13.2What AI Agents Excel At in IaC Reviews

Capability	Rule-Based Tools	AI Agent
Security misconfigurations	Check against known patterns	Reason about context-specific risk
Cost optimization	Flag specific instance types	Suggest right-sizing based on workload
Operational risk	Cannot assess	Explain impact of resource replacements
Environment drift	Diff configs	Explain intentional vs accidental differences
Change summarization	List resources changed	Natural language summary of what and why
Compliance mapping	Check against rule IDs	Map changes to specific compliance frameworks

Specific Examples

1. Detecting security misconfigurations -- AI models trained on cloud security best practices can flag overly permissive IAM policies, unencrypted resources, and public network exposure, with explanations of the specific risk.

2. Identifying drift between environments -- comparing staging and production Terraform to find intentional vs accidental differences. An AI can explain "staging has a smaller instance type (intentional cost saving) but also has a missing encryption setting (likely accidental)."

3. Suggesting cost optimizations -- flagging oversized instances, missing reserved capacity, or resources that should use spot pricing, with estimated savings.

4. Explaining complex changes -- translating a 200-line Terraform plan into a human-readable summary: "This change will replace the RDS instance (causing 5 minutes of downtime) and add a new read replica."