OpenAI Prompt Guide: Define Outcomes Over Processes
APPSO · wechat · 2026-07-13
OpenAI's official prompt guide is generating buzz. The core discussion isn't about writing fancy prompts, but how to treat AI as a delivery-oriented work partner. Based on Codex tests, GPT-5.6 is more powerful in complex tasks but consumes more tokens; legacy skills and verbose templates can actually slow execution and pollute context.
The article summarizes OpenAI's current principles:
- Define outcomes before processes: Specify deliverables, audience, and completion criteria first. Don't micromanage every step unless necessary.
- Provide only context that changes results: More data isn't always better; focus on the most relevant, up-to-date information.
- Boundaries matter more than personas: E.g., maintain budget limits, use only specified sources, draft without auto-sending.
- Make acceptance criteria verifiable: E.g., reproduce bugs, rerun tests, check data consistency, rather than just asking for a "professional tone."
It categorizes use cases into three tiers: Chat for quick Q&A and drafts, Work for multi-source, multi-step tasks, and Codex for codebase debugging and verification. The conclusion: as models grow stronger, prompts resemble task briefs and acceptance contracts, not mystical templates.
Related event: OpenAI Releases Official Prompting and Workflow Guide for Codex(3 posts)→
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