Resources to build your business with AI.
We built a RAG-powered recommendation system that matches user preferences against thousands of blog posts. It works great now, but we learned some expensive lessons about rerankers, vector databases, and data structure along the way. Here's what we wish we'd known before we started.
RAG (Retrieval Augmented Generation) combines LLMs with external data sources for enhanced AI responses. While perfect for simple Q&A and chatbots with custom data, our real-world implementation revealed significant limitations with accuracy, debugging, and complex queries that required a more sophisticated multi-layered approach.
Learn how different AI models perform for content creation based on our real-world testing. Discover the unique strengths and weaknesses of Claude, GPT, DeepSeek, and Gemini for producing marketing content.