17 articles tagged with RAG
A technical deep-dive into the limitations of ultra-long context windows. We analyze attention dispersion, distraction tokens, multi-hop reasoning failure modes, and why hybrid RAG + Contextual Compression outperforms raw prompt dumping.
How Google's $0.75 per million input token pricing disrupted enterprise AI economics in 2026. We examine TPU v6e hardware efficiency, speculative decoding batching, and how startups cut RAG infrastructure bills by 85%.
An advanced retrieval engineering guide to late chunking and contextual embedding architectures. We demonstrate why naive character splitting breaks semantic embeddings and how embedding entire documents before chunking boosts recall by 38%.
2M-10M token context windows vs retrieval accuracy. Why 'Needle in a Haystack' decay, prefill latency penalties, and financial token costs make RAG + prompt caching the smarter 2026 choice.
A complete build of a retrieval-augmented generation endpoint on top of Postgres and pgvector — chunking, indexing, hybrid search, and the reranking step most tutorials skip.
A single embed-and-retrieve step was never going to be the final form of grounding an LLM in real data. Here's how retrieval architectures actually changed as teams ran into its limits.
Optimize RAG queries. Learn how to structure document trees to maximize context cache hits and reduce token consumption.