Search the practice set

126 questions, 454 terms and 400 topics in 20 areas.

7 results for “Chunking & Retrieval”

Terminology · 3

Retrieval-Augmented Generation

Retrieving relevant documents at query time and putting them in the model's context, so answers are grounded in your data rather than in training data.

AI-Era Architecture term

Context Window

The maximum number of tokens a model can attend to in one request, holding the system prompt, history, retrieved context, tools and the answer.

AI-Era Architecture term

Embedding

A dense numeric vector representing a piece of content, positioned so that semantically similar content sits nearby.

AI-Era Architecture

Questions · 1

quiz

A client wants an assistant that answers questions from 50,000 internal documents which change weekly. RAG or fine-tuning? What actually determines the quality?

What the interviewer is testing Whether you understand what each technique actually does, and whether you know that RAG quality is a retrieval problem. Why RAG

AI-Era Architecture

Topics · 3

topic

Chunking & Retrieval

Structure-aware splitting, hybrid search and why chunking dominates quality.

AI-Era Architecture — no content yet topic

RAG Architecture

Retrieval, grounding, citation and the permissions RAG can enforce.

AI-Era Architecture — no content yet topic

Storage Costs

Tiering, lifecycle policies, retrieval charges and minimum durations.

Cost Architecture & FinOps — no content yet