AI Agents & Tool Use
AI agents — systems that can plan, use tools, and take multi-step actions — represent the cutting edge of applied AI engineering. From simple function-calling chatbots to complex multi-agent pipelines, this space is moving fast and appearing in more and more senior engineering interviews.
Agent interview questions test your ability to design systems that are reliable, observable, and safe. Key topics include: how agents decide which tools to use, how they maintain context over long tasks, how to handle failures and unexpected states, and how multiple agents can collaborate without creating chaotic feedback loops.
Strong candidates understand the trade-offs between agent autonomy and reliability, and can articulate when a simpler non-agentic approach is actually the right call.
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AI Agents & Tool Use Interview Questions
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 questionHow 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 an AI Agent That Can Book Travel End-to-End
Design a multi-step AI agent that books flights, hotels, and transportation — covering tool design, planning loops, error recovery, and user confirmation.
Read questionDesign a Multi-Agent System for Software Development
Design a multi-agent system where specialized agents collaborate on software development — covering orchestration, communication, coordination, and failure modes.
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