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AI Coding Agents on Spring Projects: Live Pipelines, Verifiable Loops, and Context Governance

AI Coding Agents on Spring Projects: Live Pipelines, Verifiable Loops, and Context Governance

·2826 words·14 mins
For engineers already shipping services on the JVM and web stacks, this article starts from a typical Spring Boot + Kotlin real-time interactive application, traces the data path from database signals through reactive SSE to the browser, and breaks human–agent collaboration into three verifiable layers: compile-and-test closure, versioned project memory (CLAUDE.md, rules, Skills), and Hooks plus MCP on the tool-call path. The second half covers gaps in tests and state machines caused by spec-less iteration, how structured clarification (Interview) writes navigation and security decisions into the specification, and how cross-cutting steps can be silently dropped in long conversations—with ideas for segmented execution.