Prompt engineering is the practice of designing and refining prompts to improve the quality, relevance, or reliability of AI system outputs.
Prompt engineering involves experimenting with how instructions are phrased, what context is included, what format is requested, and how constraints are specified. It is an iterative process — you try a prompt, evaluate the output, and adjust.
Prompt engineering can improve results but cannot overcome fundamental model limitations. If a model lacks reliable knowledge on a topic, better prompting will not reliably fix that.