Still frustrated by ChatGPT’s rambling, off-topic responses? OpenAI recently updated its official prompt guide, systematically disclosing eight core techniques for getting large models to “follow instructions properly.” At the same time, OpenAI unveiled a “killer feature”—the new “Generate Anything” function, designed to let AI automatically generate professional, effective prompts for users, freeing them from the pain of designing prompts themselves.
The core philosophy of this guide is that users should treat ChatGPT as an assistant who delivers high-quality work but requires patient, upfront guidance. According to a report by QbitAI, to achieve the best results, users should switch to OpenAI’s latest and most powerful model, GPT-5.6 Sol, as newer models tend to be more amenable to prompt engineering.
Define Clear Objectives, Avoid Vague Instructions
The guide identifies vague instructions as the number one pitfall. If you simply wave your hand and say “write a poem about OpenAI,” the result may be uninspired. The correct approach is to specify upfront: create a short, inspirational poem about OpenAI, centered on the recent DALL-E product launch, and mimic the writing style of a famous poet. Similarly, when planning a weekend outing, you must clearly tell the AI whether you want to exercise, visit scenic spots, explore exhibitions, or find good food—otherwise, repeated revisions will only dampen your enthusiasm.
Use Delimiters to Separate “Instructions” from “Text”
During use, OpenAI recommends placing core requirements at the beginning of the prompt and using officially recommended delimiters such as “###” or triple quotation marks to clearly distinguish “instructions” from “text to be processed.” The guide emphasizes that this clear-cut structure effectively improves the model’s understanding of the task. For example, wrapping text in quotation marks before inputting instructions allows the model to grasp key points more accurately, avoiding outputs that “miss the mark.”
Provide Reference Examples to Prevent AI Freestyling
If you want ChatGPT to generate memes or copy in a specific style, don’t let it conjure things out of thin air. OpenAI points out that you should first provide the AI with references and explanations, clarifying the slogan content, placement, and expected effect. For instance, when creating memes, providing specific example images or text descriptions can significantly improve task completion and response speed.
Start Simple, Feed Examples Incrementally
You don’t need to dump all your data on the AI at once. The guide suggests first giving a basic instruction to observe performance, then feeding a few examples based on its shortcomings. If it still can’t get it right, consider doing some “ideological work”—feeding a large number of correct examples to solidify this capability into the model’s parameters. For example, in keyword extraction tasks, providing two to three standard “text-keyword” paired examples often allows the model to learn quickly and produce accurate results.
Give Specific Numbers, Avoid Vague Descriptions
For ChatGPT, precise instructions are the prerequisite for solid work. The guide illustrates this with an example: if you want a product description, instead of saying “describe it in a few sentences,” specify “describe it in a paragraph of 3-5 sentences.” Vague “few sentences” may confuse the AI, while specific numerical instructions allow it to immediately understand the task boundaries.
Tell It “What to Do,” Not Just “What Not to Do”
Many users, worried about the AI generating unwanted results, repeatedly instruct it “don’t alter the original meaning” or “don’t ask for private information.” OpenAI reminds users that after listing a series of “don’ts,” it’s more important to tell ChatGPT “what it should do” and “how to do it.” For example, when handling customer service conversations, you should not only prohibit asking for usernames and passwords but also clearly guide users to the specific path for viewing help documentation.
Code Generation Requires Guiding Keywords
When you need ChatGPT to generate code, the correct approach is to explicitly add guiding keywords like “import” or “SELECT” before the content. For example, adding “import” prompts the model to start writing a Python function, while adding “SELECT” prompts it to write an SQL statement. Throwing vague requirements at the AI is often far less efficient than a precise guiding keyword.
One-Click Prompt Generation: The Ultimate Shortcut
If you still find prompt writing challenging even after mastering the above techniques, OpenAI’s newly launched “Generate Anything” feature is the ultimate shortcut. Users simply need to describe what they want to do, and GPT will automatically generate the most suitable prompt. Whether it’s removing photobombers from a picture and beautifying the image, or composing a limerick based on your current mood, GPT strives to make it happen.
Technical Foundation: GPT-5.6 Sol and Codex Integration
Behind this prompt guide update lies OpenAI’s continuous iteration of its underlying models. According to a report by Geeky Gadgets, OpenAI has integrated Codex into ChatGPT, powered by the GPT-5.6 Sol model. This integration creates a unified platform designed to streamline the coding and collaboration workflow for developers. GPT-5.6 Sol introduces enhanced reasoning, an “Ultra Mode” for handling complex tasks, and automatic task allocation, capable of breaking down large projects into manageable sub-tasks for parallel processing.
Additionally, the new platform introduces the Appshot tool, which captures application context to automate repetitive tasks, and the Sites feature, which simplifies deployment through built-in hosting and database support. These enhanced underlying capabilities are precisely what give ChatGPT the confidence to understand and execute complex prompts more accurately.
Industry analysts believe that OpenAI’s systematic disclosure of prompt techniques and the launch of automation tools signal that large model applications are moving from a “technology novelty” phase into a “deep taming” stage. For ordinary users, mastering these techniques will significantly reduce the communication cost with AI; for developers, the integration of Codex and the enhancement of model reasoning capabilities will further improve the efficiency and quality of software development.
