AI Interview Question Bank
Curated questions on system design, prompt engineering, RAG, LLM evaluation, and AI agents — with walkthroughs, follow-ups, and the kind of detail that actually helps you prep.
Browse by Category
AI Agents & Tool Use
Autonomous AI agents, function calling, planning architectures, and multi-agent systems.
AI System Design
End-to-end design of AI-powered systems — from architecture to deployment.
LLM Evaluation & Ops
Testing, monitoring, and operating LLMs reliably in production environments.
Prompt Engineering
Designing, evaluating, and optimizing prompts for real-world LLM applications.
RAG & Retrieval
Retrieval-Augmented Generation architectures — combining search with LLMs for grounded, accurate AI.
All Questions(10 of 25)
How Would You Implement Memory for a Long-Running AI Agent?
Design a memory system for a long-running AI agent — covering in-context working memory, episodic recall, semantic knowledge, and retrieval strategies.
Read questionHow Do You Decide What Tools to Give an AI Agent?
A framework for deciding which tools to give an AI agent — covering granularity, safety boundaries, observability, and the principle of minimal tool sets.
Read questionDesign a Conversational AI Customer Support System
Design an AI-powered customer support system that handles common queries automatically while escalating complex issues to human agents.
Read questionDesign a Document Q&A System for a Large Corpus
Design an AI system that answers natural language questions over a large collection of documents, with accurate citations and low hallucination rates.
Read questionHow Do You Build an Eval Suite for an LLM-Powered Feature?
Walk through building a systematic evaluation suite for an LLM feature — from test case design to automated metrics and regression tracking.
Read questionWhat Strategies Do You Use to Reduce Hallucinations?
Walk through a layered approach to reducing LLM hallucinations — from prompt-level techniques to retrieval grounding and output validation.
Read questionHow Would You Design a Prompt for Structured Data Extraction?
Design a prompt that reliably extracts structured data (JSON, tables) from unstructured text — handling missing fields, ambiguity, and format errors.
Read questionHow Do You Handle Chunking Strategies for Different Document Types?
Compare chunking strategies for different document types — PDFs, code, HTML, and tables — and learn when each approach works best.
Read questionDesign a RAG Pipeline from Scratch
Walk through designing a production-ready RAG system covering document ingestion, chunking strategies, embedding models, vector search, and LLM generation.
Read questionHow Would You Evaluate Retrieval Quality in a RAG System?
Walk through metrics and methods for evaluating retrieval quality in a RAG pipeline — from offline metrics to end-to-end answer quality.
Read questionPrep the coding round too
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