Show HN: I mapped System Design concepts to AI Prompts to stop bad code (github.com)

A new repository has been launched that maps System Design concepts to AI prompting methods, aimed at enhancing the quality of AI-generated code. This initiative provides a structured learning path from the fundamentals of system design to advanced topics, enabling developers to reason about system architecture and understand crucial trade-offs. The resource encompasses 71 chapters across various levels, covering essential elements like latency, availability, and microservices, along with practical insights into designing systems relevant for real-world applications and interviews. This repository is significant for the AI/ML community as it systematically integrates principles of system design with AI-assisted development techniques, termed "vibecoding." By linking concepts directly to AI prompts, users can improve the precision of their AI interactions, thus ensuring that generated designs are not only functional but also architecturally sound. The emphasis on practical application and interview preparation further supports users in leveraging AI tools effectively, ultimately leading to better architectural decisions and a deeper understanding of system design.