[MS] AI Coding Agents and Domain-Specific Languages: Challenges and Practical Mitigation Strategies - devamazonaws.blogspot.com
1. Introduction AI coding agents/assistants such as GitHub Copilot have become common in modern software engineering workflows. Their strengths—rapid pattern completion, context-aware suggestions, and the ability to learn style from local code—stem from broad training on large corpora of public, general-purpose code. They perform best when the languages, libraries, and idioms requested by developers align with patterns they have seen many times before. Domain-Specific Languages (DSLs) break this assumption. DSLs are deliberately narrow, domain-targeted languages with unique syntax rules, semantics, and execution models. They often have little representation in public datasets, evolve quickly, and include concepts that resemble no mainstream programming language. For these reasons, DSLs expose the fundamental weaknesses of large language models when used as code generators. While AI coding agents excel at generating code for mainstream languages, recent research shows their accuracy ...