OpenClaw is the best open source personal AI assistant in 2026 — 200K+ GitHub stars, native WhatsApp and Telegram integration, and a skills system that makes it genuinely useful. This live workshop shows you how to build and deploy it in 4 hours.
By Packt Publishing · Refunds up to 10 days before
OpenClaw went viral in 2026 because it offered something no proprietary AI assistant could — complete transparency, full customisation, native messaging integration, and zero ongoing AI costs. This workshop builds on that foundation to give you a production-ready open source personal AI.
OpenClaw is the open-source personal AI assistant that went viral in early 2026 with 200K+ GitHub stars. It runs on your own devices and connects to WhatsApp, Telegram, Slack and more. No subscription. No data leaving your machine.
Docker Model Runner is Docker's native feature for running large language models locally on your machine. It gives you an OpenAI-compatible API that OpenClaw uses as its AI brain — complete data privacy, no cloud costs.
OpenClaw gives you the assistant interface and messaging integrations. Docker Model Runner gives you the AI brain running privately on your machine. Together they create a production grade private AI assistant you fully own.
Setting this up from scattered documentation takes days of debugging. This live workshop gives you a complete guided build in 4 hours with a live instructor answering your questions. Packt has delivered 108 workshops worldwide.
Six modules. Four hours. One working private AI assistant by the time you finish.
Understand the Gateway, channels, and skills architecture. Set up and configure OpenClaw locally from scratch.
Run and manage local LLMs using Docker Model Runner. Pull models, configure memory, and understand the OpenAI-compatible API.
Configure DM pairing, allowlists, sandbox mode, and proper access controls for your local AI deployment.
Deploy your AI assistant to real messaging platforms without sending data to any third party cloud service.
Design an extensible assistant architecture. Add skills, configure personality, and set up proactive automation.
Deploy your OpenClaw and Docker setup to a VPS for always-on availability running 24 hours a day.
Concrete working deliverables — not just theory.
A fully functional local AI assistant running on your machine
Docker Model Runner configured with your chosen LLM model
OpenClaw connected to WhatsApp or Telegram
Security and privacy configuration you can trust
A reusable architecture for future AI assistant projects
Certificate of completion from Packt Publishing
Rami Krispin builds open source AI systems in production environments — not just for tutorials.
Rami is a Senior Manager of Data Science and Engineering, Docker Captain, and LinkedIn Learning Instructor with deep expertise in building and deploying production AI systems. He guides you step by step from a blank terminal to a fully deployed private AI assistant — answering your questions live throughout the 4-hour session.
You do not need to be an expert. You do need the basics.
Common questions about the workshop, what to expect, and how to prepare.
OpenClaw combines four things no other open source personal AI assistant offers together: native WhatsApp and Telegram integration without third-party services, Docker Model Runner compatibility for local LLM inference, a Python-based extensible skills system, and an active community that reached 200K+ GitHub stars in 2026.
For personal assistant use cases in 2026, yes. Modern open weight models like Llama 3 and Mistral 7B handle the tasks most people use personal AI assistants for — answering questions, helping with writing, summarising content, and general conversation — at quality comparable to proprietary models.
Yes. OpenClaw is fully open source and the instructor covers the architecture clearly enough that you can extend it after the workshop. The skills system is Python-based making customisation accessible to any Python developer.
OpenClaw uses a permissive open source licence. The open weight models (Llama, Mistral, Phi) all have permissive licences for personal use and most commercial use cases. The instructor covers the relevant licence considerations during the workshop.
Open source code is auditable — you can verify exactly what network calls OpenClaw makes and confirm it sends no conversation data to external AI services. Proprietary AI assistants cannot offer this level of transparency. Combined with Docker Model Runner's local inference, your open source personal AI assistant provides a verifiably private experience.
The open source AI assistant community in 2026 is very active. OpenClaw's rapid growth to 200K+ stars reflects developer enthusiasm. Docker Model Runner benefits from Docker's large developer ecosystem. Active communities mean regular updates, new features, and community support for deployment questions.
4 hours. Live instructor. Best open source personal AI assistant by the end. Seats are limited.
Register Now →Sunday April 26 · 9am to 1pm EDT · Online · Packt Publishing