RAG Failure Mode Catalog: Why Pipelines Don't Find the Right Doc
Twelve recurring RAG failure modes from production deployments and the fixes for each in 2026.
Agentic AI, LLM engineering, and the models behind modern automation — multi-agent systems, LLM evaluation and comparisons, RAG, fine-tuning, AI infrastructure, security, and production AI engineering.
From the blog
Twelve recurring RAG failure modes from production deployments and the fixes for each in 2026.
Code RAG is different from text RAG. The 2026 patterns for AST-aware chunking, function-level embedding, and snippet ranking.
RAG over sensitive data requires careful tenant isolation, embedding privacy, and access control. The 2026 patterns for safe RAG.
Pure-text RAG misses structured data. The 2026 hybrid patterns that combine vector retrieval with SQL, JSON, and knowledge-graph queries.
Rate limits decide UX and reliability for LLM-backed APIs. The 2026 patterns for shaping bursts, queueing, and fair allocation.
How AI engineers should read large codebases when adding AI features. The 2026 patterns and the agentic-tool tricks that speed it up.
Streaming index updates avoid the 'rebuild and redeploy' tax. The 2026 patterns for real-time vector indexing in production systems.
RRF is a one-line fusion trick that beats most learned re-rankers on real RAG workloads. Why it works and when ML re-rankers are still worth it.
Red-teaming agentic systems requires new techniques. Attack trees, prompt-injection vectors, tool abuse, and the 2026 frameworks that find them.