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An AI agent is a language model in a loop that can take actions — run commands, edit files, browse, send messages. (The basics: agents and tool calling explained.) Here are popular open-source options and how to get started. Agent tools change very fast: always follow the project’s official README for the current install command.
In this article
The landscape
| Tool | What it is | Good for |
|---|---|---|
| OpenClaw | A self-hosted personal AI assistant that connects to chat apps (WhatsApp, Telegram and others), keeps memory and can run tasks on your machine | A personal assistant you control |
| OpenHands (formerly OpenDevin) | A coding agent that works in a sandbox: reads the repo, runs commands, writes code | Software tasks, fixing issues |
| Aider | AI pair programmer in your terminal that edits files in a git repo | Developers who like the command line |
| Open Interpreter | Lets a model run code on your computer to complete tasks | Data tasks, file conversions |
| n8n | Visual workflow automation with AI nodes | Business automations with an AI step |
| CrewAI / LangGraph | Python frameworks for building multi-agent apps | Developers building their own agents |
What you need first
- A model: an API key (OpenAI, Anthropic, Google, OpenRouter…) or a local model through Ollama.
- Node.js (for OpenClaw), Python 3.10+ (Aider, Open Interpreter, CrewAI) or Docker (OpenHands, n8n).
- Ideally a separate machine, VM or user account for agents that run commands.
Install sketches
OpenClaw
npm install -g openclaw@latest
openclaw onboard # guided setup: model provider, chat channels, permissions
Aider
python -m pip install aider-install && aider-install
cd your-project && aider --model <your-model>
Open Interpreter
pip install open-interpreter
interpreter # asks before running each command by default
n8n (Docker)
docker run -it --rm -p 5678:5678 -v n8n_data:/home/node/.n8n docker.n8n.io/n8nio/n8n
Then open http://localhost:5678. OpenHands also ships as a Docker image — follow its README, as the image names and flags change between versions.
Common issues
| Problem | Usually |
|---|---|
| “Command not found” after install | The npm or pip bin folder is not on PATH; reopen the terminal or add it. |
| Agent loops or gets stuck | Weak/small model or vague goal. Use a stronger model and give one clear task with a finish condition. |
| High API bills | Agents make many calls. Set spending limits on the provider dashboard; use cheaper models for simple steps. |
| Local model too slow | Not enough RAM/GPU; use a smaller or quantized model, or a cloud API. |
| Docker errors on Windows | Enable WSL 2 and virtualisation in BIOS; start Docker Desktop first. |
Safety rules (read these)
- Run agents in a sandbox, VM or separate user; never as administrator.
- Give the minimum permissions and API keys; use keys with spending limits.
- Keep “ask before running commands / sending messages” switched on.
- Don’t expose the agent’s web interface to the internet without authentication.
- Install skills/plugins only from sources you trust, and keep the software updated.
📎 Practice files for this article
- 📄All code from this post4 examples in one file, ready to open in your editor.⬇ SH · 781 B
Free to use for learning. Files with macros (.bas) are plain text — import them with Alt+F11 → File → Import File, and always test on a copy.
Atul (AJ) builds office-automation and local-first AI tools as Atulya AI, and works with Excel, SAP and Oracle EPM every day. He writes about the shortcuts, macros and automations that actually save time — plus the occasional wacky fact. Videos on YouTube: Lazy Automator AI (@LazyAutomatorAI).
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