AI language models are incredibly versatile, capable of generating far more than just plain text. With the right prompting techniques, you can guide them to produce structured outputs like code snippets, tables, JSON objects, lists, and more. This article explores how to structure your prompts for such complex data formats.

1. Be Explicit About the Desired Format

The most crucial step is to clearly state the format you expect.

• "Generate a Python function that..."
• "Provide the information as a markdown table with columns: Feature, Benefit, Example."
• "Output the result as a JSON object with keys 'id', 'name', and 'status'."
• "List the steps as a numbered list."

2. Use Few-Shot Prompting with Examples

For more complex structures, providing examples (few-shot prompting) is highly effective. Show the AI the exact format you want.

Example for JSON output:
Input: Product A, Category X, Price $10
Output: { "name": "Product A", "category": "Category X", "price": 10 }

Input: Product B, Category Y, Price $25
Output:

3. Specify Delimiters or Enclosures

For code or specific data blocks, tell the AI to use delimiters. This makes it easier to parse the output programmatically.

• "Wrap the Python code in triple backticks (```python ... ```)."
• "Enclose the JSON output within `[JSON_START]` and `[JSON_END]` tags."

4. Break Down Complex Data Requests

If you need a very complex structure, consider asking for parts of it in separate prompts or instructing the AI to build it step-by-step. For example, for a complex JSON, you might first ask for the schema, then for data populating that schema.

5. For Code Generation:

• Specify the programming language.
• Describe the function's purpose, inputs, and expected outputs.
• Mention any specific libraries or frameworks to use or avoid.
• Ask for comments or explanations if needed.

6. For Tables:

• Clearly define column headers.
• Specify the type of content for each column.
• Indicate if a specific format like Markdown is preferred.

By clearly defining your desired output format and providing examples when necessary, you can leverage AI to generate a wide variety of structured data, significantly expanding its utility beyond simple text generation.