HOW PERPLEXITY BUILT AN AI GOOGLE

Summary from the TLDR Dev newsletter

Perplexity built an “answer engine” by combining real-time web search with LLMs through a Retrieval-Augmented Generation (RAG) pipeline that searches the web, extracts relevant snippets, and generates cited answers. Its architecture uses Vespa AI to index 200+ billion URLs, intelligently routes queries between in-house “Sonar” models and third-party LLMs (GPT/Claude) based on complexity, and runs on a custom-built ROSE inference engine optimized for speed and cost.