What Can You Use LLMs For? Four Use Cases and a Rule of Thumb
This article is a practical guide to where LLMs actually shine. It walks through four common use cases: converting unstructured data into structured tables, labeling and classification, question answering, and agents that take actions in the world. It also warns against shipping naive chatbots, pointing out that guardrails are never perfect and citing the infamous Gemini incident where the model told a user to 'please die'. The core argument is a simple rule of thumb: if a system can be built deterministically, it should be. LLMs are only worth the complexity for tasks that are either too expensive for humans to do at scale or too ill-defined for deterministic code to handle. Examples include 19th-century hawk migration logs, The Prompt Report's suicide-risk classification case, and the DeepResearch pattern.