CCA-F: Claude Certified Architect — Foundations

You are incorporating Claude Code into your Continuous Integration/Continuous Deployment (CI/CD) pipeline. The system performs automated code reviews, creates test cases, and gives feedback on pull requests. You need to craft prompts that deliver actionable feedback while minimizing false positives.

Your pipeline has a release-notes-generation step that classifies and summarizes approximately 200 commits at the end of each weekly release cycle. Each commit is presently sent as an individual Messages API call using a Sonnet-tier Claude model. The release notes are not required until the following morning (results can have approximately 12 hours of latency). Your team must lower the per-token API cost for this step while retaining the same model and prompts (with no change to model tier or output quality).

Which approach meets all of these constraints?