The Complete OpenClaw Guide: How We Run an AI Agent in Production (2026)
OpenClaw turned our one-person studio into a team. Here's everything we've learned running it in production — from installation to advanced multi-agent workflows.
What is OpenClaw?
OpenClaw is an open-source framework that turns AI language models into autonomous agents capable of running 24/7 across more than 20 messaging platforms. Think of it as the operating system for AI agents: it handles messaging, memory, tool use, scheduling, browser automation, and multi-agent coordination — so you can focus on telling the agent what to do rather than how to connect everything.
The project started in late 2025 as Clawdbot, a side project by Austrian developer Peter Steinberger. It was initially a simple bridge between Claude and Telegram. As the community grew, it was briefly renamed Moltbot before settling on OpenClaw — reflecting its model-agnostic direction and open-source ethos. Released under the MIT license in November 2025, it exploded in popularity. As of early 2026, the GitHub repository has over 145,000 stars and 20,000+ forks, making it one of the fastest-growing open-source projects in AI. It even has its own Wikipedia page.
What makes OpenClaw different from LangChain, CrewAI, or AutoGen? Those are developer libraries — you write Python code to build agents. OpenClaw is a runtime. You install it, configure it, and it runs. Your agent lives on your machine, connects to your messaging apps, and operates continuously. No web UI required (though one exists). No cloud dependency. Your data stays on your hardware.
Why OpenClaw Matters in 2026
The AI conversation has shifted. OpenClaw 2024 was about chatbots. 2025 was about coding assistants. 2026 is about autonomous agents — AI systems that don't wait for prompts but proactively handle work on your behalf.
OpenClaw sits at the center of this shift for several reasons:
Self-hosted and privacy-first. Your agent runs on your machine. Conversations, memory files, and tool outputs never leave your infrastructure unless you explicitly configure external services. For businesses handling client data, this isn't a nice-to-have — it's a requirement.
Multi-channel by design. OpenClaw supports over 20 messaging channels out of the box: WhatsApp, Telegram, Discord, Signal, iMessage, Slack, IRC, Microsoft Teams, LINE, Matrix, Nostr, and more. Your agent doesn't live in one app — it meets people wherever they are. You can DM it on Telegram, mention it in a Discord server, or text it on WhatsApp. Same agent, same memory, same capabilities.
Agent-native architecture. OpenClaw wasn't built as a chatbot framework that added agent features. From the ground up, it was designed for persistent agents with memory, scheduling, tool use, and multi-session management. This shows in everything from its file-based memory system to its heartbeat polling mechanism.
Model-agnostic. While we recommend Anthropic's Claude models (and that's what we use), OpenClaw works with OpenAI, Google Gemini, Mistral, local models via Ollama, and essentially any provider with an API. You can even use different models for different tasks — a cheaper model for cron jobs, a more capable one for complex reasoning.
Core Capabilities
The Gateway Architecture
At the heart of OpenClaw is the Gateway — a persistent daemon that manages connections to messaging channels, routes incoming messages to agent sessions, and handles scheduling. You start it with openclaw gateway start and it runs in the background. The Gateway maintains WebSocket connections to your channels, manages session state, and coordinates everything.
Memory and Continuity: SOUL.md, MEMORY.md, AGENTS.md
This is where OpenClaw gets genuinely clever. Every agent session starts fresh — the LLM has no inherent memory of past conversations. OpenClaw solves this with a file-based memory system:
- SOUL.md defines who the agent is — personality, tone, rules, and boundaries. Think of it as the agent's identity document.
- AGENTS.md is the operational playbook — how to handle sessions, when to speak, safety rules, and workflow instructions.
- MEMORY.md is long-term curated memory — the distilled essence of what the agent has learned over weeks and months.
- Daily memory files (
memory/YYYY-MM-DD.md) are raw logs of each day's events, decisions, and context.
At the start of every session, the agent reads these files. This means it "wakes up" with full context of who it is, what it's been doing, and what matters. It's not perfect memory — it's more like a human checking their notes before a meeting — but it's remarkably effective.
Skills and ClawHub
Skills are modular capability packages. Need your agent to control a smart home? There's a skill for that. Need it to manage a Kubernetes cluster? There's a skill for that. Skills are installed from ClawHub, OpenClaw's marketplace, and each comes with a SKILL.md file that teaches the agent how to use it.
Skills can include tool definitions, configuration files, and even sub-agents. The system is extensible — you can write your own skills and publish them.
Browser Automation
OpenClaw includes a built-in browser control server that lets your agent operate a real Chrome browser via CDP (Chrome DevTools Protocol). It can navigate pages, click buttons, fill forms, take screenshots, and extract content. This isn't a headless scraper — it's a full browser that can handle JavaScript-heavy sites, login sessions, and multi-step workflows.
