Prompts for Claude and GPT are similar in many ways, but there are a few slight changes you can make that will immediately help your old GPT prompt achieve better results with Claude. Here are six prompting tips to help you convert a GPT prompt to a Claude prompt.

# Adopt the Human/Assistant formatting

Claude is trained to fill in text for the Assistant role as part of an ongoing dialogue between a human user (Human:) and an AI assistant (Assistant:). Prompts sent via the API must contain `\n\nHuman:` and `\n\nAssistant:` as the signals of who's speaking. On [claude.ai](🔗), we automatically add these for you, and in our [developer console](🔗), newlines are added automatically for you to the `Human:` and `Assistant:` text boxes when prompts are run.

Here’s an example of how the formatting looks:


System Prompts
System prompts are a new feature of Claude 2.1. Moving your system prompt over is easy! When using Claude 2.1, simply write your system prompt at the beginning (no new lines needed). Then put user text after `\n\nHuman:`.
For example:

We recommend that you **use system prompts only with Claude 2.1**. If you are using models other than Claude 2.1, then we recommend you place all your instructions within the `Human:` turn. 
You do not need any separation between the 'system prompt' text and the rest of the prompt (i.e., the user input), but you can use the "BEGIN DIALOGUE" separator if you would like to further delineate the two sections, such as in the following example:

For more information, see [how to use system prompts](🔗). You can also refer to the tip ["Keeping Claude in character"](🔗) for additional tips on keeping dialogue agents in character.

# Add XML tags
XML tags look like this:

Claude has been fine-tuned to recognize XML tags within prompts. These tags can be used to demarcate different subsections of a prompt. This allows Claude to compartmentalize a prompt into distinct parts. 
For example, suppose we want to add some text from a document to our prompt, we would wrap the document in <doc> tags:

Claude is also able to recognize other structured formats like JSON and YAML, but sticking to XML will lead to the best performance in most cases.
Naming XML tags
There are no special or reserved names for these tags. They can be anything you want. It’s the format that matters - as long as you have `<>` and `</>` you’re good to go!

# Provide clear and unambiguous instructions
Claude responds well to clear and direct instructions. For example, suppose a prompt contained a line like this:

This line leaves room for Claude to make implicit assumptions. What context? What question? An answer to what? Explicitly answering these questions within the prompt will focus Claude on the task at hand.
Let’s apply this mindset to rewrite this line:

In this rewrite, we expanded on the steps Claude should take to create an answer. We also provided specifics of what the context and question are and where Claude should look to find them.
When creating prompts for Claude, it’s best to adopt the frame that Claude is new to the task and has no prior context other than what is stated in the prompt. Providing detailed and unambiguous explanations in the prompt will help Claude generate better responses.

# Put words in Claude's mouth
When using Anthropic’s API, you are not limited to just the “User” (as in GPT) or “Human” part of the request. Claude’s prompt extends to include the Assistant response as well. With the `\n\nHuman:` and `\n\nAssistant:` formatting, you can provide Claude more instructions after `\n\nAssistant:`. Claude will continue the conversation from the last `\n\nAssistant:` token.
Here’s an example:

By inserting `<rewrite>` after the `\n\nAssistant:` we have forced Claude to only provide the rest of the rewrite in its response. This avoids some of Claude’s chatty tendencies that you may experience when Claude adds a sentence or two prior to providing its answer. It’s important to note that if you adopt this approach in your own prompt, you will want to pass `</rewrite>` as a stop sequence to the API completion method.
This technique can also be used to ensure Claude always begins its answer the same way and allow Claude to acknowledge specific rules that have been stated previously in the prompt.

# Keeping Claude in character
For all Claude models, putting words in Claude’s mouth can help ensure that Claude stays in character in any dialogue based chat application. After `\n\nAssistant:`  we can insert Claude’s persona within brackets as shown:

This technique forces Claude to acknowledge that it is roleplaying as that persona and only output responses that logically follow with something the persona would say.
For specifically Claude 2.1, using system prompts can also help Claude better stay in character.

# Documents before instructions
Most Claude models have a 100K context window (~75K words). Claude 2.1 has double the context window at 200K (~150K words). These long context windows mean that Claude is great at parsing and analyzing long documents and strings of text.
It’s best to provide long documents and text before instructions or user input (this is [particularly important for Claude 2.1](🔗)). Claude pays extra attention to text near the bottom of the prompt so make sure to emphasize important instructions near the end of your prompts.
Claude’s long context allows you to experiment with new processes that aren’t possible when using other language models with shorter context windows. If your application previously required you to split inputs in order to fit within a context window, simplify your steps and combine the inputs into one.

# Add many examples (at least 3)
Claude learns well through examples of how it should respond and in what format. We recommend adding at least three examples to your prompt, but more is better! 
Examples are especially beneficial for tasks that require consistent and reliable structured outputs. Uniform examples will teach Claude to always respond in the same way every time.
We often add examples within example tags and structure them to include the question and the ideal Claude answer:

Be sure to diversify your examples to address all the edge cases of your task. Examples work well for clarifying to Claude how to handle tricky situations like telling a user "I'm unable to answer that question" when Claude lacks the pertinent details to fully answer their question.