Don't Let the Model Write the YAML: Deterministic, Minimal-Diff GitOps Remediation from LLM-Proposed Field Changes

The paper investigates how large language models (LLMs) can propose changes to Kubernetes configuration files in a GitOps workflow. It shows that having the model directly generate edited files or diffs is unsafe for unattended automation, as current text‑generation strategies either fail to apply patches or silently misapply them. The authors propose a deterministic, minimal‑diff approach where the model emits only a structured intent for a field change, and a pipeline locates and replaces the exact character span in the raw YAML, preserving formatting and comments while guaranteeing correctness and O(1) generation cost.

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• llms
• agents
• benchmarks