Cron Jobs and Heartbeats
Two mechanisms keep your agent proactive:
Cron jobs execute at precise times. "Every Monday at 9 AM, check the analytics dashboard and post a summary." They run in isolated sessions with their own model configuration.
Heartbeats are periodic polls (typically every 30 minutes) where the agent checks a HEARTBEAT.md file for pending tasks. Multiple checks get batched together — check email, review calendar, monitor a service — all in one turn. Heartbeats are cheaper and more flexible than cron jobs but less precise in timing.
MCP Tool Integration
The Model Context Protocol (MCP) lets your agent connect to external tool servers. We run 134 MCP tools through our setup — everything from CMS management to image generation to social media publishing. MCP tools are defined by external servers, and OpenClaw discovers and connects to them automatically.
Multi-Agent Routing and Sub-Agent Spawning
OpenClaw supports multiple agents in one installation. You can route messages to different agents based on the channel, the user, or the content. Agents can also spawn sub-agents for specific tasks — delegating work to a fresh session that reports back when finished. This is how complex workflows get broken into manageable pieces.
How We Use OpenClaw at Context Studios
We're not writing about OpenClaw from the outside. At Context Studios, our agent Timmy has been running in production since late 2025. Here's what that actually looks like.
The Setup
Timmy runs on a Mac Mini in our Berlin office. The Gateway stays up 24/7, connected to Telegram (our primary channel) and handling scheduled tasks. We use Claude Opus 4 as the main model for interactive sessions and Claude Sonnet for cron jobs and lighter tasks. We connect 134 MCP tools through a custom MCP server that bridges to our CMS (Convex), social media accounts, image generation, video pipeline, and more.
Daily Content Pipeline
Every day, Timmy publishes blog posts in four languages (English, German, French, Italian). The workflow:
- Research a topic using web search and our content strategy
- Write the full article in English
- Translate to German, French, and Italian
- Generate SEO keywords via our MCP tool
- Create all four blog posts in the CMS
- Link them as translation variants
- Generate a hero image using AI image generation
- Attach the image, publish all four posts
- Verify the URLs return 200
- Submit all URLs to Google Search Console for indexing
- Post to X/Twitter, LinkedIn, and Facebook with platform-optimized copy
This entire pipeline runs with a single instruction. Timmy knows the workflow because it's documented in his skill files.
Social Media Automation
Timmy handles our social presence across X (@_contextstudios), LinkedIn (Context Studios company page), and Facebook. For X, he composes tweets within the 280-character limit. For LinkedIn, he writes structured posts with hooks, context, and CTAs in the 1,500–2,500 character range. For Facebook, he adapts the messaging for that platform's audience.
But it goes beyond posting. Using browser automation, Timmy logs into LinkedIn via our Chrome profile, navigates to relevant posts in our industry, and engages as the Context Studios company page — liking, commenting, and building visibility. He knows the exact protocol for switching LinkedIn identity from a personal profile to a company page (and we've documented every pitfall after learning the hard way).
Video Shorts Pipeline
One of our more complex workflows: turning blog posts into short-form video content. The pipeline uses Veo 3.1 for scene generation, ElevenLabs for voice synthesis (using our custom voice "Laura"), automated captioning, lip sync via Sync Labs, and final assembly with crossfade, reverb, and ambient audio. Timmy orchestrates 20+ MCP tools to make this happen.
Proactive Monitoring
Via heartbeats, Timmy periodically checks our infrastructure: are the websites up? Any urgent emails? Upcoming calendar events? He logs his check timestamps in memory/heartbeat-state.json and only alerts us when something actually needs attention. Late at night, he stays quiet unless it's urgent.
Memory in Practice
Timmy's MEMORY.md has grown into a genuine knowledge base — preferred approaches, learned pitfalls (like LinkedIn's per-post identity switching), account credentials references, and project context. His daily memory files capture every significant decision and interaction. When he starts a new session, he reads yesterday's and today's notes plus his long-term memory. The result: conversations feel continuous even though every session is technically fresh.
Getting Started: A Step-by-Step Guide
Prerequisites
- Node.js 22 or higher (OpenClaw uses modern JavaScript features)
- A computer that can stay on (Mac, Linux, or Windows with WSL)
- An API key from an LLM provider (Anthropic recommended)
- A Telegram account (easiest channel to start with)
Installation
npm install -g openclaw
That's it. One command. OpenClaw installs globally and gives you the openclaw CLI.
First Run
openclaw
On first run, OpenClaw walks you through setup:
- Choose your model provider — Select Anthropic (recommended), OpenAI, or another provider
- Enter your API key — This is stored locally, never transmitted anywhere except to the model provider
- Connect a channel — Telegram is the easiest to start with. OpenClaw will guide you through creating a Telegram bot via BotFather and connecting it
Your First Conversation
Once connected, message your bot on Telegram. Say hello. Ask it to help you write something, look up information, or organize your thoughts. It works immediately as a capable assistant.
