think people actually want, not fanboy arguments, real workflow comparisons. Another story I like is the Codex monitoring Hermes workflow. A builder used Codex with GPT-5 4 on

11:28extra high to watch Hermes agent-to-agent workflows live, catch where they broke, and fix them until they worked reliably. That is a very advanced pattern, one agent supervising another agent. And I think this is where everything is going. The future is not one magic AI doing everything perfectly. That is the fantasy version. The real version is multiple agents with different jobs. One does the work, one reviews the work, one watches logs, one handles approvals, one writes the summary, one updates memory. That sounds complicated until you realize that's already how human teams work. The difference is now a solo builder can create a small digital team on a Mac mini, a VPS, or a Raspberry Pi. So, what

12:16should you do with all this? Here is my honest take. If you're using Open Claw and it is working for you, don't abandon it because Hermes is trending. That's not how serious builders operate. But, you should study Hermes. Open the official user stories page. Find one workflow that looks close to your business, not the coolest workflow, the closest one. If you run a content business, look at the YouTube research cron, the ad brief workflow, the daily briefing examples. If you run a service business, look at the inbox, calendar, task, and lead gen examples. If you build software, look at the Codex monitoring workflow, MCP integrations, local research stacks, and team repo indexing. Then, recreate the workflow in

13:02your own stack, Hermes, Open Claw, whatever. The tool matters, but the pattern matters more. Also, be careful. The same thing that makes persistent agents powerful also makes them risky. When you connect email, calendar, files, browser sessions, SSH, Discord, Slack, and payments, you are not playing with a toy anymore. You are giving software access to your operating system and your business. So, approvals matter. Logs matter. Scope matters. Secrets matter. Backups matter. If you connect everything on day one and let it run wild, that's not brave. That's just sloppy. Start with read-only workflows. Start with summaries. Start with drafts. Start with one small recurring task.

13:49Then add write access after it earns trust. That is true for Hermes. That is true for Open Claw. That is true for any agent system. My final take is this. Hermes is not just hype anymore. 237 real user stories is a signal. 160,000 GitHub stars is a signal. Daily commits are a signal. But, the biggest signal is the shape of the workflows. People are not only asking Hermes questions. They are giving it jobs. And that is the whole game. If you're building with AI agents, don't waste time arguing in the comments about tool is king. Pick a real workflow. Run it. Measure it. Make it safer. Make it repeatable. Then compare.

14:34That's how you find out what is real. We'll see you in the next one. Be blessed.