OpenAI has released a detailed prompting guide for its latest flagship model, GPT-5.1, signaling a significant shift in how developers and users must interact with its increasingly sophisticated artificial intelligence. The new model is engineered to balance high-level intelligence with speed and to follow user instructions with unprecedented precision.[1] This heightened capability for instruction-following necessitates an evolution in prompting strategies, moving away from conversational coaxing towards more structured and explicit commands. The guide serves as a crucial manual for developers, walking them through the process of updating existing workflows and adapting their prompting habits to unlock the full potential of the new system, which introduces features like adaptive reasoning and greater control over the AI's personality and tone.[1][2]

The core advancements in GPT-5.1 are what drive the need for this updated approach to prompting. A key feature is its adaptive computation, which allows the model to allocate more "thinking time" and resources to difficult problems while handling simpler requests more quickly and efficiently.[2][3] This is surfaced to users through two distinct modes: "Instant," which prioritizes speed for conversational and summary tasks, and "Thinking," which engages in slower, more deliberate reasoning for complex logic and multi-step planning.[2][4][5] Furthermore, GPT-5.1 introduces a new "none" reasoning mode designed for low-latency applications, providing a strong alternative for developers migrating from earlier models like GPT-4.1.[1][6] The model's steerability has also been significantly enhanced, allowing for fine-tuned control over its personality, tone, and the verbosity of its output.[1][4] These architectural changes mean that prompts that worked well for GPT-5 or GPT-4 may no longer be optimal, and the new guide provides a roadmap for navigating these differences.

A central theme of the new prompting guide is the imperative for clarity and precision. Because GPT-5.1 is vastly better at adhering to instructions, ambiguous or contradictory prompts are more likely to produce strange or inconsistent behavior.[7] The guide effectively advises users to treat prompts less like conversational requests and more like technical specifications. Developers are encouraged to reduce conflicting instructions, such as asking the model to "be very concise and explain in detail" simultaneously.[7] For those migrating from GPT-5, OpenAI highlights the need to be more explicit in prompts to ensure persistence and completeness, as the model's better-calibrated reasoning can sometimes lead it to be overly concise.[1] Similarly, while the model is generally more detailed, its verbosity can be inconsistent, making explicit instructions on the desired level of detail and output format essential for reliable performance.[1]

The guide places a heavy emphasis on optimizing GPT-5.1 for agentic and coding tasks, which represent a substantial leap forward for the model.[8] It recommends that developers prompt the model to "think carefully" and plan extensively before making function calls, as well as reflect on the outcomes of previous calls to ensure a user's query is fully resolved.[1] This structured approach to reasoning improves the reliability of complex, multi-step workflows. For coding applications, the guide introduces new, powerful tool types. A notable example is the `apply_patch` tool, which allows GPT-5.1 to create, update, and delete files using structured diffs rather than just suggesting code edits, enabling more robust and iterative development cycles.[1][9] The guidance also encourages the use of the new Responses API, which persists reasoning between tool calls, leading to more efficient and intelligent agentic behavior.[8][6]

In conclusion, the release of the GPT-5.1 prompting guide marks a pivotal moment for the AI industry, reflecting the technology's maturation from a probabilistic text generator into a more deterministic and reliable instruction-following engine. The implications are significant for both developers and the businesses that rely on their applications. Developers must now adopt a more rigorous and structured approach to prompt design, treating it as a form of light-spec programming. This shift demands greater precision but in return offers unprecedented control and reliability, allowing for the creation of more complex and dependable AI agents and workflows.[7] The enhanced steerability over personality and tone also opens new avenues for creating sophisticated, customer-facing applications that can adhere to specific brand voices. As the industry moves towards building more autonomous AI systems, the principles of clarity, structured reasoning, and precise instruction-following outlined in this guide will likely become the standard for effective human-AI interaction.