Prompt Engineering
Prompt engineering is the practice of crafting effective instructions and context for AI models to produce desired outputs. It combines clear communication with an understanding of how language models process information, enabling developers to get better and more consistent results from AI assistants.
Origin
Emerged as a discipline alongside the rise of large language models (LLMs) in 2022-2023, becoming increasingly important as AI assistants became capable of complex tasks.
Example
Prompt engineering is the art and science of communicating effectively with AI. In vibe coding, your prompts are your primary tool — the better you communicate intent, the better results you get.
Key Principles
Be Specific, Not Verbose
Good prompts are precise without being overwhelming. Include relevant constraints and context, but don't over-specify implementation details unless necessary.
Provide Context
AI models work best when they understand the bigger picture. Share relevant context about your project, tech stack, and coding standards.
Iterate and Refine
Treat prompting as a conversation. Start with a clear request, then refine based on what the AI produces. Each exchange helps the AI understand your intent better.
Common Patterns
- Role prompting — "You are an expert React developer..."
- Few-shot examples — Showing examples of desired output
- Chain of thought — Asking AI to explain its reasoning
- Constraints — "Do not use external libraries" or "Keep it under 50 lines"
Why It Matters for Vibe Coding
In traditional development, your skill is measured by how well you write code. In vibe coding, it's increasingly about how well you communicate what you want. Prompt engineering is the bridge between your vision and working software.
Further Reading
Cursor
Emergent — An agentic vibe-coding platform that builds production-ready apps