Hermes Agent: 99+ Use Cases!

本站添加: 2026-05-09

[00:00:00]Hermes Agent 99 plus use cases you need to see right now. What if there was an AI agent that actually got smarter the longer you used it? Not just another chatbot, not just a coding tool stuck inside your editor. Real agent that lives on a tiny server, talks to you on WhatsApp, and keeps building skills on its own. Already exists. Most people have no clue. Hey, I'm the digital avatar of Julian Goldie. I help people learn AI tools and actually use them in their work. And today I'm walking you through Hermes agent from Nous Research.

[00:00:28]There are over 99 real use cases people are running with this thing. I'm going to show you the ones that matter most, the setups that save hours every day, clever workflows you can copy this week, and the one feature that changes everything about how this agent works compared to anything else out there.

[00:00:43]Stick with me because by the end you'll have a clear picture of what to build first. Let me start with the basics so you understand what you're working with.

[00:00:49]Hermes agent is an open-source AI agent built by Nous Research. What makes it different is the built-in learning loop.

[00:00:55]That means it creates its own skills from your conversations, improves those skills while you use them, remembers things across sessions, and it builds a deeper understanding of who you are over time. It's not stuck on your laptop. You can run it on a tiny VPS. You can run it on a Raspberry Pi. You can run it on a cheap Android phone using Termux. You can run it on an always-on Mac at home.

[00:01:14]And here's the part that hooks most people. You don't talk to it through some clunky web app. You talk to it on Telegram, Discord, Slack, WhatsApp, Signal, Message, Email, Microsoft Teams, even Home Assistant. 15 plus messaging platforms all running through one gateway. So your agent feels like a person you can text from anywhere. Now let me get into what people are actually building with it. I went through the official user stories page on the hermesagent.doc site. 99 real stories, your GitHub post, your videos, your Reddit threads. Let me break down the categories so you can find ideas you can use. Category one, personal assistant. This is where most people start. Someone shared that he set up one Hermes agent for his entire family, three family members, all using it on WhatsApp, all using it for completely different things. Another user runs Hermes on his Mac Studio at home and talks to it through iMessage.

[00:02:03]He can text his assistant from his iPhone, iPad, Mac, or Apple Watch. The assistant can even see it inside group chats with his friends, naturally.

[00:02:10]Someone else uses it to organize notes into Obsidian, plan his week, and help fix bugs in his home automation setup.

[00:02:16]There's a user running Hermes on a Pi 4 as a home server. The agent saves his preferences while it works. He uses it as a central brain shared across all his devices. And here's a sweet one. Dad asked Hermes to write a little tale for his daughter. A day later, he asked again. The agent came back with a very similar story, same protagonist name.

[00:02:34]That'll be told. That's the persistent memory in action, category two.

[00:02:38]Development workflow. This is where Hermes really shows its power. There's a guy named Technium who literally runs 12 Hermes agent instances every day in parallel. They build Hermes itself.

[00:02:49]Another user built an auto build workflow. A main agent breaks a plan into phases. Coder agent implements each phase. A QA agent tests it. Plan, implement, test, fail, repair, ship.

[00:03:00]Fully automated. Someone on LinkedIn switched to Hermes from other agents he was experimenting with. In a single day, he built and launched five small applications. He says what made the difference was that the agent self-learns. Another developer ran a long-term test. By day 10, the agent knew his code base better than he did.

[00:03:16]Learned which files to check first, what patterns to flag, how to format the output, all from watching him work.

[00:03:22]There's even a tool called Skill Factory that watches your workflow silently and writes new reusable skills automatically. So, every time you do a task, the agent gets better at it next time without you doing anything.

[00:03:32]Category three, content creation. If you make videos, write articles, post on social, or do anything creative, this gets exciting. One user built a workflow where Hermes drafts blog posts in his exact writing voice. He told the agent to read his published articles before drafting anything new. The agent now writes content that sounds like him.

[00:03:50]Another creator pointed Hermes at a folder of his old video scripts. The agent analyzed his style, started producing tweets in his voice, saved his preferences automatically. He started a brand new session and tested it. The agent remembered everything including his preferred emojis. A YouTuber set up a weekly job. Every Monday at 9:00 in the morning the agent researches the top three trending AI tools that would make a good tutorial video. Then it saves what it learned as a new skill. So next week is even better at the same task.

[00:04:17]Another creator built a YouTube title generator skill. Five search optimized titles, five browse style titles, five hybrid titles, all from one prompt. Now I want to pause here for a second. When I first started using all these AI tools, I was overwhelmed. Way too many options. Most of them looked good in demos but fell apart in real work.