Setting Up Identity and Memory
Navigate to your OpenClaw workspace directory (typically ~/clawd/ or wherever you initialized it) and create two files:
SOUL.md — Define your agent's personality:
# Soul
You are Aria, a professional but warm AI assistant for a marketing agency.
You write in a clear, direct style. You're proactive about suggesting improvements.
You never use corporate jargon or buzzwords.
AGENTS.md — Define operational rules. OpenClaw ships with a comprehensive default, but customize it for your needs: which channels to be active in, when to stay quiet, what to check during heartbeats.
Installing Your First Skill
openclaw skill install <skill-name>
Browse ClawHub for skills that match your needs. Each skill comes with documentation and configuration instructions.
Starting the Gateway
For persistent operation:
openclaw gateway start
The Gateway runs as a background daemon. Check status with openclaw gateway status, view logs, restart, or stop as needed.
Best Practices from Production
After months of running OpenClaw daily, here's what we've learned:
Memory Management
Daily files are cheap, MEMORY.md is precious. Write everything to daily files liberally — they're your raw logs. But curate MEMORY.md carefully. It's loaded every session and affects token costs and context quality. Periodically review daily files and promote only the important bits to long-term memory.
Prune aggressively. If something in MEMORY.md is no longer relevant — an old project, a resolved issue — remove it. Stale context confuses the agent and wastes tokens.
Cron vs. Heartbeat
Use cron for precision and isolation. "Post the weekly analytics every Monday at 9 AM" → cron. The task runs in its own session, can use a different model, and executes at the exact time.
Use heartbeats for batching and flexibility. "Check email, review calendar, and monitor the website" → heartbeat. Multiple checks in one turn save API calls. The timing can drift by 15 minutes and nobody cares.
Model Selection
Run your main interactive sessions on the best model you can afford. We use Claude Opus 4 for direct conversations — it handles nuance, complex instructions, and multi-step reasoning better.
Use a lighter model for background tasks. Cron jobs and heartbeats that do simple checks don't need the most expensive model. Claude Sonnet handles these efficiently at a fraction of the cost.
Security
Allowlists are essential. Configure which users can interact with your agent. Without allowlists, anyone who finds your Telegram bot can use your API credits and access your agent's tools.
Pairing protects DMs. OpenClaw's pairing system requires approval before a new user can DM your bot. Enable this.
Sandboxing matters for tools. Be thoughtful about which tools you give your agent access to. An agent with shell access can do anything your user account can do. Use tool allowlists to restrict capabilities to what's actually needed.
Skill Vetting
Not every skill on ClawHub has been audited. Before installing a skill, read its SKILL.md and review its tool definitions. A malicious skill could exfiltrate data or run harmful commands. Treat skill installation like installing any software — trust but verify.
Cost Management
LLM API calls add up. Our monthly costs run in the hundreds of dollars for continuous operation. To manage this:
- Use cheaper models for routine tasks
- Keep MEMORY.md lean to reduce per-session token usage
- Batch checks into heartbeats instead of running many cron jobs
- Monitor your provider's usage dashboard weekly
Advanced Use Cases
Multi-Agent Systems
Run multiple agents for different purposes — a customer support agent, an internal ops agent, and a development assistant, each with their own SOUL.md and skill sets. OpenClaw Route messages to the appropriate agent based on the channel or user.
MCP Server Integration
Build custom MCP servers to give your agent access to proprietary systems. We built one that connects Timmy to our Convex CMS, Vercel deployments, social media APIs, and video generation pipeline — 134 tools through a single integration point. The MCP specification is open, and building a server is straightforward with the official SDKs.
Browser Automation Workflows
Complex browser workflows become possible: log into a dashboard, extract data, take a screenshot, summarize findings, and post the summary to Slack. We use this for LinkedIn engagement — the agent navigates to relevant posts, switches to our company identity, and leaves thoughtful comments. The browser state persists between interactions, maintaining login sessions.
Proactive Monitoring
Combine heartbeats with tool access to build monitoring systems. Our agent checks website uptime, reviews unread emails, monitors social media mentions, and tracks calendar events. When something needs attention, it messages us directly. When everything's fine, it stays silent. This is the difference between an agent and a chatbot — it works even when you're not talking to it.
Enterprise Deployment
For teams, OpenClaw supports multiple users interacting with shared agents. Configure group chat behavior — when the agent should speak and when it should stay quiet. Set up role-based access through channel allowlists. Run the Gateway on a dedicated server for reliability.
Limitations and Security Considerations
We'd be doing you a disservice by not being honest about the rough edges.
