Super-prompting: Bootstrapping AI coding agents

Jun 6

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.

https://github.com/derrybirkett/ai-news-aggregator-docs

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