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tech 15 June 2026

Building Your Own AI Dev Platform in Your Homelab

Learn how to turn your homelab into an efficient AI development platform using OpenCode, Docker, and GitOps.

Article inspired by the original source
My Homelab AI Dev Platform ↗ rsgm.dev

Introduction

Imagine a space where you can freely experiment with AI technologies without the constraints of a formal work environment. This is exactly what a homelab AI Dev Platform offers. Using open-source tools and modern practices, you can create a sophisticated AI development environment that allows you to innovate at your own pace.

Why a Homelab for AI?

Before diving into the technical details, it’s important to understand why a homelab can be an ideal solution for AI development. With rising cloud service costs and the need for total control over data and processes, having a homelab gives you the freedom to experiment without cost or security limitations.

In 2023, 84% of companies invested in AI initiatives, but many struggle with managing costs and complexity (source: IDC). A homelab helps you overcome these challenges at a fraction of the cost.

OpenCode: The Cornerstone of Your Platform

OpenCode is an integrated development environment that allows you to code seamlessly while staying connected to your resources. With features like a built-in web server, a file browser, and persistent coding sessions, OpenCode offers unparalleled flexibility.

Setting Up OpenCode

To start, install OpenCode on a dedicated VM on your Truenas server. Configure it to run as a systemd unit, ensuring its continuous availability. OpenCode connects to your Git server with dedicated SSH keys, ensuring security and efficiency in managing code branches.

Managing Containers with Docker and GitOps

To effectively manage your services, use Docker Compose and Arcane. Move your Docker stacks under GitOps to automate deployments. This simplifies container updates and reduces the risk of human error.

Automating Updates

Use AI to summarize release notes and quickly identify critical updates. This reduces time spent on manual maintenance and improves system stability.

Security and Control

While AI can generate code, maintain strict control over the deployment process. Changes must pass through a PR (Pull Request) review before merging. This ensures that unreviewed code is never deployed, protecting your infrastructure.

Evolving into a Production Platform

While this document focuses on a homelab, the same architecture can be evolved into a production development platform. By integrating ephemeral containers and audit logs, you can offer developers an agile and secure environment.

Conclusion

Building a homelab AI Dev Platform is a powerful initiative for any developer looking to master AI. With the right tools and practices, you can transform your personal space into an innovation lab.

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