OpenClaw FAQ

This is the most important question and deserves a direct answer: OpenClaw gives the AI broad access to your filesystem and can run shell commands. That's a lot of trust.

The agent can read files, write files, run code, and browse the web. By default, there's no sandbox preventing it from accessing sensitive parts of your computer. In practice, a properly configured agent with good identity files won't wander into areas you haven't told it about, but the technical capability is there.

For personal use with non-sensitive data: reasonable risk if you're comfortable with the tool. For business use with client data (financial, medical, legal): you need NemoClaw, which adds a real security sandbox enforced at the operating system level.

The short version: trust the tool proportional to the sensitivity of data on your machine. Use NemoClaw for any business-critical sensitive data.

The AI model itself (Claude, GPT-4, etc.) runs in the cloud, which means the text you send to the agent (and any text the agent sends to the model) passes through the AI provider's servers (Anthropic for Claude, OpenAI for GPT-4).

This includes anything in the agent's context window: your messages, any file contents the agent reads, web search results, etc. The AI provider receives this text to process your request.

OpenClaw itself is self-hosted. Your conversation history, memory files, and configuration stay on your machine. The cloud providers only see what's actively being processed.

If you need data to never leave your building (medical records, attorney-client privileged documents, financial records), you have two options: run a local model with NemoClaw's local inference, or use NemoClaw with NVIDIA's API (which has enterprise data handling agreements).

Several layers of control:

• SOUL.md: Define explicit limits on what the agent should and shouldn't do. "Never send emails without my explicit approval" or "Never modify files outside the workspace folder" written in SOUL.md are respected by the agent.
• AGENTS.md: The operating rules file. Add specific prohibitions and approval requirements here.
• Config restrictions: Limit which tools are available via tools config in openclaw.json.
• Channel allowlists: For WhatsApp, set channels.whatsapp.allowFrom to specific numbers so the agent won't respond to anyone else.
• Kill switch: openclaw gateway stop shuts down the entire gateway immediately.

For hard security boundaries (filesystem access restrictions, network call controls), those require NemoClaw. Config file instructions are honored by a well-behaved agent but aren't enforced at the OS level.

OpenClaw itself is free (MIT licensed). You pay only for the AI API tokens you use.

Rough monthly cost estimates:

• Light use (a few requests per day, simple tasks): $2–$8/month with Claude Sonnet
• Moderate use (daily briefings, some email triage, research): $10–$30/month
• Heavy use (constant automation, many tool calls, long sessions): $30–$100+/month

Claude Sonnet (the recommended default) costs around $3 per million input tokens and $15 per million output tokens as of early 2026. A typical morning briefing uses roughly 2,000–5,000 tokens. Check Anthropic's current pricing for latest rates.

Budget tip: Claude Haiku is ~10x cheaper than Sonnet. Use Haiku for simple tasks (weather, calendar reminders) and Sonnet for complex tasks (research, drafting).

For most people starting out: Claude Sonnet. It's the best balance of capability and cost from Anthropic. It's the default for good reason.

When to use other models:

• Claude Haiku: Cost-sensitive workflows, simple tasks, high-volume automations where quality matters less than price
• Claude Opus: Complex reasoning tasks, long-form writing where quality is paramount, worth the higher cost for specific high-stakes tasks
• GPT-4o (OpenAI): If you prefer OpenAI's ecosystem or need specific OpenAI features
• Local models (via Ollama): Privacy-sensitive use cases where data can't leave your machine; quality is lower, setup more complex

You can change the model in openclaw.json under agents.defaults.model and you can switch mid-session by updating the config and restarting the gateway.

Yes, but with caveats. OpenClaw works on Windows in two ways:

1. Via WSL2 (strongly recommended): Runs in a Linux environment inside Windows. Most stable, best supported. Requires a one-time WSL2 setup (about 15 minutes). See the install guide for step-by-step.
2. Native Windows (PowerShell): Works for basic use but some features behave differently. You'll hit PATH issues after install (documented in the error fixes section).

If you have the option, use WSL2. It eliminates a whole class of Windows-specific quirks.

OpenClaw handles context window limits automatically through compaction. When a session gets long enough to approach the model's context limit, OpenClaw compresses the older parts of the conversation into a summary, freeing up space for new messages.

