GitHub Copilot Meta Prompts

What are Meta Prompts

What are we talking about?

• Developers gladly use GitHub Copilot while new developing applications
• But they encounter challenges for more complex use cases - reverse engineering, or optimizing code etc

Yeah, I've heard about it, how are we solving it?

The root cause analysis revealed Developers

1. Weren't sure how to provide "adequate" problem context
2. Weren't comfortable with the "black box" nature of Copilot and demanded clarity on "the how"
3. Required the suggestions in particular format - like a JSON payload, and Copilot responses wasn't matching

This is where Meta Prompts come in

Sounds interesting tell me more

Meta Prompts

• are a recent Phenomenon (Check References below)
• emphasize Structure and Syntax of the prompt
• use Type Theory for clearer classification of the prompt elements
• leverage LLMs ability to parse and understand Structured data (XML, JSON etc) better
• are more effective when emphasis is on the "how" rather than the "what"?

Makes Sense, is there a prescribed format

• Could be XML or JSON
• Could follow one of the Prompt crafting frameworks like CO-STAR or TIDD-EC

Got it, How does this look in real life?!

Let's do a quick demo!

References

• https://meta-prompting.github.io/
• https://github.com/meta-prompting/meta-prompting
• https://meta-prompting.github.io/MP.pdf