prompt engineering
Prompt engineering is the practice of crafting, refining, and iterating prompts like input instructions, context, and examples to guide a generative model toward producing desired, high-quality, and reliable outputs.
It treats the underlying model’s parameters as fixed and focuses on optimizing the input rather than retraining the model.
Prompting techniques may include the following:
- zero-shot and few-shot prompting
- structured instructions
- chain-of-thought or reasoning-style cues
Prompt designers typically distinguish between system (global behavior) and user (task-specific) messages, include retrieved or contextual grounding information, and iterate on prompt design based on output quality, feedback, and evaluation.
Related Resources
Tutorial
Prompt Engineering: A Practical Example
Learn prompt engineering techniques with a practical, real-world project to get better results from large language models. This tutorial covers zero-shot and few-shot prompting, delimiters, numbered steps, role prompts, chain-of-thought prompting, and more. Improve your LLM-assisted projects today.
For additional information on related topics, take a look at the following resources:
By Leodanis Pozo Ramos • Updated Dec. 7, 2025
