When would you choose an agent over a chain? — When the task requires dynamic tool selection based on results; when control flow cannot be determined in advance.
What is the "agent paradox"? — Complex tasks benefit most from agents, but are also hardest to evaluate. Always define evaluation before deployment.
How does LangGraph's checkpointing enable HITL? — interrupt_before pauses execution and returns control; PostgresSaver persists state durably; the caller resumes by invoking graph.invoke() with the human decision in state.
Why enforce tool authorization at the MCP server rather than relying on the agent? — The LLM is not a reliable security boundary — it can be manipulated by prompt injection. The MCP server is code; it enforces authorization independent of the model's reasoning.
What are the four HITL trigger categories? — Confidence-based (agent uncertainty), risk-based (action side-effect level), policy-based (business rule mandates review regardless of confidence), anomaly-based (agent detects unexpected state).
What is the M×N problem MCP solves? — Without a standard protocol, M AI applications × N backend systems = M×N integrations. With MCP: M clients + N servers; each addition requires one implementation, not M or N.