If you've been experimenting with AI tools like GPT-4, Claude, or Cursor to generate code, you've probably realized this: the prompt is the blueprint. But vague prompts yield vague results. That's why I've been developing Super Prompts — structured, markdown-based project guides that act like mini product specs for coding agents.
What's a Super Prompt?
A Super Prompt isn't just a single instruction — it's a whole operating manual. It includes:
- Project description and app goals.
- Technical requirements (accessibility, test coverage, performance targets).
- File structure and naming conventions.
- Dev task breakdowns with success criteria and clear start/end states.
- Policies like coding standards and component casing styles.
- Development workflow from environment setup to deployment.
Why it matters
Instead of treating the AI as a glorified autocomplete, Super Prompts give it a strategic briefing. You're not coding line by line — you're setting the rules of the game and letting the AI fill in the details. This approach saves time, increases build accuracy, and makes AI a true collaborator in your software pipeline.
Watch the walkthrough
In the video, I break down a real Super Prompt for an AI News Aggregator built with Next.js and React. You'll see exactly how I structure everything — from task flow to naming conventions — to get predictable, high-quality results from an AI agent.
Want to try it yourself?
Download the full markdown Super Prompt and start automating your next project: github.com/derrybirkett/ai-news-aggregator-docs.