Focus on the Product Requirements Prompt (PRP) framework, a structured approach to context engineering for AI-assisted software development. They explain that traditional "vibe coding" and simple prompt engineering are insufficient for complex tasks, proposing that PRPs, which combine adapted Product Requirements Documents with curated codebase intelligence and agentic runbooks, effectively bridge the gap between high-level intent and low-level AI code generation. The sources also provide a comparative analysis of leading AI code assistants (Cursor, Gemini, GitHub Copilot, and Claude), detailing how their features support the PRP framework's components like explicit context referencing, persistent project rules, and agentic execution. Finally, they evaluate the practical application and performance of this methodology, discussing productivity gains, common pitfalls, security implications, and the evolving role of developers towards a human-AI collaborative partnership.