A developer has opted against using a large language model for refund eligibility checks, instead implementing a deterministic system using plain Java code. The decision was documented in ADR 001, prioritizing assertability, security against data injection, cost-effectiveness, and auditability over the perceived convenience of an LLM. This approach ensures that refund decisions are based on clear, verifiable facts like delivery and payment status, and adherence to a defined return window, with any edge cases becoming policy work items rather than LLM judgments. AI
IMPACT Highlights the trade-offs in using LLMs for business logic, favoring deterministic systems for auditable and cost-effective operations.
RANK_REASON Article discusses the implementation of a software tool (a refund eligibility checker) and its design choices, rather than a core AI release or research.
AI-generated summary · Google Gemini · from 1 sources. How we write summaries →