Prompt guidance | OpenAI API
GPT-5.5 works best when prompts define the outcome and leave room for the model to choose an efficient solution path. Compared with earlier models, you can often use shorter, more outcome-oriented prompts: describe what good looks like, what constraints matter, what evidence is available, and what the final answer should contain. Avoid carrying over every instruction from an older prompt stack. Legacy prompts often over-specify the process because earlier models needed more help staying on track. With GPT-5.5, that can add noise, narrow the model’s search space, or lead to overly mechanical answers. For more detail on GPT-5.5 behavior changes, start with the Using GPT-5.5 guide. This guide focuses on prompt changes that follow from those behavior changes. The patterns here are starting points. Adapt them to your product surface, tools, evals, and user experience goals. Codex can implement the changes from this guide with the OpenAI Docs Skill. To use this skill in other coding agents,
GPT-5.5 GPT-5.4 GPT-5.3 Codex GPT-5.2 GPT-5.1 GPT-5 GPT-4.1 GPT-5.5 New in GPT-5.5 vs GPT-5.4 Shorter, outcome-first prompts usually work better than process-heavy prompt stacks. More efficient reasoning means `low` and `medium` effort should be re-evaluated before escalating. Preambles, `phase` handling, and assistant-item replay remain important for tool-heavy Responses workflows. Explicit personality, retrieval budgets, and validation rules help shape customer-facing and agentic UX. GPT-5.5 works best when prompts define the outcome and leave room for the model to choose an efficient soluti
Explore this link on the map →saved by
related reading
- The Shape of AI | UX Patterns for Artificial Intelligence Designshapeof.ai
- Cookbookcookbook.openai.com
- Impeccable: The missing upgrade to Anthropic's impeccable skillimpeccable.style
- Codex use casesdevelopers.openai.com
- Use Cases | Claudeclaude.com
- GitHub - brexhq/prompt-engineering: Tips and tricks for working with Large Language Models like OpenAI's GPT-4. · GitHubgithub.com
- There's An AI For That® — The front page of AItheresanaiforthat.com
- OpenAI | Research & Deploymentopenai.com
- Parsed | Custom, interpretable AI systems that continuously learnparsed.com
- Rewind.ai - Every AI Tool, Completely Freerewind.ai
- GitHub - affaan-m/ECC: The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond. · GitHubgithub.com
- Prompt generation | OpenAI APIplatform.openai.com