LLM-Augmented Release Intelligence: Automated Change Summarization and Impact Analysis in Cloud-Native CI/CD Pipelines
Cloud-native software delivery platforms orchestrate releases through complex, multi-stage pipelines composed of dozens of independently versioned tasks. When code is promoted between environments -- development to staging, staging to production -- engineering teams need timely, accurate communication about what changed and what downstream components are affected. Manual preparation of such release communication is slow, inconsistent, and particularly error-prone in repositories where a single promotion may bundle contributions from many authors across numerous pipeline tasks. We present a framework for AI-augmented release intelligence that combines three capabilities: (1) automated comm...
| Authors | Happy Bhati |
|---|---|
| Primary category | cs.SE |
| Published | 15 March 2026 |
| Last updated at source | 15 March 2026 |
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