Why I Don’t Trust LLMs to Decide When the Weather Changed

Relying on a large language model (LLM) to determine if a weather forecast has "changed significantly" is unreliable because it replaces a clear, deterministic rule with a probabilistic interpretation. A more robust approach uses a hybrid system where traditional code acts as a "deterministic gatekeeper," making decisions by comparing forecast data against predefined thresholds. In this architecture, the LLM is only used *after* a significant change is detected, serving as a "narrator" to translate structured data about the change into a natural language alert. This method ensures that the core decision-making is testable, reproducible, and cost-efficient, separating the decision logic from the narrative explanation.