Introduction

If you’ve been following AI agents recently, you might have heard two names: OpenClaw and Hermes Agent. In the Chinese community, OpenClaw is referred to as “Lobster,” while Hermes is translated as “Hermes.”

You may have seen many comparisons between them, but honestly, most articles are too technical, discussing architectural differences, memory layers, and model fine-tuning—leaving the average person still unsure about their differences. Today, I will clarify this with a metaphor.

What is OpenClaw?

In simple terms:

OpenClaw is a central scheduling hub.

You can send messages to it from WeChat, Telegram, Feishu, Discord, or any other platform. It receives your message and executes it step by step based on the “Skill” files you provide. Its operation is similar to a compliant employee. The more detailed your instructions are, the better it performs. If you don’t provide instructions, it remains idle.

This is the fundamental logic of Lobster: You drive it.

What is Hermes?

The logic of Hermes Agent is entirely different.

The core of Hermes is not scheduling but learning.

After completing a task, it automatically performs three actions:

1. It distills the process of solving the problem into a Skill file, including steps and precautions.
2. It saves this Skill in memory for future similar tasks.
3. It continuously optimizes this Skill during use, automatically updating it when better methods are discovered.

Do you understand? It evolves itself.

The state of Hermes after one hour of use is different from that after ten hours. After a week, it will adapt to your habits without needing you to explain everything repeatedly.

A Metaphor is Enough

OpenClaw is like a pet dog.

You need to feed it, walk it, and train it. If you don’t feed it, it gets hungry; if you don’t train it, it won’t learn new skills. The effort you invest determines its performance. If you get busy and neglect it, it just waits for you.

Hermes is like a horse that finds its own food.

You give it a direction, and it runs off, finding food and navigating on its own. The next time it takes the same route, it knows it better than you do. You don’t have to worry about whether it’s well-fed each time.

It’s not about which is better; it’s about what you need to invest in them.

Lobster requires your time and technical skills, while Hermes requires your trust and patience.

Memory System: The Real Difference

Some may ask: What is the core difference between these two tools?

The answer is: Memory.

Lobster has shallow memory. After each conversation, most context disappears. Although there is a manual memory function, you have to maintain it yourself—like taking notes for your dog.

Hermes has layered memory that is permanently saved.

It has four layers of memory:

1. Working Memory: Content of the current conversation, readily accessible.
2. Session Memory: Cross-conversation searches, allowing retrieval of things said a week ago.
3. User Modeling: Long-term accumulation of your preferences, work habits, and project backgrounds. The longer you use it, the better it understands you.
4. Skill Memory: Automatically generated Skill files that can be reused and shared.

The cumulative effect of these four memory layers is that after some time, it defaults to executing tasks according to your habits without needing repeated explanations. Many users describe the experience as becoming accustomed to it, feeling it’s more efficient without knowing why. The root cause lies here.

Who Should Use What?

This is not an either-or question; it depends on your needs.

Choose Lobster (OpenClaw) if:

• You are part of a team needing to interface with multiple channels like WeChat, Feishu, DingTalk, etc.
• You want every action to be precise and controllable, avoiding surprises.
• You have technical skills and are willing to spend time writing and maintaining Skills.
• In enterprise scenarios, auditability is more important than autonomy.

Choose Hermes if:

• You are an individual looking for a long-term intelligent assistant.
• You don’t want to repeatedly write Skills and maintain memory.
• Your tasks are repetitive—like daily information organization, report writing, or research—where Hermes’s learning cycle significantly boosts efficiency.
• You want the agent to become smarter over time rather than remain at the initial level.

Using Both Together: This is a common approach in the community: let Hermes handle high-level decisions and long-term task planning while Lobster’s tool ecosystem executes specific operations. One handles the brain, while the other manages the limbs.

Migration Cost

If you are already using Lobster and want to try Hermes, migration is straightforward. Hermes includes a built-in migration command that automatically imports your memories, skills, personality settings, and API keys. You can also preview what will be migrated before confirming.

Summary

Lobster is Agent 1.0: Human-driven Agent.

Hermes is Agent 2.0: Agent drives itself.

Both paradigms will coexist long-term, suitable for different scenarios. However, the direction is clear.