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(6 of 25)
Explain the ReAct Pattern and When You Would Use It
Understand the ReAct pattern — how Reasoning + Acting enables LLMs to solve multi-step problems with tools, and when to choose it over alternatives.
Read questionExplain the Tradeoffs Between Latency, Cost, and Quality in LLM Selection
Navigate the three-way tradeoff between LLM latency, cost, and quality — and learn how to make the right selection for different use cases.
Read questionWhat Metrics Would You Track for an LLM in Production?
A comprehensive framework for monitoring LLMs in production — from latency and cost to output quality and user satisfaction signals.
Read questionExplain Chain-of-Thought Prompting and When to Use It
Understand chain-of-thought prompting — how it works, when it helps, and when simpler prompts are actually better.
Read questionHow Do You Evaluate Whether a Prompt Is Working Well?
Walk through a systematic approach to measuring prompt quality — from building eval datasets to automated metrics and human evaluation.
Read questionWhen Would You Choose RAG Over Fine-Tuning?
Understand the tradeoffs between RAG and fine-tuning — and learn a decision framework for choosing the right approach for your use case.
Read questionPrep the coding round too
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