Prompt Engineering

The discipline of designing instructions for a language model to get the desired response. It’s not just “writing nicely”: it involves structuring context, examples, output format, constraints, and reasoning steps. A well-designed prompt can make a mediocre model useful without touching code or training.

When should I use Prompt Engineering at a company?

The first step in any generative AI project. Before discussing RAG or fine-tuning, measure how much a good prompt can get out of the base model. Many business use cases can be solved with high-quality prompting.

When is it NOT a good idea Prompt Engineering?

Expecting prompts to solve business knowledge problems (that’s what RAG is for) or deep-seated format/style consistency (that’s what fine-tuning is for). Also, prompts without systematic evaluation—without tests, you don’t know if you’ve improved.