Compact Constraint Encoding for LLM Code Generation: Token Economics and Constraint Compliance
arXiv·medium signal
This empirical study investigates whether compact, structured constraint headers can replace verbose natural-language prompts for guiding LLM code generation — covering technology choices, dependency restrictions, and architectural patterns. The finding: compact encodings achieve comparable or better constraint compliance while using significantly fewer tokens, with direct cost implications for API-heavy development workflows. Practical for anyone paying per-token for code generation at scale.