01 —The original idea: “WhatsApp Relay”
Peter Steinberger sat at his computer one evening at the end of November 2025 and a simple question arose: “Can I give my computer a task via WhatsApp - and he does it while I'm somewhere else?"
The answer was: Technically yes, but no ready-made tool existed for it. So he built it himself. He called it internal “WhatsApp Relay”. The mechanics were radically simple: a message goes to a WhatsApp number. The WhatsApp API forwards them. Anthropic's Claude API receives them, thinks about it, returns an instruction. The instruction will executed on the local computer.
First working version: one hour.
“He had a deceptively simple question: Can an AI assistant make progress check his work via a chat app? One evening he bandaged one Messaging API using Claude's API, gave the system local system access - and had a prototype in an hour."— emergent.sh, Complete Guide OpenClaw 2026
Steinberger thought it was so obvious that OpenAI or Anthropic would soon build exactly that. So he put the code on GitHub – not as a product, but as an experiment. The project was called Clawdbot, a pun on "Claude" with a lobster claw as a mascot. The internet responded with an enthusiasm he didn't expect.
02 —What OpenClaw really is - and what it isn't
Above all else, one thing must be clear: OpenClaw is not a chatbot. It is also not a model, not a SaaS solution and not a competing product to Claude or ChatGPT.
OpenClaw is one Orchestration layer – a framework, that runs on your own computer and from any AI model (Claude, GPT-5, Gemini, DeepSeek, Llama via Ollama) one capable of action agents makes.
ChatGPT answers questions. OpenClaw gets things done. It reads emails, books appointments, executes terminal commands, scrapes websites, fills out forms, manages files – and does this autonomously, on your own Hardware, 24/7. It is aptly called: "Claude with hands."
The crucial difference lies in the ratio of input to output. With a chatbot, you enter a prompt and receive text back. With OpenClaw you specify a goal - and the agent decides independently She carries out which steps are necessary and observes the result and iterates until the task is completed.
The project is MIT licensed, free and open source. Written in TypeScript and Swift. Runs locally on your own hardware – Data only leaves your own computer if you use an external one AI model (Claude API, GPT API) is used.
03 —Architecture: The Four Layers of the Agent
OpenClaw does not work like a conventional software system solid logic. It is a Composition system, that the agent made up of individual building blocks every time you start – from the file system, in real time.
The architecture consists of four central layers:
The crucial difference to other agent frameworks: Standard agents are amnesiacs. Start on every reboot them at zero. OpenClaw solves this by consistently reading configuration files at startup - the agent "wakes up" and literally reads itself into its existence into it.
A deep understanding of your own system is also built in: The agent knows its own source code, its configuration, which models he uses and which options are available. This creates what Steinberger “System Awareness” called – not in a philosophical sense, but in a highly practical one: An agent that knows its own architecture can know itself develop and create new skills on demand.
04 —SOUL.md – The “character” of the agent
One of OpenClaw's most innovative concepts is the SOUL.md file. It is the foundation of every OpenClaw agent - a simple Markdown file, which describes in natural language who the agent is, how he communicates, what his values are and what boundaries he has to adhere to.
Typical SOUL.md sections: Identity (Who are you?), Communication style (How do you communicate?), Core Values (What do you stand for?), Non-negotiables (What do you never do?). The file is injected into the system prompt every time the agent is started. No database access, no API – just Markdown.
The philosophical difference to an ordinary system prompt lies in the intention: "You're not a chatbot. You're becoming someone." This is how a much-quoted SOUL.md example from the community begins. The first line of a standard prompt would be: "You are a helpful assistant." This is a behavior instruction. SOUL.md is an identity definition.
Along with IDENTITY.md (specific role), MEMORY.md (knowledge) and HEARTBEAT.md (planned autonomous actions) forms SOUL.md that, what Steinberger did? "Harness" called – the framework that ensures the agent is always running, is always available and always across all channels carries the same context.
05 —The memory system: Persistence without a database
The most common criticism of AI chatbots is: "Goldfish Brain." As soon as the browser window is closed, everything is forgotten. OpenClaw solves the problem in a radically simple way - and that's exactly where the elegance lies.
Memory in OpenClaw are Markdown files on the local hard drive. The agent is instructed to provide relevant facts after each meaningful interaction to write into his memory files. The next time it starts, it reads it. “Mental notes” disappear when restarting – files do not disappear.
OpenClaw is building one Vector index about the memory files:
Chunking (approx. 400 tokens, 80 token overlap) →
Embedding via OpenAI, Gemini or local GGUF model →
SQLite with optional sqlite-vec acceleration.
When retrieved, it combines Vector similarity (semantic match)
with BM25 keyword relevance (exact token match).
Score: vectorWeight × vectorScore + textWeight × textScore.
The result: An agent that understands "Mac Studio gateway host"
even if the note only says “the machine on which the gateway is running”.
06 —Skills: How OpenClaw expands its capabilities
In most agent frameworks, a "tool" is a JSON function signature. A rigid interface. OpenClaw thinks radically differently: Skills are Markdown files with embedded scripts.
