Teaching AI to Terraform (So We Don't Have To)

Join us as Sam demonstrates how to teach AI to write Terraform configurations using Model Context Protocol (MCP) servers. Sam introduces the Terraform MCP server and walks through practical demos showing how AI can understand and safely interact with your infrastructure. You'll see live examples of AI planning, generating, and evolving Terraform configurations - from creating landing zones to setting up workspace variables automatically. Whether you're managing complex multi-cloud environments or just getting started with infrastructure as code, this episode demonstrates how MCP servers bridge the gap between AI capabilities and real-world Terraform workflows. Learn how to get started, which Claude models work best for different tasks, and best practices for integrating AI into your IaC pipelines. Timestamps 0:00 Welcome & Introduction 4:37 Sam McGeown's Background 6:02 Introduction to Terraform MCP Server 12:35 What is Model Context Protocol? 18:22 Setting Up the Terraform MCP Server 24:16 Demo: Claude Desktop Integration 30:41 Creating Infrastructure with AI Prompts 36:52 Reading & Analyzing Existing Terraform Code 42:18 Generating Landing Zone Configurations 47:35 Working with Terraform Workspaces 50:37 Creating Variables Automatically 52:14 Model Selection: Sonnet vs Opus 55:11 Live Demo: Workspace Variable Creation 58:33 Getting Started & Resources How to find Sam: https://www.linkedin.com/in/sammcgeown/ Links from the show: https://developer.hashicorp.com/terraform/mcp-server