Python is excellent for experimentation, but when it’s time to ship AI agents to production, you need the performance, concurrency, and type safety of Go.
​In this hands-on workshop, we will abandon the Python notebooks and build a robust, autonomous AI Agent from scratch using Go. We won’t just be making API calls; we will architect a system capable of reasoning, planning, and executing tools safely.

​What we will build:
We will build a CLI-based DevOps Agent. By the end of the session, you will have a compiled binary that you can ask to perform tasks (e.g., "Check the disk usage, and if it's over 80%, compress the log folder").

​The Workshop Flow:

​The Foundation: creating a clean interface to LLMs (OpenAI/Anthropic) decoupling the provider from the logic.

​The Brain: implementing the ReAct (Reason + Act) loop using a custom Go state machine.

​The Tools: using Go interfaces and struct tags to create strongly-typed tools that the Agent can invoke.

​Safety & Concurrency: adding context for timeouts and Goroutines for parallel processing.

​No magic frameworks. Just standard library Go and solid engineering principles.