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  "path": "/t/natural-language-requests-vs-long-structured-prompts-what-actually-improves-performance/1381299#post_15",
  "publishedAt": "2026-05-20T12:07:17.000Z",
  "site": "https://community.openai.com",
  "textContent": "Thank you all for the replies. This has been very helpful for me.\n\nI don’t have many people around me who talk about prompting in this way.\nI’m not an engineer, and most prompt examples I usually see are template-like, so I sometimes wondered if my way of working with ChatGPT was a bit unusual.\n\nReading your examples was genuinely encouraging.\nIt’s fun to see that other people are using similar patterns in practice.\n\nI’m starting to think the useful distinction is not simply “natural language vs structured prompts,” but “which format works best at which stage of the workflow.”\n\nFor small tasks, natural language is often enough.\nFor larger tasks with many constraints, a structured format helps.\n\nBut in my experience, the strongest pattern is often:\n\nnatural conversation → structured artifact → execution or implementation\n\nSo maybe structured prompts are not always the starting point.\nSometimes they are an intermediate artifact created from the conversation.",
  "title": "Natural-language requests vs. long structured prompts: what actually improves performance?"
}