prompt-engineer

Reduce hallucinations by adding clear instructions, XML-structured prompts, and quality safeguards grounded in reference materials. Multishot examples and prompt chaining further constrain the model to generate accurate, consistent results with fewer unsupported claims.

Structure complex multi-step workflows through prompt chaining, passing XML-structured outputs between sequential calls. This method allows language models to handle intricate tasks reliably by breaking them into manageable, well-defined steps with strict format control.

Add guardrails against jailbreaks and prompt injection by implementing safety improvements directly within the prompt design. Tightening instructions, applying structured XML tags, and using reference-grounded safeguards mitigate security risks in production workflows.

Models give messy answers due to vague instructions or missing context. Fix this by redesigning the prompt with clear instructions, adding multishot examples for guidance, and applying XML structure until the output becomes stable and reliable.

Use multishot prompting instead of a single system prompt when tasks are complex and require consistent format control. Providing multiple examples guides the model to recognize patterns and produce reliable results for advanced prompt techniques.