Before compacting, OpenClaw triggers a silent "memory flush," reminding the agent to write anything important to the memory files first. This way, significant information isn't lost.

The compaction is transparent. You'll notice a brief pause but the conversation continues. The agent will have less detailed memory of the very early parts of a long session, but key facts written to MEMORY.md are preserved.

For very long, complex tasks, best practice is to start fresh sessions for distinct topics rather than carrying everything in one endless session.

Each session starts fresh with the AI model. There's no inherent memory in the model itself. OpenClaw's memory system works by reading files at session start.

For the agent to remember something across sessions, it must write it to a file: either the daily log (memory/YYYY-MM-DD.md) or the long-term memory file (MEMORY.md).

If you find the agent forgetting important things, explicitly tell it: "Write that to memory" or "Remember this for future sessions." You can also manually edit MEMORY.md to add important context that the agent should always have.

Daily logs are read for today and yesterday. Anything older than yesterday is not automatically loaded (though the agent can search older logs if you ask it to).

Yes, and it's a great use case. Running on a VPS means your agent is always on even when your personal computer is off. Recommended setup:

• Ubuntu 22.04 LTS VPS (DigitalOcean, Linode, Hetzner all work well)
• Minimum: 1 vCPU, 1GB RAM (2GB recommended for comfortable headroom)
• Use a clean base image; avoid marketplace 1-click images for OpenClaw
• Install with the Linux installer
• Set up with --install-daemon so it starts automatically on server restart

For remote access to the control panel, see the remote access guide (Tailscale is the simplest approach).

They're built for different jobs:

• Claude Code is a coding assistant you invoke in your terminal for specific coding tasks. It's excellent at writing, reviewing, and debugging code. Not designed for 24/7 operation, messaging app integration, or proactive automation.
• OpenClaw is a persistent gateway agent. It lives on your machine 24/7, connects to your messaging apps, has a memory system, can run on a schedule, and handles all kinds of tasks, not just coding.

Many power users run both. Use Claude Code when you're in a development workflow and want to write code. Use OpenClaw for everything else: automations, briefings, research, ongoing tasks.

Interestingly, OpenClaw can actually spawn Claude Code as a sub-agent for coding tasks within a larger workflow.

n8n and Zapier are workflow automation tools where you define exact steps, exact triggers, exact outputs. They're excellent at deterministic automation: "when X happens, do Y."

OpenClaw is an AI agent that can reason, adapt, and make judgment calls. "Read this 50-page document and tell me if there's anything that should concern me" is not something n8n can do. Reading your email inbox and deciding which ones actually need a response requires judgment that rule-based automation can't match.

In practice, they complement each other. Zapier is great for triggering OpenClaw (e.g., "when a new email arrives, run this agent task") or for publishing its output (e.g., "post this to Slack"). OpenClaw is great for the intelligent processing in between.

Honestly: OpenClaw requires more technical comfort than most consumer apps. You'll run commands in a terminal, edit a JSON config file, and troubleshoot the occasional error.

That said: if you can follow the install guide here step by step, and you're willing to spend a few hours on setup, you can get it working. The install guides at Prentus AI are written specifically for non-developers.

What determines success more than technical skill: patience and willingness to read the error message carefully. Most install problems have simple fixes if you search for the exact error text.

If you're truly not comfortable with terminals at all, the more realistic path is to hire someone to set it up for you (a one-time cost) and then use the finished product through Discord/WhatsApp which requires no technical knowledge at all.

Start with the morning briefing. It's the most popular first use case for good reason:

• High immediate value (you'll use it every day)
• Teaches you cron scheduling, channel delivery, and web search tools
• Low risk (read-only operations, no writing to external systems)
• Gives you something tangible to show people if you're exploring this for a business

Once that's working, tackle email triage next. That's where most people find the biggest time savings for their day-to-day work.

In order of speed:

1. Discord: discord.com/invite/clawd, the most active community. Search before posting; most common questions have been answered.
2. Reddit: r/openclaw, good for longer troubleshooting threads
3. Official docs: docs.openclaw.ai, the authoritative reference, especially the troubleshooting section
4. GitHub Issues: github.com/openclaw/openclaw, for actual bugs, not setup help