Hermes Agent_ 99+ Use Cases!

Sanny Vanjara

21h • General discussion

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Most people still think AI agents are just chatbots with better prompts.

Hermes Agent changes that completely.

This thing doesn’t just answer questions… it actually learns how you work over time.

And once you understand what people are building with it right now, you realize where AI is heading next.

Hermes Agent is an open-source AI agent framework from Nous Research. But unlike normal AI tools that forget everything after each chat, Hermes has persistent memory, self-improving skills, multi-agent workflows, and cross-platform messaging built in.

That means your AI assistant actually gets smarter the more you use it.

Not theoretically.

Literally.

People are already running Hermes on Raspberry Pis, cheap VPS servers, old Mac Minis, and even Android phones using Termux. Then they connect it to WhatsApp, Telegram, Discord, Slack, iMessage, Signal, email, Microsoft Teams, and more.

So instead of opening another AI app…

You just text your AI assistant like a real person.

That’s the first thing that makes Hermes different.

The second thing is the learning loop.

Hermes watches how you work, builds reusable skills automatically, and improves workflows over time. So the fifth time you run a task, the agent often performs better than you would manually.

That’s the part most people completely miss.

This isn’t static AI.

It evolves.

Here are a few real examples people are already running with Hermes Agent.

One user built a family assistant shared across WhatsApp. Three family members all using the same Hermes system for different tasks.

Another creator pointed Hermes at a folder of old blog posts and video scripts. The agent learned his tone, formatting style, and preferred emojis… then started writing content that sounded almost identical to him.

Another setup automatically researches trending AI stories every Monday morning, writes summaries, suggests content ideas, and stores everything as reusable skills so the workflow improves every single week.

That’s insane.

And developers are taking this even further.

Some people are running 10–12 Hermes agents simultaneously.

One agent researches.

One codes.

One tests.

One reviews.

One handles QA.

The agents coordinate together automatically.

There are users building fully automated software pipelines where the AI plans features, writes code, tests bugs, fixes failures, and ships updates without constant supervision.

But honestly, the business workflows are where this gets really practical.

People are using Hermes for inbox summaries, CRM updates, inventory tracking, client onboarding, project management, AI content systems, research automation, meeting notes, and customer support.

One team connected Hermes to Google Meet so every meeting gets transcribed and summarized automatically.

Another user connected Apple Health data and had Hermes analyze sleep patterns using Python scripts the agent wrote itself on demand.

And because Hermes supports local AI models through LM Studio or Ollama, sensitive business data never has to leave your machine.

That’s a huge deal for privacy.

The integrations are also wild.

Hermes connects with email, Slack, Discord, Telegram, Obsidian, Home Assistant, GitHub, local markdown systems, and even cross-agent memory pools where multiple AI systems share the same context.

One workflow I really like is the daily briefing setup.

You simply tell Hermes:

“Every morning at 9AM, check Hacker News and summarize the top AI stories into Telegram.”

Done.

Another strong use case is content style training.

Feed Hermes your old articles, newsletters, sales pages, or tweets… and now your AI writes in your exact voice consistently.

No retraining every session.

No copy-pasting context endlessly.

The memory stays.

And this is where Hermes feels fundamentally different from tools like ChatGPT.

Most AI tools are transactional.

You ask.