Architectural Constraints Alignment in AI-assisted, Platform-based Service Development

📅 2026-05-06
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📝 Abstract
AI-assisted development tools enable rapid prototyping of services but often lack awareness of architectural constraints, infrastructure dependencies, and organizational standards required in production environments. Consequently, generated artifacts may exhibit brittle behavior and limited deployability. We propose a retrieval-augmented scaffolding approach that combines platform-based code generation with agentic clarification loops to expose and resolve architectural constraint ambiguities. By combining template retrieval with structured interaction, the method embeds production-relevant considerations during service scaffolding. Evaluation indicates improved architectural consistency and deployability compared to general-purpose AI code generation workflows, suggesting that constraint-aware retrieval is essential for aligning AI-assisted service development with production software engineering practices.
Problem

Research questions and friction points this paper is trying to address.

architectural constraints
AI-assisted development
service deployability
production alignment
platform-based development
Innovation

Methods, ideas, or system contributions that make the work stand out.

retrieval-augmented generation
architectural constraints
AI-assisted development
scaffolding
deployability
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