RAG Architecture Review with Abhishek Mane

Your retrieval is returning garbage. Your LLM is hallucinating. Your chunking strategy feels like guesswork. I've been there.

In this session, I'll audit your RAG pipeline end-to-end — ingestion, chunking, embeddings, retrieval, reranking, and prompt assembly. We'll identify exactly where quality breaks down and I'll give you a concrete fix list you can implement this week.

What we'll cover:

1. Chunking strategy review (size, overlap, semantic boundaries)
2. Embedding model selection and fine-tuning signals
3. Retrieval tuning: dense vs. sparse vs. hybrid
4. Reranking and context window optimization
5. Hallucination detection and source attribution
6. Production checklist: caching, monitoring, cost controls

Best for: Engineers with a working prototype that's failing in production, or teams about to build their first RAG system and want to avoid the common traps.

Bring: your current architecture diagram or code repo (optional but helpful).