Overview
The AI agents interview, answered. Six modules move from agent fundamentals and architecture (reactive and deliberative agents, tool calling, ReAct loops, planner-executor designs, memory and reflection) through the framework ecosystem and what it takes to run agents in production. Use-case design rounds then walk through complete agent systems, advanced topics cover evaluation, security and multi-agent coordination, and a final module collects the follow-up questions interviewers ask next. Every answer is written in the first person with a concrete example, and many carry a diagram.
What you will learn
- Explain agent architectures, from reactive loops to planner-executor designs
- Compare the major agent frameworks and say when to use each
- Design tool calling, memory and reflection for a real agent
- Take an agent to production with evaluation, observability and cost control
- Defend an agent against prompt injection and unsafe actions
- Walk through complete agent use-case designs in an interview
- Handle the follow-up questions that come after a first answer
Included with the kit
- 66 written parts, yours for good
- 11h 41m of reading, measured not estimated
- Written for the intermediate level
- Every future revision included
- UPI, cards and netbanking
Prerequisites
- Working knowledge of LLM APIs and prompting
- Comfort reading Python; no prior agent framework experience needed
Curriculum
6 sections · 66 parts · 11h 41m01Module 1: Agent Fundamentals & Architecture10 parts · 56 min
Understand what agents are, how they reason, use tools, plan, remember, and stay safe.
- Core Understanding of Agents5 min
- Reactive vs Deliberative Agents5 min
- Tool-Calling Agents6 min
- ReAct Pattern and Reasoning Loops5 min
- Planner-Executor Architecture5 min
- Agent Fundamentals & Architecture: Memory in Agents6 min
- Reflection and Self-Correction6 min
- Single-Agent vs Multi-Agent Systems6 min
- Control and Safety Fundamentals7 min
- Design Thinking and Trade-Offs5 min
02Module 2: Agent Frameworks & Ecosystem6 parts · 40 min
Build agents with LangChain, LangGraph, CrewAI, AutoGen, Google ADK, and MCP, and know when to pick each.
- LangChain Agents6 min
- Agent Frameworks & Ecosystem: LangGraph8 min
- CrewAI7 min
- AutoGen6 min
- Google Agent Development Kit (ADK)5 min
- Model Context Protocol (MCP)8 min
03Module 3: Agent Production Systems5 parts · 38 min
Run agents in production with control over latency, cost, reliability, observability, and scale.
- Performance & Latency Optimization8 min
- Cost Optimization & Budget Control10 min
- Reliability & Failure Handling8 min
- Observability & Monitoring6 min
- Scalability & Infrastructure6 min
04Module 4: Agent Use-Case Design3 parts · 46 min
Design complete agent systems for real scenarios from requirements to production.
- Use Case 1 - Autonomous Data Analysis Agent13 min
- Use Case 2 - AI Research & Report Generation Team14 min
- Use Case 3 - Enterprise Knowledge Assistant (Agentic RAG)19 min
05Module 5: Advanced Agent Topics14 parts · 315 min
Go deeper: new frameworks and protocols, memory, HITL, evaluation, security, production engineering, advanced architectures and reasoning, sandboxing, and governance.
- New Frameworks & Protocols61 min
- Context Window Management & Memory Architecture20 min
- Human-in-the-Loop & Control Patterns12 min
- Advanced Agent Topics: Agent Evaluation & Benchmarking12 min
- Advanced Agent Topics: Agent Security & Prompt Injection19 min
- Production Engineering - Versioning, Tracing & Compliance21 min
- Advanced Architecture Patterns22 min
- Fine-Tuning & Model Optimization for Agents20 min
- Advanced Use Cases41 min
- Agentic AI Concepts & Emerging Trends18 min
- Prompt Engineering for Agents16 min
- Advanced Reasoning Patterns25 min
- Agent Sandboxing & Isolation12 min
- Agentic AI Ethics & Governance16 min
06Module 6: Follow-ups28 parts · 206 min
Handle the deeper follow-up questions interviewers ask after your first answer.
- Agent Frameworks7 min
- Memory Systems4 min
- Tool Design & Integration4 min
- Reasoning & Planning4 min
- Multi-Agent Systems4 min
- Agent Security4 min
- Production Engineering4 min
- Agent Evaluation3 min
- Emerging Trends3 min
- Coding Agents3 min
- Voice Agents3 min
- Ethics & Governance3 min
- Agentic Patterns3 min
- ReAct Pattern & Reasoning Loops11 min
- Multi-Agent Coordination6 min
- Follow-ups: Memory in Agents11 min
- Tool-Calling12 min
- Follow-ups: LangGraph12 min
- Agent Production Reliability12 min
- Cost Optimization11 min
- Follow-ups: Agent Security & Prompt Injection11 min
- Agentic RAG11 min
- Human-in-the-Loop11 min
- Context Window Management9 min
- Follow-ups: Agent Evaluation & Benchmarking10 min
- A2A Protocol & Inter-Agent Communication8 min
- Frameworks: LangChain vs LangGraph vs Custom10 min
- Planner-Executor & Task Decomposition12 min
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