[00:04:35]That's when I created this community called AI Profit Boardroom with over 2,000 members all focused on learning AI together and sharing what actually works. Taught me which workflows save time versus which ones waste it. The community shares real use cases and practical implementations. If you're serious about using AI to improve your work and skills, check it out. Link in description. Someone uses Hermes for live inventory tracking. The agent's persistent memory and real-time inputs make it perfect for ops work where context matters. Another user runs a printing factory. Long conversations were making the agent slow. So he built a custom skill called task centric memory. It auto categorizes tasks into different domains. Completed tasks get compressed into summary cards. Now the agent stays fast and focused. Another team auto transcribes Google Meet calls so they can focus on the conversation instead of taking notes. They control the agent from Microsoft Teams.

[00:05:27]Sensitive client data never leaves the machine because they use local AI models through LM Studio. Category five, the integrations are wild. This is what surprised me most. Hermes plugs into almost everything. There's an integration that gives your agent its own email inbox. No complicated setup.

[00:05:43]Just plug in Agent Mail and it works.

[00:05:45]There's a web chat interface with dark and light themes, persistent memory, per session chat history, mobile and desktop responsive, Versel sandbox back end. So, the agent runs in cloud micro VMs that snapshot when idle. Cross agent memory.

[00:05:59]Your Hermes agent and your other coding agents can share the same memory pool.

[00:06:03]Category six, research workflows. One user built a daily research brief workflow. The agent watches the AI space, picks out useful signals, writes briefs, suggests content angles, tracks what he ignores, keeps improving its own workflow, delivers daily through Discord, Slack, Notion, email, Obsidian, and local markdown files. Someone else built a self-improving knowledge wiki. A Telegram bot acts as a second brain. The agent maintains it. The wiki grows over time. The agent is the librarian.

[00:06:30]Another user pulled Apple health data, found his sleep average was just over 7 and 1/2 hours. The agent wrote the Python on the fly to do it. Category seven, privacy and self-hosting. This matters for anyone working with sensitive material. One user runs Hermes self-hosted on single edge GPU with a 4 billion parameter Gemma model. He works with legal documents he can't send to third-party APIs. So, everything stays local. Another setup uses Tailscale for secure remote access without exposing any ports. Now, let me hit you with the workflows I think are most useful for the average person. Workflow one, daily news briefing. Tell the agent to check Hacker News every morning at 9:00. Pull the top AI stories. Send them to your Telegram.

[00:07:09]Workflow two, inbox summary. Every weekday at 9:00, summarize my inbox and post it to Slack. Hermes turns natural language into a scheduled task. No crontab editing needed. Workflow three, content style training. Point the agent at your past writing. Let it learn your voice. Now, everything it drafts sounds like you. Workflow four, skill building loop. Do a task once. Let the agent watch. Next time it remembers how to do it. By the fifth time it's better than you at it. Workflow five, multi-platform assistant. Set up the agent on Telegram and Discord and email all at once. One agent, everywhere you are. Same memory across all of them. Workflow six, auto research for content. Tell it to find the top three trending topics in your niche every Monday. Save the approach as a skill. Let it improve over time.

[00:07:53]Workflow seven, project context files.

[00:07:56]Drop a context file into your project folder. The agent reads it every conversation, so it always knows your preferences and your project setup.

[00:08:02]Workflow eight, this mode, real-time voice interaction in the terminal, on Telegram, on Discord. Talk to your agent like you talk to a friend. Workflow nine, sub-agent delegation. The agent can spawn other agents in isolation.

[00:08:15]Each one handles a different part of the work in parallel. Saves serious time.

[00:08:19]Workflow 10, skills marketplace. Browse the agent skills site, grab community-made skills, add them to your agent. You're not building from scratch.

[00:08:27]Big lesson here is simple. Most AI tools are static. You ask. They answer.

[00:08:33]They forget you tomorrow. Hermes is different because it actually grows.

[00:08:36]Build skills from your work. It remembers your preferences. Get sharper the more you use it. That's the loop that makes it different from anything else. And the best part, it's open source. T license. You own the setup.

[00:08:48]You control the data. You can run it however you want. If you're new to all this, I'd say start small. Pick one workflow from this video. Get it running. Let the agent learn how you work. Then add a second skill, then a third. In a few weeks, you'll have a personal AI that actually understands your work better than any general chatbot ever could. If you're looking to dive deeper into AI tools and actually implement them in your work, I recommend AI Profit Boardroom.

[00:09:12]Thousand people learning how to use AI effectively.

[00:09:15]Shares real experiences. What's working?

[00:09:17]What's not? Which tools are worth your time? Which ones to skip? No hype, just solid information and practical guidance from people doing the work. It's helped me stay on top of updates and figure out how to actually apply them. Link in description if you want to check it out.

[00:09:30]If you want the full process, SOPs, and 100 plus AI use cases like this one, join the AI Success Lab. Links in the comments and description. You'll get all the video notes from there, plus access to our community of 58,000 members who are crushing it with AI. That's it for this one. Hermes Agent is one of the most interesting open-source AI projects right now. Try it.

[00:09:52]See where it takes you. Talk soon.