Adding AI to Your IaC Workflow Without Starting Over
summary
Spacelift Intent is an open-source MCP server that provisions cloud resources by calling OpenTofu/Terraform provider APIs directly — no HCL, plan, or apply — and records state in a local SQLite DB. Demo provisions an S3 bucket with versioning in ~30 seconds and a VPC+EC2 stack under three minutes, shows drift detection and revert or adopt reconciliation, and tears down resources in dependency order. Claim: use Intent for fast prototyping workflows while keeping GitOps/Terraform for production; PR review latency (two days) is the real cost.
AI-written summary · about
chapters (9)
- 0:00Introduction
- 1:10AI in infrastructure workflows
- 5:04Introducing Intent MCP server
- 13:07Demo setup and configuration
- 16:39Creating S3 bucket with AI
- 20:50Building full dev environment
- 23:43Drift detection and audit trail
- 25:54Production vs prototyping
- 27:20Q&A session
related talks
12mDemo Theater: Practical Path to Infrastructure as Code at Scale
27mAdvanced Multipurpose Infrastructure: A Self-Managed Cloud Environment with HashiCorp Terraform
09mClosing Session
31mCommodified IaC using Terraform Cloud
32mAI Meets IaC — Intelligent Terraform Authoring on Azure
31mEnter the Machines: Reducing Friction in DevOps Using AI
25mAccelerating Azure IaC: Copilot, Terraform, and the power of AI
14mInfrastructure as Code IaC
