How an LLM‑driven ingestion pipeline silently corrupted its vector store
An autonomous RAG pipeline fed LLM‑generated extractions straight into its vector store, letting hallucinated metadata like wrong fiscal years become searchable. The silent feedback loop let the chatbot cite fabricated data, eroding trust and forcing a costly rebuild. It shows why raw LLM output can’t be trusted as a data source without strict validation.