Prompt Engineering in Production: What Actually Matters
· 8 min read
Most engineers learn prompt engineering backwards. They start with "be creative" and "think step by step," iterate on a demo until it works, then discover in production that the model is hallucinating 15% of the time and their JSON parser is throwing exceptions every few hours. The techniques that make a chatbot feel impressive are often not the ones that make a production system reliable.
After a year of shipping LLM features into real systems, here's what actually separates prompts that work from prompts that hold up under load.
