This post shares a personal journey of exploring agentic DevOps using Claude Code, shifting from traditional tool-driven workflows to AI-orchestrated engineering.
•CLAUDE.md serves as a control system for AI behavior, defining architecture, deployment workflows, and engineering constraints (e.g., no JavaScript frameworks allowed)
•Terraform automation was implemented using slash commands (/tf-plan, /tf-apply) to generate configs, validate changes, and suggest improvements
•Secure CI/CD pipelines were built with GitHub Actions and OIDC, eliminating long-lived AWS credentials
•Specialized AI sub-agents were created for security checks, cost optimization, and deployment workflows
•Model Context Protocol (MCP) servers enable AI to interact with live infrastructure and execute real DevOps tasks
This summary was automatically generated by AI based on the original article and may not be fully accurate.
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