OpenAI has revealed the meta-prompt for its new o1 model family. By detailing what makes its prompt system tick, OpenAI is helping developers improve and fine tune how their products interact with its growing ecosystem of apps and sites.


The meta-prompt (a prompt optimizer) and system prompt (a model conditioner) operate behind the scenes, issuing detailed instructions that dictate how the AI should behave throughout an interaction. When users initiate a conversation, the meta-prompt has already set the stage, guiding the AI on everything from understanding the main objective of a task to structuring its output. This includes specifics such as preserving the user’s original content, offering concise improvements when necessary, and ensuring that the AI follows clear reasoning steps before presenting a conclusion


“A meta-prompt instructs the model to create a good prompt based on your task description or improve an existing one,” OpenAI said in its official platform guide. This provides a lot of technical and relevant information to squeeze the most out of its models, including a suite of examples of prompts, tips to increase accuracy, and a very detailed prompt engineering guide.


This release arrives not long after Anthropic, a key competitor founded by ex-OpenAI employees, revealed the system prompts for its own chatbot, Claude. We wrote a more detailed analysis of Claude’s prompt when it was released.



A tale of two AIs

Peek under the hood, and you'll find two very different engines running these AI behemoths, and each prompt can tell a lot about how both companies think and what they expect from their products. In general terms, OpenAI conceptualized ChatGPT as a powerful computational tool whereas Anthropic envisioned Claude more as a friendly, human-like assistant.


Here’s how Anthropic and OpenAI stack up:


General approach

OpenAI's prompts read like a technical manual for a high-performance machine. It's all about efficiency, accuracy, and getting the job done with minimal fuss. Their AI is designed to be a tool, focused on delivering results rather than engaging in chitchat.


Anthropic, on the other hand, has crafted Claude to be more like a knowledgeable friend. Their meta prompt paints a picture of an AI with a distinct personality, complete with quirks, interests, and even a sense of humor. It's clear Anthropic is aiming for an AI that can engage in meaningful conversations, not just spit out information.


Why this is important: If you want to complete a task and get on with the next thing in your routine, OpenAI seems to have the better prompt for it.


If you want to interact with your model or engage in a sort of co-work environment with mutually improving results, Claude may be your better choice here.


Structure and formatting instructions

OpenAI's approach is highly structured and methodical. Its meta prompt is organized into clear sections with specific guidelines for each aspect of the AI's functionality. It's like a well-organized filing system, where everything has its place.


Anthropic takes a more narrative approach. Its meta prompt reads almost like a character description for a novel, with detailed instructions on how Claude should behave in various situations. It's less about rigid structure and more about creating a coherent personality.


In terms of formatting, Claude uses XML tags whereas OpenAI seems to have opted for a structured markdown format to separate different sections.



Why this is important: Knowing how to break up and structure a prompt is key to get the best results out of the models. For example, if you ask a model to reproduce a specific method to solve a problem and provide an example, properly tagging it will help the model understand that you just want to reproduce the steps and will not consider the example as part of the problem you are trying to solve.


Assistant's self-awareness and limitations

OpenAI keeps things strictly business when it comes to self-awareness. Its AI is instructed to be clear about its capabilities and limitations, but without entering into philosophical questions about its nature or existence. Again, ChatGPT is designed to be an efficient tool that knows exactly what it can and can't do, no more, no less.


Anthropic, however, has given Claude a more nuanced sense of self. The meta prompt includes instructions on how to handle questions about its own nature, its interactions, and even how to discuss its limitations.


For example, Anthropic even gives emotions to Claude 3.5 Sonnet, prompting things like, “It is happy to help with writing, analysis, question answering, math, coding and all sorts of tasks.”


OpenAI goes for a boring “given a task description or existing prompt, produce a detailed system prompt to guide a language model in completing the task effectively.”


Why this is important: This is just interesting to have a good expectation on what your interactions will be like with each model. Overall, Claude seems to be more friendly whereas ChatGPT in its text version feels more robotic.


Instructions on reasoning and problem-solving

OpenAI's meta prompt emphasizes a logical, step-by-step approach to problem-solving. It instructs the AI to break down complex problems into manageable parts and to show its work clearly. This method is reminiscent of a meticulous scientist, carefully documenting each step of an experiment and is more noticeable when you can see o1 at work, using an embedded Chain of Thought reasoning to solve a problem.


“Encourage reasoning steps before any conclusions are reached,” OpenAI’s prompt reads, “ATTENTION! If the user provides examples where the reasoning happens afterward, REVERSE the order! NEVER START EXAMPLES WITH CONCLUSIONS!”


And yes, caps are part of the prompt.



Anthropic encourages Claude to think out loud, so to speak. The meta prompt instructs the AI to explain its thought process, share insights along the way, and even express uncertainty when appropriate. It's more like a collaborative problem-solving session with a thoughtful colleague.


“When presented with a math problem, logic problem, or other problem benefiting from systematic thinking, Claude thinks through it step by step before giving its final answer,” Calude’s prompt reads.


Why this is important: OpenAI seems to have the better prompt for solving complex tasks that the user does not know how to approach. The Chain of Thought reasoning is more systematic than a simple thought process hidden by an XML tag. However, knowing when a model is not 100% certain is key to spot hallucinations.


Style and tone guidelines

OpenAI's style guide emphasizes clarity and conciseness. The meta prompt instructs the AI to use straightforward language, avoid fluff, and get to the point quickly. It's all about efficient communication, like a no-nonsense news report.


Anthropic aims for a more conversational tone. Claude is instructed to engage in a natural, flowing dialogue and even use humor when appropriate. This is why the model’s behavior and tone seems more approachable to the point that some users find it annoying when it starts apologizing too much.


Why this is important: This explains why Claude’s tone is better for creative writing. Also, OpenAI’s new canvas mode may help tackle this problem, but overall Claude tends to do better because it’s prompted to be more natural and familiar than ChatGPT.


Avoidance of self-reference

Both OpenAI and Anthropic agree on minimizing unnecessary self-reference. Their meta prompts instruct the AIs to avoid drawing attention to themselves, keeping the focus on the task or conversation at hand.


OpenAI's approach is more reactive. Their AI is instructed to wait for clear user prompts before taking action, like a well-trained assistant waiting for instructions.


Anthropic gives Claude more leeway to be proactive. Their meta prompt allows for offering additional information or suggesting related topics, more like an eager research assistant always ready with extra insights.



Final Thoughts

While OpenAI and Anthropic share the goal of improving AI-human interaction, their approaches highlight different priorities. OpenAI’s focus on task efficiency and precise prompt engineering contrasts with Anthropic’s commitment to human-ish AI behavior and transparency. OpenAI’s meta-prompt is all about generating effective, structured outputs, while Anthropic’s prompts are about ensuring that the AI behaves responsibly, encouraging user interaction.


In terms of getting the job done, both chatbots will work. However, knowing how each company thinks and expects from their models is a good way to know what to expect from their models and how to properly interact with their AIs to be more effective.