Day one-Lesson 2: Build your First Multi Agent Systems

Description

Welcome to Day One – Lesson Two of the 5-Day AI Agents Intensive Course! In this session, we go beyond creating a single agent and build your first real multi-agent system using Google’s Agentic Development Kit (ADK). You’ll learn not only how to build the main agent patterns in ADK, but also when to use each one — based on real workflow needs. 🧠 What You’ll Learn 🔧 Tool Agents (Real LLM Agents Used as Tools) • How they work: Tool Agents run their own LLM, follow their own instructions, and return structured outputs. • When to use: Whenever you need a specialized capability (researcher, summarizer, critic, coder…). • Key idea: The Orchestrator LLM decides when to call them. 🔗 Sequential Agents • How they work: Tasks run in a strict order (A → B → C). • When to use: When your workflow is a fixed pipeline and every step depends on the previous one. • Key feature: Deterministic, predictable execution. ⚡ Parallel Agents • How they work: Multiple agents run at the same time. • When to use: Independent tasks where speed or throughput matters. • Key feature: Concurrent execution. 🔁 Loop Agents • How they work: Repeat a cycle until conditions are met (A ⇆ B ⇆ A). • When to use: Iterative refinement tasks like Writer ↔ Critic workflows. • Key feature: The system improves its output over repeated cycles. 🧠 LLM-Based Orchestration (sub_agents) • How it works: The root LLM orchestrator chooses which agent to call, in which order, based on the user’s request. • When to use: Complex tasks requiring dynamic planning — not fixed pipelines. 🎯 Why Multi-Agent Systems Matter Instead of a ❌ monolithic LLM that tries to do everything, you’ll build a ✔ team of expert agents, each with a clear job: • Research Specialist • Summary Specialist • Coordinator Orchestrator • Shared State to exchange outputs This produces more predictable, modular, and high-quality results. By the end of this lesson, you’ll have a working multi-agent workflow that uses real LLM agents as tools — all orchestrated by a smart root agent. 🧠 What You’ll Need • A Kaggle account (free) • Python basics • A Google API key to access Gemini models • Curiosity to explore multi-agent AI systems! #AI #AIAgents #GoogleADK #Gemini #GoogleAI #Kaggle #PythonAI #AgenticAI #MultiAgent #AITools #GoogleDevelopers #ADKTutorial #GeminiAI #AIIntensive #ArtificialIntelligence #GoogleADKCourse #AIProject #AIAgentCourse #SequentialAgent #ParallelAgent #ToolAgent