How to Use Modular Prompts Across Different AI Platforms
TL;DR:
- Paste each module separately in ChatGPT for clearer processing
- Use JSON formatting to structure modules in Claude AI
- Pass modules as variables in Make.com and merge them at generation
- Each platform handles modular prompts differently, so match your approach to the tool
Most people treat all AI platforms the same way when it comes to modular prompting. That's a mistake. Each platform processes information differently, and your approach needs to match.
Understanding Platform Requirements
Different AI platforms have their own ways of handling modular prompts. Getting this right means the difference between confused responses and sharp, targeted output.
ChatGPT works best when you feed it modules one at a time. Claude prefers everything structured upfront. Make.com lets you build with variables and merge them later.
Setting Up Modules for ChatGPT
With ChatGPT, treat each module as a separate conversation block. Paste your first module, let it process, then add the next one.
This approach helps ChatGPT understand that each section serves a different purpose. You might have one module for context, another for specific instructions, and a third for output formatting.
Keep each module focused on one job. If a module tries to do too much, ChatGPT can get confused about which part to prioritise.
Structuring Prompts for Claude AI
Claude handles modular prompts through JSON formatting. Wrap each module in proper JSON structure so Claude can separate and process each section clearly.
Your JSON should look clean and follow standard syntax. Use curly braces for containers and quotes around identifiers. Poor formatting leads to processing errors.
{
"context": "Your context module here",
"instructions": "Your instruction module here",
"format": "Your formatting requirements here"
}
Claude reads this structure and treats each section according to its label. This gives you more control over how the AI weighs different parts of your prompt.
Working with Make.com Variables
Make.com handles modular prompts through variables. Set up each module as its own variable, then merge them at the generation step.
This method gives you flexibility. You can test different combinations of modules without rebuilding your entire prompt structure each time.
The merging happens right before the AI generates its response. This means you can adjust which modules to include based on earlier steps in your automation.
Test different merging orders. Sometimes the sequence of your modules affects the quality of the final output. Front-load your most important context, then add instructions and formatting requirements.
Common Mistakes to Avoid
Don't use the same approach across all platforms. What works in ChatGPT won't necessarily work in Claude or Make.com.
Avoid making modules too long. Each module should handle one specific aspect of your prompt. Long modules defeat the purpose of modular design.
Watch out for context bleeding between modules. This happens when one module's instructions interfere with another module's purpose.
Testing Your Modular Setup
Run the same prompt across different platforms using their preferred modular approach. Compare the outputs to see which platform handles your specific use case best.
Start with simple modules and build complexity gradually. This helps you spot where things go wrong before your prompts become too complex to debug.
Document what works. Keep notes on which module combinations produce the best results for different types of tasks.
FAQs
Do I need to use JSON for all AI platforms?
No, only Claude requires JSON formatting. ChatGPT works with plain text modules, and Make.com uses variables.
Can I reuse modules across different platforms?
Yes, but you'll need to reformat them according to each platform's requirements. The content can stay the same.
How many modules should I use in one prompt?
Start with 3-4 modules maximum. You can always add more once you've tested the basics.
What happens if my JSON formatting is wrong in Claude?
Claude will return an error or produce confused output. Double-check your syntax before submitting.
Jargon Buster
- Modular Prompts: Breaking your prompt into separate, focused sections that each handle a specific task
- JSON: A structured data format that uses brackets and quotes to organise information
- Variables: In Make.com, these are containers that hold your module content until you're ready to merge them
- Context Bleeding: When instructions from one module interfere with another module's purpose
Wrap-up
Each AI platform handles modular prompts differently, and your success depends on matching your approach to the platform. ChatGPT needs separate inputs, Claude wants JSON structure, and Make.com works with variables.
The key is testing your setup with simple modules first, then building complexity once you understand how each platform processes your input. Keep your modules focused, avoid trying to make one module do too much, and document what works for future reference.
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