Day 78 of 133

RAG foundations: pipeline + chunking + DSA Intervals

When RAG vs FT; latency in retrieve→rerank→generate; chunk strategies.

DSA · NeetCode Intervals

Meeting Rooms IIDSA · Intervals
Interview questions to prep
1. Compare heap-based (O(n log n)) vs sweep-line (start/end events) approaches.
2. What if you need to assign each meeting to a specific room, not just count?
Minimum Interval TO Include Each QueryDSA · Intervals
Interview questions to prep
1. Do you sort by start or by end? Defend the choice based on the invariant you need.
2. Walk through merge / overlap detection: what's your condition for 'overlapping'?
3. How does complexity break down: O(n log n) sort + O(n) sweep — can you do better in any case?

Why RAG: closed-book vs open-book LLMsGenerative AILangChain
Interview questions to prep
1. When would you reach for RAG over fine-tuning, and vice versa?
2. What problems does RAG solve that long context windows don't?
Standard RAG pipeline: index → retrieve → rerank → generateGenerative AIPinecone
Interview questions to prep
1. Walk through the four stages of a standard RAG pipeline.
2. Where does latency hide in a RAG pipeline?
3. A RAG answer is wrong and you suspect retrieval. How do you prove whether the issue is corpus coverage, extraction, retrieval, reranking, or generation?
4. How would you log and compare top-k results before and after a retrieval change?
5. What offline benchmark and online A/B signals would tell you the retrieval fix is safe?
Chunking strategies: fixed, semantic, hierarchicalGenerative AIPinecone
Interview questions to prep
1. Compare fixed-size, semantic, and hierarchical chunking — when does each fit?
2. How does chunk size affect retrieval quality vs answer quality?

References & further reading