LLMs → RAG → Agents

GenAIFundamental

Structured Gen AI prep — LLMs, RAG, agents, and production systems in one track.
No scattered prep. Choose a module below and go deep.

Explore topics

Guide modules in prep order — LLMs, RAG, agents, then production systems.

#	Module	Interview focus
01	LLM Fundamentals Tokens, transformers, embeddings, context	Tokens, transformers, embeddings, context	Open guide
02	LLM Integration APIs, streaming, tool calling, structured output	APIs, streaming, tool calling, structured output	Open guide
03	Prompt Engineering CoT, ReAct, guardrails, evaluation	CoT, ReAct, guardrails, evaluation	Open guide
04	RAG Pipelines Chunking, retrieval, reranking, hybrid search	Chunking, retrieval, reranking, hybrid search	Open guide
05	Vector Embeddings ANN search, vector DBs, similarity	ANN search, vector DBs, similarity	Open guide
06	Semantic Search BM25 + vectors, ranking, optimization	BM25 + vectors, ranking, optimization	Open guide
07	AI Agents & Workflows Planning, tools, multi-step agents	Planning, tools, multi-step agents	Open guide
08	AI-powered UI Systems Copilots, streaming chat, AI UX	Copilots, streaming chat, AI UX	Open guide
09	AI Backend Engineering SSE, queues, caching, observability	SSE, queues, caching, observability	Open guide
10	AI System Design Enterprise RAG, scalable AI architecture	Enterprise RAG, scalable AI architecture	Open guide
11	AI Performance & Security Latency, eval, prompt injection	Latency, eval, prompt injection	Open guide
12	AI Interview Scenarios Debugging, tradeoffs, whiteboard drills	Debugging, tradeoffs, whiteboard drills	Open guide
13	Full-stack AI Mini Project Full-stack support copilot capstone	Full-stack support copilot capstone	Open guide

13 guide topics