What the heck is OpenClaw/Clawbot/MoltBot?
Source: Dev.to
Why Are AI Agents Suddenly a Big Deal?
Something happened recently in the world of AI agents. All of a sudden, people around me started going crazy about this new AI agent whose name has already changed three times.
But AI agents are not new. They’ve been around for almost three years. So what changed? Why does it suddenly feel like a big deal or even a breakthrough in the era of AI agents?
Let’s break it down.
What Is an AI Agent?
At its core, an AI agent is an LLM that is given a concrete instruction to perform a particular task.
- It can reason to make better decisions.
- It has access to a set of tools to perform actions in the real world.
- It can operate beyond simple text generation.
Enter OpenClaw
OpenClaw (yes, the one that changed its name three times) does something similar — but also a lot more.
- First of all, it’s open source, which means anyone can run it locally or on the cloud.
- More importantly, OpenClaw is not just an agent — it’s an agentic system.
When LLMs entered the real world, they only had a brain. They could think and respond, but only through text. It always felt like something was missing. AI agents were supposed to bridge that gap. OpenClaw is one of the first serious attempts at doing exactly that.
An AI That Has Its Own World
OpenClaw can literally control a computer.
- It understands its environment.
- It can take actions.
- It can spawn multiple sub‑agents to handle complex tasks.
- It can effectively manage and coordinate those agents.
Because of this power, it’s recommended to give OpenClaw an isolated and dedicated environment to do its work. You can run it on your own machine, but unless you really know what you’re doing, it’s risky.
Communication: How Do You Talk to It?
Any AI agent needs a way to communicate with humans. Usually this is done via a web‑based UI, but OpenClaw is designed to run independently and potentially forever.
Instead of a UI, it uses existing messaging platforms like:
- Telegram
- Slack
These channels let you access the agent from any device. They establish a secure connection so whenever you send a message, the agent acknowledges it, responds, or takes action.
Dashboard
OpenClaw is model‑agnostic. You can configure it to use:
- Anthropic models
- Google Gemini
- Open‑source models
Choose whatever works best for your use case.
Agents
When you set up OpenClaw, you start with a single agent that is managed via a gateway. You can then create multiple specialized agents for specific tasks.
The real beauty of OpenClaw is that these agents can:
- Communicate with each other
- Assign tasks
- Share context
Memory System
OpenClaw has a structured memory system:
AGENTS.md– operating instructions and additional memorymemory/YYYY‑MM‑DD.md– daily append‑only logs that capture day‑to‑day context (today’s and yesterday’s files are loaded at session start)MEMORY.md– curated long‑term memory for decisions, preferences, and durable factsSOUL.md– defines the agent’s persona, tone, boundaries, and communication styleIDENTITY.md– specifies the agent’s name, vibe, emoji, and avatarUSER.md– stores facts about you, including your preferred name and profile details
Skills
Skills are special “doors” that let the agent interact with the outside world — similar to tools in LLMs.
Examples:
- Playing your favorite song on Spotify
- Calling APIs
- Interacting with services
Heartbeat (Cron Jobs)
OpenClaw also supports scheduled tasks using cron‑like heartbeats.
Running an agent 24/7 is a bad idea unless you’re doing very intensive work. Instead:
- The agent wakes up at a specific time.
- Does its job.
- Goes back to sleep.
This approach minimizes compute costs. If multiple agents are involved, they can coordinate by updating MEMORY.md to assign tasks or share context.
So What’s the Real Breakthrough?
What’s surprising is that OpenClaw isn’t built on some brand‑new LLM breakthrough. It still uses the same class of models that appeared around 2022 — just smarter versions.
The real innovation is not the model, but the system. OpenClaw is an agentic system that defines a sophisticated way for AI to:
- Control its environment
- Work autonomously
- Coordinate multiple agents
- Persist memory and context
Final Thoughts
There’s a lot more that I didn’t cover in this post. The goal here was to get you familiar with this new agentic system and explain why it’s different from traditional AI agents.
If you have questions or doubts, feel free to leave a comment.
Hope you enjoyed reading this!
