Prompt engineering best practices
Better prompts mean better products. These six practices will help you write prompts that are reliable, testable, and easy to improve over time.
Start with 'You are a...' so the model knows the tone, expertise, and audience. A 'senior technical writer' answer differs from a 'beginner-friendly tutor' answer for the same question.
Tell the model what it needs to know before you ask for the output. Background, constraints, and format all belong in the context section.
One or two input/output examples (few-shot prompting) teach the pattern faster than a long description. Examples are especially useful for formatting, classification, and extraction.
Ask for JSON, bullet points, a table, or a specific length. The more precise the format instruction, the less cleanup you have to do later.
Limit length, tone, topics, or citations. Constraints reduce hallucinations and keep outputs aligned with your product's needs.
A small wording tweak can change output quality, cost, or latency. Run the old and new prompt against the same input to see the real difference.
Test your prompts as you improve them
PromptForge versions every prompt edit and lets you run two versions side by side against real models. See which one is faster, cheaper, and more accurate — without writing any API code.
- Save unlimited prompt versions
- Run A/B tests across models
- Keep full run history