RAG System Failures (and How to Fix Them with Multimodal AI APIs)

RAG System Failures (and How to Fix Them with Multimodal AI APIs) A developer's honest post-mortem on building a RAG system just hit HackerNews with 84 comments. Here are the key lessons — plus how to supercharge your RAG pipeline with multimodal AI via NexaAPI. The Post That Got Everyone Talking A developer published an honest account of building a RAG (Retrieval-Augmented Generation) system from scratch — what worked, what failed, and what they wish they'd known. The original article resonated deeply with the HackerNews community. The comments are gold. Developers are sharing their own RAG war stories: chunking strategies that backfired, embedding models that underperformed, retrieval pipelines that returned irrelevant context. But here's what most of the discussion missed: most RAG systems are text-only, and that's a huge limitation . This article covers the key RAG lessons from the HN discussion — and shows you how to build a multimodal RAG system that handles text, images, and aud