You are integrating Claude Code into your Continuous Integration/Continuous Deployment (CI/CD) pipeline. The system runs automated code reviews, generates test cases, and provides feedback on pull requests. You need to design prompts that provide actionable feedback and minimize false positives. Your pipeline includes a release notes generation step that classifies and summarizes approximately 200 commits at the end of each weekly release cycle. Each commit is currently sent as a separate Messages API call using a Sonnet-tier Claude model. The release notes aren't needed until the following morning (results have ~12 hours of acceptable latency). Your team needs to reduce per-token API cost for this step while keeping the same model and prompts (no change to model tier or output quality). Which approach satisfies all of these constraints?
Select one answer.
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