3h ago · 19 min read · Three months into a contract with a mid-sized insurance company, I was sitting across from their CTO watching their "AI knowledge base" answer questions about their own products. The system retrieved the right documents 90% of the time. But on anythi...
Join discussion
3h ago · 19 min read · Three months into a contract with a mid-sized insurance company, I was sitting across from their CTO watching their "AI knowledge base" answer questions about their own products. The system retrieved the right documents 90% of the time. But on anythi...
Join discussion1d ago · 19 min read · Three months into a contract with a mid-sized insurance company, I was sitting across from their CTO watching their "AI knowledge base" answer questions about their own products. The system retrieved the right documents 90% of the time. But on anythi...
Join discussionDec 9, 2025 · 2 min read · AI features break when models hallucinate. SaaS founders need to understand why it happens and how to reduce it before shipping AI products. A lot of SaaS founders assume “hallucination” is an ML researcher’s word.It isn’t.It’s a product problem — an...
Join discussion
Sep 11, 2025 · 4 min read · The generative AI boom has marked the beginning of a new wave of smart applications, but with it comes an old curse: hallucinations and unreliable answers when large language models (LLMs) are functioning without anchoring. Retrieval Augmented Genera...
Join discussion
Apr 17, 2025 · 5 min read · What is RAG? Retrieval-Augmented Generation. It is a technique that increases the accuracy and reliability of LLM models by feeding relevant and specific information or data sources to the model. With this system, users can build conversations with d...
Join discussion
