Day 1B: Agent Architectures — How Modern AI Agents Are Built (Google x Kaggle)

Description

Day 1B dives deep into Agent Architecture — the structural design that allows agents to plan, interact, reason, call tools, access memory, and perform coordinated tasks. This step is essential before working on multi-agent systems and project builds. ⭐ What You’ll Learn Single-agent architectures Planner vs Executor roles How tools are selected Agent workflow (input → observation → reasoning → decision → action) How Google Gemini implements tool use How this structure scales into multi-agent systems Resources 👉 Kaggle Day 1B Notebook 👉 Google Gemini Architecture Overview: https://ai.google.dev/gemini 👉 “Introduction to Agents” whitepaper: https://www.kaggle.com/whitepaper-introduction-to-agents Additional documents: 👉 check out the documentation related to LLM agents in ADK: https://google.github.io/adk-docs/agents/llm-agents/ 👉 ADK documentation for more information on guiding agents with clear and specific instructions: https://google.github.io/adk-docs/agents/llm-agents/ 👉 check out the documentations related to: 👉 Sequential agents in ADK: https://google.github.io/adk-docs/agents/workflow-agents/sequential-agents/ 👉 Parallel agents in ADK: https://google.github.io/adk-docs/agents/workflow-agents/parallel-agents/ 👉 Loop agents in ADK: https://google.github.io/adk-docs/agents/workflow-agents/loop-agents/ 👉 Custom agents in ADK: https://google.github.io/adk-docs/agents/custom-agents/ 💬 Drop your questions in the comments and I’ll help you out! 🔔 Subscribe for Day 2 – where we’ll dive into Custom Tools, MCP, and Long-Running Agent Operations! #multiagentsystems #googleinternship #coursecontent #agentai #AgentArchitecture #AIAgents #Gemini #googleai