Hermes – The AI Agent System Business Users Guide

Hermes Agent is an always-on AI helper you can run on your own computer or a cheap server. It remembers your work, can take action (not just chat), and can message you in Slack, Telegram, WhatsApp, or email. Nous Research, an open-source AI lab, released it in February 2026. Six months later it has about 230,000 GitHub stars, a desktop app, and a paid cloud option. Investors have been talking about a round around $1.5 billion, according to TechCrunch. Nous has not confirmed that number.

This post is for people who use ChatGPT or Copilot at work and want to know what “an AI agent” actually means, what Hermes is good for, and who is using it. It is based on Nous’s own docs, GitHub, TechCrunch, and what users have been posting on Reddit, X, and YouTube over the last month.

First, two names that get mixed up

Hermes started as a family of open language models from Nous Research, the same way some companies publish their own ChatGPT-style models. Those models still exist (Hermes 4 is the current chat family).

Hermes Agent is a different product: software that uses a language model, plus memory, tools, schedules, and chat apps, so the model can do work over days and weeks. Nous’s own docs warn that Hermes 4 is tuned for conversation, not for the fast tool-calling loop the agent needs. For agent work they point people at models such as Claude Sonnet, GPT-5.x, Gemini, or DeepSeek.

If someone says “we use Hermes,” ask which one they mean.

What an agent is, in plain language

A chatbot answers a question and forgets you when you close the tab.

An agent can:

• Keep a file of who you are and how you like things done
• Use tools: search the web, open a browser, run a script, read a folder, send a message
• Repeat a job on a schedule (“every weekday at 8am, send me a briefing”)
• Hand work to a second copy of itself, the way a manager assigns a task

Hermes Agent is that second kind of product. Official docs describe it as “the self-improving AI agent built by Nous Research.” You install it on a laptop, a $5 virtual server, or Nous’s hosted cloud. You talk to it in a terminal, a desktop app, or the chat apps you already use.

The software is MIT licensed (free to use and modify). You pay for the model behind it, and optionally for Nous Portal, which bundles hundreds of models plus web search, image generation, speech, and a cloud browser on one bill. Portal plans listed on portal.nousresearch.com run from a free tier up through Plus ($20/month), Super ($100), and Ultra ($200).

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Who built it

Nous Research grew out of a Discord community in 2022 and incorporated in 2023. The founders commonly named in coverage are Jeffrey Quesnelle (CEO/CTO), Ryan “Teknium” Teknium (head of post-training and the public face of the agent), Karan Malhotra (head of behavior), and Shivani Mitra. Earlier funding included Paradigm and others; Crunchbase-linked reporting puts prior capital around $70 million.

The culture still looks like an open-source lab, not a classic enterprise vendor. Releases land on GitHub. Teknium answers users on X. The v0.20.0 “Herald” release on August 3, 2026 listed roughly 3,650 commits, 1,400 merged pull requests, and 650+ contributors since the previous major version. A patch, v0.20.1, shipped August 13.

That speed is the product story and the risk. Hermes is moving faster than most companies’ IT review cycles.

How Hermes actually works (without the jargon)

Think of four layers.

1. A brain you choose. Hermes does not force you onto one AI vendor. You can point it at Anthropic, OpenAI, Google, OpenRouter, a model on your own GPU, or Nous Portal. Educator Tina Huang, whose 29-minute setup video has more than 250,000 views, said the usual advice is a strong hosted model such as Claude Sonnet, while she personally runs an open model on a Mac Studio because she uses the agent all day.

2. Memory that survives overnight. ChatGPT starts fresh. Hermes keeps notes across sessions: your projects, preferences, and how a past problem was solved. It can search old conversations. That is why people treat it less like a search box and more like a junior staffer who was here yesterday.

3. Skills, which are written playbooks. After you walk it through the same multi-step job a few times, Hermes can write a SKILL.md file: the steps, the pitfalls, how to check the result. Next time it loads that playbook instead of reinventing the work. Skills follow the open agentskills.io format, so they can be shared. This is the “learning loop” Nous markets. It does not rewrite Hermes’s core code. It writes instructions you can open and edit.

4. A gateway into real tools and real chat apps. One Hermes process can talk on Telegram, Discord, Slack, WhatsApp, Signal, email, Microsoft Teams, Google Chat, and a long list of China-market apps (Feishu, WeCom, DingTalk, QQ). It can also browse the web, run code in a sandbox, and fire a job on a timer. The line people in the community repeat is that the chat window is not the product. The always-on gateway is.

