Prompt Engineering Fundamentals
Core techniques for getting reliable, structured output from modern language models.
Be explicit about structure
Models follow structure better than they infer it. Specifying the exact output format — a JSON schema, a numbered list, a fixed set of headings — dramatically reduces variance compared to a vague instruction like 'summarize this.'
Show, don't just tell
Few-shot examples (showing 2-3 sample input/output pairs before the real request) remain one of the most reliable ways to steer tone, format, and edge-case handling, often outperforming longer prose instructions.
Iterate like an engineer
Treat prompts as code: version them, test them against edge cases, and measure output quality against a rubric rather than eyeballing a single response — this is what separates prompt engineering from prompt guessing.
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