This is How to Design AI Agents System (Multi-Agent , Agentic RAG , HIL , MCP) | Part 1

Description

Stop building simple chatbots! 🚀 This is your practical, comprehensive guide to designing scalable, resilient, and intelligent AI agent systems. We break down the High-Level Design (HLD) of a Note-Taking AI Agent using a powerful multi-agent, hierarchical framework , diving deep into Agentic RAG, ReAct agents, and Human-in-the-Loop (HIL) workflows. 🧠 What You'll Master In this masterclass, we explore the world of AI agents, architecting a complex system using a Note-Taking AI Agent case study. You'll learn: ReAct-Style Agents: Understand the core "Reason and Act" loop for complex decision-making. Multi-Agent Architecture: See how to design a hierarchical, loosely coupled system with specialized agents (Security, Ingestion, Retrieval, Maintenance, etc.). Agentic RAG: Implement advanced retrieval and self-correction by allowing the agent to Reason about the results and potentially Re-Query. Core Design Pillars: Building Loosely Coupled, Highly Extensible, Modular, and Resilient LLM systems. Architecture: We use a three-tier design (Perception, Planning, Execution) and model workflows as an extensible Graph/DAG. Shared Memory: How the Persistent State object acts as the single source of truth for all agents. Related Question What are the four core requirements used to define this intelligent note-taking AI agent? How does the ReAct loop (Reason and Act) fundamentally improve an agent's performance compared to a simple prompt? In the multi-agent design, which single agent is responsible for dynamic task orchestration and creating the DAG (Directed Acyclic Graph) plan? Explain the purpose of the Security Agent in this architecture. What is the main role of the "Reduce" node in the TaskPlannerAgent's workflow? How do the agents maintain context and state across multiple steps in the workflow? What critical step makes the Retrieval Agent's process "Agentic RAG" rather than standard RAG? Which two specific tools does the Ingestion Agent use to finally save the processed note data? Why is the Human-in-the-Loop (HIL) check mandatory in the Maintenance Agent's workflow? What are three of the core design pillars (e.g., Modular, Resilient, etc.) that ensure this system is scalable? #ai #aitools #systemdesigninterview #softwaredesign #algorithms #programming #developer #backenddevelopment #chatgpt #claude #mcp #coding #faang #interviewtips #interviewquestions #interviewprep #gemini #tools #agenticai #agenticrag #algorithms #databaseconcepts #vectordatabases #langgraph #manim #react #hld