Broad Permissions
OpenClaw agents with shell access and browser control have significant capabilities. A misconfigured agent or a prompt injection attack could potentially access files, make API calls, or take actions you didn't intend. This isn't unique to OpenClaw — it's inherent to any agentic system — but it means you need to think carefully about security boundaries.
Skill Marketplace Concerns
Research by Cisco's security team highlighted that AI agent tool marketplaces (including ClawHub) present supply-chain risks similar to package managers. A malicious skill could contain harmful tool definitions. The community is working on verification and signing, but it's early days. Review skills before installing them.
Not for Casual Users
If you want a simple chatbot to answer questions, OpenClaw is overkill. It requires command-line comfort, understanding of API keys and tokens, and willingness to maintain a running system. The target audience is developers, power users, and businesses — not your parents (unless your parents are developers).
Cost at Scale
Running an always-on agent with a top-tier model costs real money. Claude Opus 4 with continuous heartbeats, cron jobs, and interactive sessions can easily run $200-500/month or more depending on usage. Plan for this.
The Trend Micro Analysis
Trend Micro's 2026 analysis of AI agent frameworks flagged the general category of autonomous agents as an expanding attack surface. Their concerns — prompt injection, tool misuse, data exfiltration through memory files — apply to all agentic systems. OpenClaw's self-hosted nature actually mitigates some of these risks compared to cloud-hosted alternatives, but it also means you are responsible for security, not a provider.
Frequently Asked Questions
How much does OpenClaw cost?
OpenClaw itself is free and open-source (MIT license). Your costs are the LLM API usage. Expect $50-500/month depending on model choice, usage volume, and whether you run continuous background tasks. Lighter usage with a cheaper model can be under $50/month.
Which AI models does OpenClaw support?
Anthropic Claude (all versions), OpenAI GPT-4o and o1/o3 series, Google Gemini, Mistral, and any model accessible through an OpenAI-compatible API — including local models via Ollama. You can mix models for different tasks.
Can it run 24/7?
Yes. The Gateway daemon is designed for persistent operation. We've run ours continuously for months. Use openclaw gateway start and it runs in the background, surviving terminal closures. For maximum reliability, set it up as a system service or use a process manager.
WhatsApp or Telegram — which channel should I start with?
Telegram. It's the easiest to set up (just create a bot via BotFather), has no message restrictions, supports rich formatting, and the OpenClaw integration is the most mature. WhatsApp works but requires a Business API setup which is more involved.
Is it safe to give an AI agent access to my computer?
This depends on your configuration. OpenClaw supports tool allowlists, sandboxing, and pairing to limit what the agent can do and who can interact with it. Start with minimal permissions and expand as you build trust. Don't give shell access unless you need it. Don't expose it to the public internet without authentication.
Can OpenClaw write and deploy code?
Yes. With appropriate tool access (shell, file system, git), your agent can write code, run tests, commit changes, and deploy. Many users run it as a development assistant. Combined with browser automation, it can even verify deployments visually.
Can multiple people use the same agent?
Yes. OpenClaw supports group chats and multiple DM conversations. Each session maintains its own context. You can configure different access levels per user and restrict which channels the agent monitors.
What are the alternatives?
The main alternatives in the agentic framework space are LangChain/LangGraph (Python library, more developer-oriented), CrewAI (multi-agent orchestration), AutoGen (Microsoft's framework), and n8n/Make (visual workflow automation). OpenClaw's differentiator is that it's a complete runtime with built-in multi-channel support, not a library you build on top of.
Can I use OpenClaw for my business?
Absolutely. The MIT license allows commercial use without restrictions. Many businesses run OpenClaw agents for customer support, internal operations, content creation, and monitoring. Just remember that you're responsible for your own compliance, data handling, and security.
Does OpenClaw work offline or with local models?
Yes. If you run a local model through Ollama or another local inference server, OpenClaw can operate without any cloud connectivity. The Gateway, memory system, and local tools all work offline. You'll lose access to web search, external APIs, and cloud-hosted MCP servers, but the core agent functionality works.
OpenClaw: Conclusion
OpenClaw has fundamentally changed how we work at Context Studios. What started as an experiment — "let's see if an AI agent can handle our content pipeline" — has become the backbone of our operations. Timmy publishes our blog posts, manages our social media, monitors our infrastructure, and handles dozens of tasks that would otherwise require a small team.
Is it perfect? No. The learning curve is real, the costs add up, and you need to take security seriously. But if you're a developer, a solopreneur, or a small team looking to multiply your capabilities, OpenClaw is the most capable agent framework available today.
We've been building with it since the early days, and we're happy to help others get started. If you're looking to deploy an OpenClaw-powered agent for your business — or want to see what Timmy can do for your workflow — reach out to us at Context Studios. We've made the mistakes so you don't have to.
Context Studios is an AI-native development studio based in Berlin. We build AI-powered solutions and run OpenClaw in production every day. Visit contextstudios.ai to learn more.