State machines, cyclic workflows, and the Model Context Protocol — essential for agent infrastructure interviews.
LangGraph and MCP are the infrastructure layer behind modern AI agents. LangGraph gives you deterministic state machines for agent workflows; MCP standardizes how agents connect to external tools and data sources.
If you're interviewing for agent platform or developer tools roles, these two topics are non-negotiable.
Deep explanations with architecture diagrams for every question below.
LangGraph has emerged as the go-to framework for stateful agent workflows, replacing brittle LangChain chains in production. Interviewers want graph thinking — nodes, edges, conditional routing, and checkpointing — not just API familiarity. Essential for any LangChain shop hiring GenAI engineers.
Read full explanationThe Model Context Protocol is Anthropic's open standard reshaping how LLMs connect to tools and data. If you're interviewing for Claude ecosystem roles or AI platform engineering, expect MCP questions. Understand host vs server architecture and how MCP differs from ad-hoc function calling.
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