ai-native-development

What problem does it solve?

Provides patterns for integrating LLMs, RAG pipelines, vector databases, agentic workflows, and cost-aware AI development.

Core Features & Use Cases

• RAG & Embeddings: Implement retrieval-augmented generation with embeddings.
• Vector Databases: Use Pinecone, Weaviate, or Chroma for scalable storage.
• Agents & Tool Use: Build agentic workflows where LLMs orchestrate tools.
• Cost & Observability: Track costs and observability for AI systems.
• Use Case: Build a chat assistant that references a knowledge base with citations.

Quick Start

Provide a simple prompt to launch a RAG-based chat with citations to get started.