
30/08/2025
1. Be precise and avoid conflicting information
↳ GPT-5 models are significantly better at instruction following
↳ But they can struggle with vague or conflicting instructions
↳ Clear, specific prompts = better results
2. Use the right reasoning effort
↳ Use “Thinking” and “Pro” for the most complex tasks
↳ Use “Instant” for simple problems
↳ Match the effort to the complexity
3. Use XML-like syntax to help structure instructions
↳ Delineate different sections of your prompt to improve GPT-5’s understanding
↳ Example : I'm a software developer Explain object-oriented programming
↳ Benefit: Reduces misinterpretations
4. Avoid overly firm language
↳ With other models you might use firm language like "Be THOROUGH"
↳ GPT-5 can backfire as the model might overdo what it would naturally do
↳ Less aggressive = more effective
5. Give room for planning and self-reflection
↳ Let the model think first before taking action
↳ Use tags like to improve reasoning
↳ Allows the model to plan and iterate on the best approach
6. Control the eagerness of your coding agent
↳ GPT-5 tries to be thorough and comprehensive by default
↳ Use prompting to control how eager it should be
↳ Set boundaries on scope and ex*****on
I’d add a 7th tip to this list:
Append your prompt with
↳ “Say ‘I don’t know’ if you can’t find reliable evidence for your claims.”
Then prompt GPT-5 to
↳ “Ask me clarifying questions until you are confident in answering.”
This is a great way to minimise model hallucination.
https://cookbook.openai.com/examples/gpt-5/gpt-5_prompting_guide
https://cdn.openai.com/API/docs/gpt-5-for-coding-cheatsheet.pdf