August’s Herald release added spoken conversation (you can interrupt it mid-sentence), a standard way for agents to talk to other agents (A2A), signed webhooks into your other systems, and a research mode that tries to tie claims to sources.

The jobs it is actually used for

The interesting part is not the feature list. It is that people leave it running.

Morning briefings and “don’t make me open ten tabs”

This is the most common pattern. You tell Hermes, in ordinary language, to scan a set of sources every weekday and send a short digest to Slack or Telegram. At CO/AI we have this running and it works.

An XDA-Developers write-up is a clear example: a daily 8am job pulls Reddit and Hacker News, ranks what is worth reading, and delivers a small queue. The same author dumped a zip of Computex emails into Hermes, got a verified itinerary (who to follow up with, what to ignore), and an calendar file. That is a business problem with a different label: trip logistics, vendor meetings, inbox pile-up.

CRM vendors have published the same shape for sales: a morning briefing of new leads, unpaid invoices, and tickets, posted to Slack, with the option to type “mark invoice INV-1208 as paid” in the same chat.

Competitive and market watching

Marketing teams already pay for tools that scrape competitor sites. Hermes users schedule the same work themselves: scrape a YouTube channel against industry news and flag content gaps; watch listings or competitor pricing; send a Monday report. One MindStudio demo had Hermes find Northwest London plumbers without websites and return three pitch-ready leads, running on a cheap CPU instance. Treat demos as demos. The pattern is real: recurring research that used to be an intern’s Monday.

A persistent coding partner, not a tab in the IDE

Developers use Cursor, Claude Code, and Copilot inside the editor. Hermes sits beside that stack. It remembers the repo’s conventions between days, can SSH into a machine, review another agent’s output, and keep a Kanban of unfinished work. On X, IBuzovskyi described putting Hermes, Claude Code, Codex, and Goose in one shared channel, each with a job, humans @-mentioning the right one. That is “small AI team,” not “smarter autocomplete.”

A Reddit user posted a full setup with 28 cron jobs and 30+ skills. That is an operations load, not a toy.

The assistant that lives in WhatsApp or Telegram

ChatGPT is an extra app. Hermes users keep putting it in the chat they already open. @EXM7777 wrote that three family members share one agent on WhatsApp, powered by a single expensive ChatGPT subscription, because it lives in the thread and does things unprompted. Founders use the same idea for a personal chief of staff: inbox digest before they open a laptop, voice notes from a phone, replies in Telegram.

A small but telling example from witcheer on X: someone had Hermes ping them on Telegram every 15 minutes until they confirmed they took medication. They had been missing doses a few times a week. Reminder apps were easy to ignore. The agent nagged until it got a confirmation. That is persistence, which is the actual product.

One person, several “employees”

Solo operators are the loudest business users. A thread on r/hermesagent this week was titled “I was exhausted running my startup alone, so I built an AI team using Hermes Agent.” @ones_07389 described four agents on one 32GB Ubuntu laptop: a default “PM” on Feishu, plus Dev, DevOps, and content agents, with a nightly self-learning job at 4:30am.

Bot Mode, in public beta as of August 13, makes that mental model official: each profile becomes a named bot with its own memory, skills, and schedule, and bots can message each other. Teknium posted a working video the day after xAI’s Grok Bot news. Community accounts treated that as the difference between a lab that ships and a company that waits for a roadmap.

Privacy-sensitive work on your own hardware

A large slice of the audience is people who will not paste client files or email archives into a public chatbot. Hermes can run a local model so the reasoning never leaves the machine. The XDA author still would not give the agent live access to a personal mailbox. They zipped what they needed and dropped it in chat. That is the right instinct for a business: the agent is powerful because it can touch files and networks. You decide what it is allowed to touch.

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Who the biggest users actually are

Nous has not published a Fortune 500 customer list. If a vendor pitch says “used by these logos,” ask for a named reference. What we can see in public is a very large practitioner community, plus Nous using the product on itself.

Nous Research internally. A May community roundup claimed Teknium runs a dozen Hermes instances in parallel for backend monitoring and post-training work. Whether the exact count is twelve or “a lot,” the lab is dogfooding the agent as production infrastructure, not a side demo.

