How to Build a Silicon-Based Intelligent Life Form? Hermes Agent: Smart Architecture in Practice

Hermes is a program, an Agent OS in the AI era, an intelligent entity running on a terminal system, which can also be viewed as a prototype of a silicon-based intelligent life form.

Looking at its architecture from the perspective of a life-form may make it easier to understand.

1. Hardware Carrier (Body)

• Whether it's a local PC or a remote server, either can serve as its carrier—this is its physical body.

2. Software Program (Coordination System)

• Its coordination and command system.
• Includes "Channels" configuration, allowing it to communicate with people via CLI, WeChat, QQ, and more.

3. Large Language Model (Soul)

• Hermes without a "large language model" injected is like a "person in a vegetative state." So we either add memory and graphics cards to a local computer to locally deploy an open-source large model, or call cloud-based large models by connecting to various model APIs.
• Wittgenstein once said: "The limits of my language mean the limits of my world." What you can use and understand language to describe is the extent of the world you can perceive; once something exceeds the expressive power of language, it cannot enter your cognition. Anything that cannot be described in language or formulated as a proposition falls outside the "thinkable, speakable world." And the power of today's large language models lies precisely in their having learned all human languages.

4. Skill Environment (Limbs)

• What do you want it to do? You need to equip it with the corresponding tools. For example, if you want it to write Word documents, you need to install Word document software; if you want it to generate videos, besides installing Skills, you also need the corresponding players.
• Its skills are gradually adapted or learned and grown based on the owner's needs.

5. Operation & Maintenance (Immune System)

• This is the most easily overlooked part, yet it's also the part that subsequently requires continuous human effort (or money to solve). Try to keep it from "getting sick," and ensure it receives timely treatment when it does.

Overall, we can understand Hermes as a prototype of an open-source silicon-based intelligent life form powered by large models as its energy source and Python as its skeleton.

What steps does our actual "building" process involve?

I. Prepare a Computer or Server

• At least 4GB of memory and 50GB of storage.

II. Deploy the Hermes Program

• Install the Hermes program.
• Log in to q.qq.com to register a QQ bot, and record the AppID and AppSecret—used to bind Channels after logging into the Hermes management page, which is one of the convenient ways to communicate with Hermes.
• You can also bind a WeChat claw to communicate with it via WeChat. However, currently each WeChat account can only bind one bot, meaning you can either bind OpenClaw or Hermes, not both. (QQ can bind multiple bots for interaction.)

III. Inject the "Soul"

This step essentially requires you to install a large model locally or use a cloud-based model's API.

• Since model runtime primarily depends on memory and VRAM, I suggest running a lightweight 4B-8B model locally as a fallback, and using a cloud API for the main model.
• For example, Doubao's published parameters are 200B+, meaning if you want to locally deploy Doubao to achieve its chat capabilities, you'd basically need a graphics card with 200GB of VRAM, which isn't cheap. DeepSeek R1 has 671B total parameters and requires 640GB+ of VRAM to run—and you might not even like it. So directly connecting to a cloud API is, for most people, both cheaper (nearly free) and more practical (plenty of choices).

Thus, this step's task becomes applying for APIs from various model providers:

1. Doubao - Volcengine https://www.volcengine.com/
2. SiliconFlow https://account.siliconflow.cn/ (DeepSeek, GLM-5.1, 5.2, Kimi, Qwen, and other models can all be configured here)
3. Moonshot https://www.moonshot.cn (direct link. I searched "Moonshot" on a certain search engine and the top results were all redirect links to sketchy websites—it's still like this, really can only sigh.)

IV. Skill Configuration

This is where things diverge significantly. It's similar to how everyone's computer has different software installed.

Developers / Technical personnel:

• github-pr-workflow GitHub PR full-process automation (branch creation, commits, adding reviewers)
• systematic-debugging Four-stage root cause debugging method, quickly locating problems
• writing-plans Technical proposal writing, breaking down implementation steps… these are almost must-haves.

Content creators / Operations personnel:

• markdown-writer Markdown document writing and formatting, essential for tech blogs
• content-ideas Content topic generation, combining trending topics with historical data
• daily-report Work daily/weekly report auto-generation, integrating task completion status

Initial configuration doesn't need to be "comprehensive"—start with 3-5 high-frequency skills covering your most frequent work scenarios, then gradually expand as you become familiar, letting the Agent grow and self-optimize through use.

V. Operation & Maintenance

• Regularly rotate API keys
• Avoid enabling public network access in the settings interface
• Back up regularly if possible

This requires continuous time and effort. Sometimes it's like raising a child—you can't just leave it completely unattended. Honestly, my approach is to let Claude Code monitor and maintain it in the background. This may not be scientific, but it's quite convenient.