To get the most from GPT-5, the first rule is to write prompts that are specific, clear, and structured. The GPT-5 Prompting Guide emphasizes stating your goal directly, specifying the output format, and including any constraints or examples. For instance, instead of asking “Explain how this code works,” you might say, “Explain how the following Python function works, in numbered steps, and include an example of its output.” This gives GPT-5 both a target and a structure to follow, which leads to more consistent results. It’s also useful to include relevant context—such as previous conversation history or supporting data—so the model doesn’t need to guess at missing details.
GPT-5 offers additional control through parameters like verbosity and reasoning_effort. You can set verbosity to “low” for concise summaries, “medium” for balanced detail, or “high” for deep explanations. The reasoning_effort parameter can be “minimal,” “medium,” or “high,” giving you control over how much processing the model does before answering. In practice, this means you might run with minimal for quick lookups in a chatbot, and high when performing a multi-step reasoning task like refactoring a large codebase. For agent-like use cases, you can also supply tool-call preambles—short explanations telling GPT-5 how and when to use external tools—which improves reliability in automated workflows.
Finally, treat prompt design as an iterative process. Test different versions of your prompt, review the outputs, and refine the instructions to reduce ambiguity. GPT-5 can assist in this process—one approach is to ask GPT-5 to evaluate your prompt and suggest improvements before running it for the final task. Breaking down complex instructions into ordered steps also helps, especially for long or technical processes. When handling multimodal inputs, be explicit about how the model should use each type of data. By combining clear instructions, parameter tuning, and iterative refinement, developers can make GPT-5’s responses more accurate, reliable, and aligned with the needs of their applications.