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You are integrating Claude Code into your Continuous Integration/Continuous Deployment (CI/CD) pipeline.

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 request using a Sonnet-tier Claude model. The release notes are not needed until the following morning, providing approximately 12 hours of acceptable latency.

Your team must reduce the per-token API cost while retaining the same model, prompts, and output quality.

Which approach satisfies all these constraints?

A.

Issue the 200 Messages API requests concurrently because parallel execution reduces the per-token price.

B.

Submit the 200 requests through the Message Batches API with unique custom_id values and retrieve the results after the batch finishes.

C.

Concatenate all 200 commit messages into one Messages API request because reducing the number of requests always reduces token costs.

D.

Replace the Sonnet-tier model with a Haiku-tier model to obtain a lower per-token price.

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