Top Agentic AI Interview Questions & Answers (2026) with clear, practical answers for 2026 interviews.
What is Agentic AI?
LLMs that take actions through tools in a loop (reason → act → observe), not just answer questions. They plan, call tools, use memory and can run multi-step workflows.
What is an agent loop?
The model decides a tool call, the system executes it, feeds the result back, and repeats until a stop condition — bounded by step/recursion limits.
What is LangGraph and why use it?
A framework to model agents as state machines (nodes + edges over shared state) with cycles, conditional branching, persistence and human-in-the-loop — more reliable than opaque agents.
What is MCP (Model Context Protocol)?
A standard protocol for exposing tools/resources to agents, so an agent can act on Jira, GitHub, databases etc. through a consistent, scoped, authenticated interface.
How do you add memory to an agent?
Short-term (message history), windowed, summary memory, or vector-backed long-term memory retrieved by relevance — chosen on context-window cost vs recall.
How do you keep agents safe in production?
Human-in-the-loop approval for risky actions, scoped tool permissions, input/output guardrails, prompt-injection defences, step limits and audit logging.
How do you evaluate an agentic system?
Task success rate, step efficiency, tool-call correctness and failure analysis on a fixed eval set, with human review for high-risk flows.
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