Prompt engineering is the discipline of writing instructions to language models that produce reliably-good outputs. The category was bigger in 2023 when techniques like chain-of-thought, few-shot examples, and structured output were genuine breakthroughs; in 2026 most of those patterns are baked into the models themselves and the field has narrowed to specific high-stakes use cases — prompts for production systems, model-specific fine-grained control, jailbreak research, and adversarial prompt injection defense.
The honest framing in good courses is that prompt engineering for chat-style use is mostly common sense (be specific, give examples, ask for the format you want); prompt engineering for production matters because small wording changes can swing accuracy by 5-10 points on an eval set, and that swing is the difference between shipping and not.
