A developer built a non‑conversational AI agent that turns Terraform‑defined AWS infrastructure into clear, Product Manager‑friendly explanations. The tool reads a short, human‑written summary and outputs a high‑level system overview, skipping low‑level syntax while highlighting intent, impact, and business risks.

Product managers routinely ask how new infrastructure affects user experience, data residency, scaling, cost, and security. By translating technical details into business terms, the agent lets them assess trade‑offs quickly, align budgets, and communicate decisions to stakeholders without wading through code.

The system relies on an Algolia index named terra‑pr containing 13 curated records for key AWS services—EKS, EC2, Lambda, API Gateway, RDS, S3, CloudFront, CloudWatch, IAM, VPC, and billing. Gemini powers the LLM, and a tightly engineered prompt restricts scope to AWS, Terraform, and the Product Manager persona.

Fast, context‑aware retrieval keeps explanations accurate and reduces hallucination, making the agent a practical tool for cross‑functional teams. As cloud adoption grows, tools that bridge engineering and product perspectives will become essential. Watch for broader adoption of retrieval‑augmented LLMs in infrastructure documentation.