What happens when you combine AI creativity with real DevOps engineering and HashiCorp tooling? In this session, I’ll share how I created and evolved my entire professional website—from a single AI-generated draft to a fully automated, production-ready cloud platform—using Lovable AI, Terraform, and GitHub Actions.

The journey started with a prompt engineered in ChatGPT to describe the ideal structure of my site. From that, Lovable created the first one-page version. But real scalability required engineering: I modularized the site into multiple pages, versioned the code in GitHub, and migrated all legacy content into a new, modern architecture.

To bring everything to production, I built a complete Infrastructure as Code stack with Terraform on Azure. All infrastructure—storage, networking, domains, and deployment pipelines—became declarative, reproducible, and fully Git-driven.

I designed a CI/CD pipeline following a testing pyramid for Terraform, including:

• Terraform fmt, validate, and init
• TFLint for best practices
• Checkov and tfsec for security scanning
• Terraform-docs autogenerated in each commit
• Plan workflow for PRs with automatic comments
• Apply workflow with concurrency control, summaries, and environment variables

Everything is automated through GitHub Actions, ensuring that every change, from IaC to content updates, goes through a secure and auditable pipeline before reaching production.

This talk blends real-world engineering, AI-assisted development, best practices in Terraform, and production-grade DevOps.

After this session, attendees will understand how to:

• Use AI as an accelerator without losing architectural rigor
• Structure Terraform for maintainability and security
• Apply DevSecOps practices to IaC workflows
• Build a complete CI/CD pipeline for Terraform
• Deploy and operate a real project using HashiCorp tooling

A practical story of how AI + Terraform + DevOps can multiply productivity and deliver real business value.