VQV Signal
AI coding agents now support multiple software development stages beyond code completion, including planning and testing. This work proposes a lightweight, specification-driven lifecycle to better integrate AI agents with established software engineering practices.
AI coding agents now support multiple software development stages beyond code completion, including planning and testing. This work proposes a lightweight, specification-driven lifecycle to better integrate AI agents with established software engineering practices.
AI-assisted summary based on the listed source.
AI coding agents increasingly support software development beyond code completion, including planning, implementation, testing, and repository-level task execution. Their practical use, however, often remains only weakly connected to established software engineering practices. The aim of this work is to develop...
Bridging AI coding tools with traditional software engineering can improve governance and effectiveness in AI-assisted development. This approach aims to make AI agents more practical and aligned with real-world development workflows.
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VQV surfaced this signal because it is recent, relevant to AI Coding Tools, connected to arXiv.
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