Advanced Retrieval-Augmented Generation (RAG)

Chunking strategies, multi-query routing, HyDE, cross-encoders, and RAGAS evaluation.

3 weeks · wk 12–14Core / deep pace5 topics15 Interview Questions

Why this pace:Naive RAG (chunk -> embed -> retrieve -> prompt) fails in production due to context fragmentation, noisy retrieval, and hallucinated syntheses. Production RAG requires multi-stage retrieval pipelines.

SEC FOCUS

Prevent prompt injection from untrusted retrieved documents (Indirect Prompt Injection) by strictly delimiting retrieved context from system instructions.

Topics & Action Items (5)

Chunking Strategies: Semantic, Recursive & Document-Aware

4 hrs

Query Transformation: Multi-Query, Decomposition & HyDE

5 hrs

Cross-Encoder Reranking: Cohere Rerank & BGE-Reranker

4 hrs

Contextual Retrieval & Long-Context Prompt Packing

4 hrs

RAG Evaluation Metrics: RAGAS & TruLens

5 hrs

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Vector Databases, Embeddings & Semantic Search

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LLM Agents & Multi-Agent Swarms