By now, even the most casual generative-AI tinkerer knows that the specificity of one’s prompt determines, to a large extent, the quality of a model’s output—whether that’s a realistic image, an on-topic paragraph, or a code block that actually works.
Many industry leaders claim that prompt engineering—the practice of tailoring your input to improve the model’s on-task performance—is a skill with a limited shelf life, given how rapidly AI technology is advancing. That remains to be seen; for now and for the foreseeable future, designing better prompts remains a practical skill worthy of data and ML practitioners’ attention.
To help you develop your prompting chops, we’ve selected some of our best recent articles on the topic, covering a wide spectrum of use cases and experience levels. Let’s prompt away!