Agentic AI Interview Playbook: Answer Like a Senior Engineer

Section Goal: Build crisp mental models of what agents ARE, how they differ from traditional ML systems, and the core components interviewers expect you to know cold.

• What Actually Makes It an Agent?
• The Autonomy Spectrum: Assistive vs Autonomous
• Core Components Every Agent Needs
• When NOT to Build an Agent

Section Goal: Master how to explain tool calling mechanics, schema design, error handling, and the trade-offs between deterministic vs LLM-driven tool selection.

• How Tool Calling Actually Works (Under the Hood)
• Tool Schema Design: What the LLM Needs to Succeed
• Error Handling: When Tools Fail
• Deterministic vs LLM-Driven Tool Selection
• Security & Sandboxing: The "Drop All Tables" Problem

Section Goal: Articulate strategies for short-term vs long-term memory, context window optimization, and when to use retrieval vs summarization vs stateful storage.

• Short-Term vs Long-Term Memory (And Why You Need Both)
• Context Window Economics: When to Summarize vs Retrieve
• Stateful vs Stateless Agents
• The Staleness Problem: When Memory Becomes a Liability

Section Goal: Explain how RAG fits into agent architectures, retrieval-action loops, chunking/indexing trade-offs, and when RAG becomes a bottleneck vs an enabler.

• RAG as a Tool vs RAG as a Foundation
• Chunking & Indexing for Agentic Retrieval
• Multi-Hop Retrieval: When One Query Isn't Enough
• When RAG Becomes the Bottleneck

Section Goal: Break down planning strategies (ReAct, Chain-of-Thought, Tree-of-Thought), explain when each fits, and articulate failure modes like infinite loops or hallucinated plans.

• ReAct Explained: Thought → Action → Observation
• Chain-of-Thought vs ReAct: When to Use Each
• Tree-of-Thought & Planning Ahead
• Failure Modes: Infinite Loops, Hallucinated Plans, and Dead Ends
• When to Hard-Code the Plan

Section Goal: Demonstrate how you'd instrument, debug, and evaluate agents. Cover logging, tracing, human-in-the-loop, and the "how do you know it's working?" question.

• What to Log in an Agent (And Why)
• Tracing Multi-Step Agent Executions
• Evaluating Agents: Beyond Accuracy
• Human-in-the-Loop: When and How
• Cost Monitoring & Budget Guardrails
• Deployment Patterns: Sync vs Async Agents