Open-source developers, at unusual scale. NousResearch/hermes-agent had about 230,500 stars as of August 13, 2026, and was still adding on the order of 500 stars a day in recent GitTrend figures. That is consumer-app popularity on a developer tool. Star counts are not seats, and GitHub has a lot of drive-by stars. Even so, the contributor list on Herald (650+ people in one release window) is a better signal: people are patching it.

r/hermesagent and the Nous Discord. The subreddit is where weekly “what did you actually do with it?” threads live. Those threads matter more than launch posts. They are full of briefings, homelab admin, spreadsheets, Kubernetes, and “my Telegram bot got frozen.” Discord is where configs and breakage get discussed faster than Reddit.

YouTube operators who treat it as a daily driver. Tina Huang’s fundamentals video is the on-ramp a lot of non-researchers will see. Jack Roberts’s upgrade video has about 51,000 views. Peter Yang’s interview with Karan Malhotra is the founder-facing version. These people are not “the product.” They are how business-curious users find it.

OpenClaw migrants. OpenClaw (sometimes written Openclaw) went viral earlier in 2026 as a local agent you talk to from Telegram. Hermes shipped weeks later with built-in skills and a learning loop. Official docs include hermes claw migrate. Community write-ups compare them the way people compared Slack and Teams: same job, different defaults. Hermes is often described as less fiddly, with cron and memory built in. OpenClaw is often described as having more channels and a bigger plugin zoo. Some people run both.

Asia-Pacific operators. Gateway support for Feishu, WeCom, Weixin, DingTalk, QQ, and LINE is not a footnote. Japanese and Chinese X posts about Bot Mode and Portal model drops are a large share of recent chatter. There is a community WeChat bridge (HermesClaw) so Hermes and OpenClaw can share an account. If your company already lives in Feishu or WhatsApp, that is a better fit than a tool that only exists inside VS Code.

Privacy and homelab users. LocalLLaMA, self-hosted, and Home Assistant crowds use Hermes to turn a local model from a chat toy into something that runs scripts and jobs. They are not “enterprise,” but they are the people stress-testing reliability before IT does.

Karan’s jab at big-company wrappers. On August 13, co-founder karan4d posted, “i love all the hermes wrappers we’ve been seeing from the multi billion dollar companies!!!” That is not a customer case study. It is a hint that large vendors are packaging similar agent patterns, and that Nous wants the open core to stay the reference.

What you will not find, as of mid-August 2026, is a clean public roster of named banks, retailers, or governments running Hermes in production. The commercial motion is still “download it” plus Portal subscriptions at $20–$200, plus hosted cloud instances billed by the day. TechCrunch’s funding story is about converting GitHub fame into paid seats. That conversion is the open question, not a finished fact.

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What this is not

Hermes is not a replacement for your CRM, your help desk, or your ERP. It sits on top of them.

It is not a fully managed “AI employee” you can hand to a non-technical team with no one on call. The installer is good (a curl command or a desktop app). Day-two work is still skills, permissions, and “why did the Telegram bot get banned.” This week’s subreddit had that freeze thread. Messaging platforms do not love bots that look automated.

It is not safe by default in the way a locked-down SaaS app is. An agent that can run commands and read files is closer to giving a contractor a laptop. News outlets have reported that this class of open-source agent software, including Hermes, has shown up in cyberattacks. For a business, the response is boring and correct: isolate it, require approval for sensitive actions, do not point it at production credentials, and assume anything in its memory could leak if the box is compromised.

It also burns money if you point a frontier model at a chatty loop. Community advice is to use a cheaper model for routine cron jobs and a stronger one for hard reasoning. Tina Huang’s point about setup is the same point in different clothes: a sloppy install produces a toy that disappoints you. A careful install produces something you keep.

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If you are a business user, how to think about a trial

Pick one recurring job you already pay a person (or yourself) to do every week: a competitor recap, an inbox triage, a pipeline snapshot, a “what changed in these five folders” note. Put Hermes on a separate machine or a small cloud instance. Connect one chat channel, not five. Turn on command approval. Run it for two weeks. Then ask only two questions: did the memory help, and did the scheduled job actually fire without you babysitting it?

If both answers are yes, you have a category of software most companies still have not named. If either answer is no, you learned that cheaper than a platform RFP.

Official starting points: hermes-agent.nousresearch.com, docs at hermes-agent.nousresearch.com/docs, code at github.com/NousResearch/hermes-agent, and the community at r/hermesagent and discord.gg/NousResearch.

The people already living with it are not waiting for an enterprise brochure. They are sending themselves an 8am briefing and arguing about which model should drive the next one.