To teach OpenClaw a new skill, you create a directory writes a Markdown file that describes what the skill does, adds the script – and the agent can use it immediately. No reboot, no code deployment, no API registration.
The ClawHub Marketplace is the app store for OpenClaw skills. Thousands of community-developed skills cover everything: from Notion integration to bright data scraping to Spotify control. The catch: Quality varies greatly, and before security hardening In 2026, there were 341 malicious skills on ClawHub with a contamination rate found by 12% - a direct indication of why enterprise deployments curated, verified skill sources.
The supported messaging platforms (as of April 2026):
All channels share a single, shared memory. The agent is aware of a command via WhatsApp in the morning, when asked via Slack in the evening.
07 —Product evolution: From v0.1 to NemoClaw
08 —OpenClaw vs. ChatGPT Enterprise vs. n8n – the honest comparison
| criterion | OpenClaw | ChatGPT Enterprise | n8n/Zapier |
|---|---|---|---|
| type | Autonomous agent + framework | Chatbot with restricted Actions | Workflow automation |
| Acts autonomously | ✓ Yes – multi-stage, without confirmation | ⚠ Restricted – Tools via API | ✗ No – rule-based, no AI thinking |
| Data sovereignty | ✓ Local, on-premise possible | ✗ OpenAI US Cloud | ⚠ Depends on hosting |
| memory | ✓ Persistent, across sessions | ⚠ Memory feature, limited | ✗ No AI memory |
| Skill expansion | ✓ Markdown files, self-writing | ⚠ GPT plugins (limited) | ✓ Lots of connectors |
| Multi-model | ✓ Claude, GPT, Gemini, DeepSeek, Ollama | ✗ OpenAI only | ⚠ About AI nodes |
| Messaging native | ✓ WhatsApp, Telegram, Slack and much more. | ✗ Browser/API only | ⚠ About webhook connectors |
| Open source | ✓ MIT license | ✗ Closed Source | ⚠ n8n: partially, Zapier: no |
| Enterprise ready (out of box) | ⚠ Needs professional setup | ✓ Can be used immediately | ✓ For simple flows |
| Cost | € – LLM API costs only | €€€ – Subscription + API | € to €€ – subscription model |
The short version for decision-makers: n8n and Zapier are the right choice for rule-based, predictable processes without AI thinking. ChatGPT Enterprise is the easiest way to use AI, with the disadvantage of US cloud dependency and no real agent logic. OpenClaw is the most powerful tool for complex, Autonomous workflows – but professional deployment is needed in order to Meet enterprise requirements.
09 —What companies in the DACH region need to know
OpenClaw is not a plug-and-play enterprise product. The security researchers at SOCprime found shortly after the launch over 1,000 unsecured instances on the public internet – with exposed API keys, chat histories and system credentials. The reason: The agent needs root-level access to the system, to fulfill his tasks. Without a professional security concept This is a massive attack surface.
What every business installation needs: Sandboxed Execution Environment Role-Based Access Control (RBAC) · Audit logging of all agent actions · Encryption of all communication channels · Curated, verified skill sources instead of ClawHub community · AVV contract for all API calls to external models · On-premise deployment for GDPR-critical data
The good news: Enterprise maturity is growing rapidly. NVIDIA NemoClaw addresses GPU acceleration and enterprise governance. The OpenClaw Foundation works on team management, compliance tools and auditable logging. And focus on projects like IronClaw (NEAR AI). explicitly focuses on safer sandboxing.
For companies in the DACH region that want to start using OpenClaw today, There is no way around an experienced implementation partner – someone who knows enterprise architecture, GDPR-compliant deployments has carried out and understands where the limitations of the current framework lie.
FAQ: Frequently asked questions about OpenClaw
Peter Steinberger built the first version in an hour: He connected the WhatsApp API with Anthropic's Claude API and made it possible to delegate tasks to the AI model on the local computer. The project was published on GitHub in November 2025 and has since grown by the community to 300,000+ lines of code.
ChatGPT is a chatbot that generates text. OpenClaw is an execution framework that performs autonomous actions in the real world: reading emails, executing terminal commands, managing calendars, controlling browsers, moving files - without confirmation at each step. It runs locally, is model-agnostic and open source.
SOUL.md is a Markdown file that defines the personality, values, and behavior rules of an OpenClaw agent in natural language. It is injected into the system prompt every time the agent is started and ensures a persistent, consistent identity across all sessions and messaging channels.
OpenClaw is model-agnostic: It supports Claude (Anthropic), GPT-5 (OpenAI), Gemini (Google), DeepSeek, KIMI K2.5, Xiaomi MiMo as well as locally operated models via Ollama. Companies can choose any model – or combine different models for different tasks.
OpenClaw has enormous potential for companies, but requires a professional enterprise architecture: sandbox environment, role-based access control, audit logging and GDPR-compliant deployment. A standard community setup is not enterprise-ready. Clawgency implements OpenClaw with this architecture for companies in the DACH region.
ClawHub is the official skill marketplace for OpenClaw - comparable to an app store for agent skills. Thousands of community-developed skills expand the agent. For enterprise use, only verified, curated skills should be used; Malware-infected skills were found in the community pool.
Make OpenClaw enterprise-ready – for your company
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