Agentic AI & Generative AI — Interview Revision Notes

Preparing for AI Engineer, Generative AI or Agentic AI interviews? This practical 38-page PDF brings important concepts, implementation patterns, code examples and common mistakes together in one revision guide.

Instead of jumping between multiple resources, use these notes to revise key topics and refresh your understanding before technical interviews or projects.

What’s covered?

• Python Environment Setup: uv, virtual environments, dependencies and API keys
• LangChain v1: Agents, tools, model integration, streaming, batch processing, structured output and middleware
• LangGraph: StateGraph, nodes, edges, ReAct agents, memory, streaming and human-in-the-loop workflows
• MCP: Model Context Protocol, MCP servers, clients and tool integration
• RAG: Document loading, chunking, embeddings, vector databases, retrieval and generation
• Vectorless RAG: PageIndex, tree-based indexing and reasoning-based retrieval
• Deep Agents: Planning, sub-agents, system prompts and file-system-based memory
• Guardrails: Safety checks, PII handling and approval workflows
• Evaluation: Test datasets, LLM-as-a-judge and RAG evaluation metrics
• LLM Gateway: LiteLLM, routing, fallbacks, caching and cost tracking

Who is this for?

• Students preparing for AI/ML and Generative AI interviews
• Python developers learning to build LLM applications
• Beginners exploring AI agents and RAG-based applications
• Developers who want a compact technical revision resource

What will you receive?

• One downloadable 38-page PDF
• Concept explanations and technical summaries
• Code snippets and implementation patterns
• Common mistakes and troubleshooting notes
• A structured learning path across the covered topics

Important note

These are revision notes, not a complete video course or a guarantee of interview selection. The examples follow the course material and may require adjustments for current library versions, model names and APIs. Check official documentation before using code in production.

Get the notes, revise smarter, and strengthen your understanding of modern AI application development.