AI-Native Development

Overview

AI-Native Development focuses on building applications where AI is a first-class citizen, not an afterthought. This skill provides comprehensive patterns for integrating LLMs, implementing RAG (Retrieval-Augmented Generation), using vector databases, building agentic workflows, and optimizing AI application performance and cost.

Real-World Use Cases:

• AI-Powered Documentation Search: Semantic search over technical docs with hybrid retrieval
• Code Review Assistant: Automated code analysis with security, performance, and style checks
• Customer Support Chatbot: RAG-based Q&A with citation of knowledge base articles
• Content Analysis Pipeline: Multi-agent workflows for analyzing articles, tutorials, and documentation
• Research Assistant: Multi-query RAG with source tracking and synthesis