Gemini ADK: End-to-End Agent Development Course
Course Curriculum
17 modules designed to master the subject.
Module 1: Introduction to Gemini ADK
Learn the purpose of the ADK and how it fits into the Gemini ecosystem compared to other frameworks.
What is Gemini ADK: Purpose and Ecosystem
An in-depth introduction to the Gemini Agent Development Kit (ADK). Learn how it fits into the Google AI ecosystem, its architectural philosophy, and why it's the preferred choice for building enterprise-grade intelligent agents.
What is an Agent: Definition, Autonomy, and Evolution
Master the fundamental definition of an AI agent. Explore the differences between chatbots and agents, degrees of autonomy, and the transition from deterministic to probabilistic behavior in modern AI systems.
Real-World Agent Use Cases: From Enterprise to Individual Productivity
Explore the transformative power of AI agents in the real world. From automating complex enterprise workflows and scientific research to revolutionizing developer productivity and customer support.
Module 2: Core Concepts of Agentic Systems
Understand agent architecture, state management, and autonomy levels in AI systems.
Agent Architecture: Perception, Reasoning, and Action Loops
Deconstruct the internal architecture of modern AI agents. Learn how perception, reasoning engines, and action interfaces work together in a continuous feedback loop to solve complex problems.
Stateless vs. Stateful Agents: Memory and Persistence Strategies
Understand the critical differences between stateless and stateful AI agents. Learn when to use short-term context vs. long-term memory, and explore architectural patterns for persistent agent performance.
Control and Autonomy Levels: Human-in-the-Loop Design
Explore the spectrum of AI autonomy. Learn how to design systems with varying levels of human intervention, from strictly guided assistance to fully autonomous agentic workflows, using Gemini ADK.
Module 3: Gemini Models and Capabilities
Explore the Gemini model family, multimodal capabilities, and selection criteria for agent tasks.
Gemini Model Family: Flash, Pro, and Ultra Models
A comprehensive guide to the Google Gemini model hierarchy. Learn the technical specifications of Nano, Flash, Pro, and Ultra, and master the criteria for selecting the optimal model for your agentic workloads.
Multimodal Capabilities: Seeing, Hearing, and Reasoning with Gemini
Master the native multimodal capabilities of Gemini. Explore how agents can process images, audio, video, and text in a single reasoning step, and learn the architectural benefits of native cross-modal intelligence.
Model Constraints and Limits: Engineering for Stability
Master the boundaries of Gemini models. Learn to navigate context limits, latency challenges, and safety guardrails while building robust, production-grade AI agents.
Module 4: Gemini ADK Architecture
Deep dive into the high-level design, lifecycle, and configuration of agents using the ADK.
Gemini ADK High-Level Design: Interfaces and Core Classes
Delve into the architectural blueprint of the Gemini ADK. Understand the core classes, interfaces, and the philosophy of 'Separation of Concerns' that makes ADK the most robust framework for enterprise AI agents.
Agent Lifecycle: Initialization, Execution, and Termination
Master the end-to-end lifecycle of a Gemini ADK agent. Learn how to manage the transition from initialization through iterative execution loops to safe and verifyable termination.
Agent Configuration: Environment, Metadata, and Overrides
Master the art of configuring Gemini ADK agents for production. Learn to manage secrets, define personas through YAML, and implement dynamic overrides to adapt your agents' behavior in real-time.
Module 5: Prompting and Agent Instructions
Master system instructions, task decomposition, and safety guardrails through structured prompting.
System Instructions: Defining Personas and Operational Boundaries
Master the art of crafting system instructions for Gemini agents. Learn to define robust personas, establish expertise, and set operational boundaries that ensure your agents remain focused and reliable.
Task Instructions: Decomposing Goals into Actionable Steps
Learn the science of task decomposition for AI agents. Master the techniques for breaking down complex user goals into granular, sequential, and parallelizable sub-tasks that Gemini can execute with high precision.
Guardrails and Constraints: The Brakes of Autonomous Systems
Ensure your Gemini agents operate safely and within enterprise boundaries. Learn to implement probabilistic and deterministic guardrails, manage prohibited actions, and design robust safety filters.
Module 6: Tools and Action Execution
Design and integrate deterministic and non-deterministic tools into your agentic workflows.
What Are Tools in ADK: Function Calling and Registration
Unlock the active power of Gemini agents. Learn how to transform standard Python functions into intelligent tools through automated schema registration and native function calling.
Tool Design Principles: Idempotency, Atomicity, and Safety
Master the principles of professional tool design for AI agents. Learn how to build idempotent, atomic, and secure tools that handle errors gracefully and provide reliable feedback to the Gemini reasoning engine.
Tool Invocation Flow: Arguments, Execution, and Feedback
Follow the precise path of a tool call in Gemini ADK. Understand how the model generates arguments, how the runtime executes the logic, and how the resulting observation is fed back into the reasoning loop.
Module 7: Memory and State Management
Implement short-term context, episodic memory, and long-term storage strategies for persistent agents.
Types of AI Memory: Short-Term, Episodic, and Semantic
Deconstruct the memory architecture of intelligent agents. Learn to distinguish between short-term context, episodic event logs, and long-term semantic knowledge to build agents that remember and learn.
Memory Storage Strategies: Redis, SQL, and Vector Databases
Build the infrastructure for persistent AI agents. Compare the implementation of Redis for session state, SQL for structured logs, and Vector Databases for semantic knowledge retrieval in your Gemini ADK projects.
Memory Retrieval: RAG vs. Native Long-Context
Navigate the most important technical debate in AI systems today. Learn when to use Retrieval-Augmented Generation (RAG) and when to leverage Gemini's massive 2-million token native context window for optimal agent performance.
Module 8: Planning and Reasoning
Build multi-step execution plans and handle uncertainty with advanced reasoning patterns.
Planning in Agentic Systems: CoT, ReAct, and Tree-of-Thought
Master the logic of AI decision-making. Explore advanced planning patterns like Chain-of-Thought and ReAct to help your Gemini agents reason through complex, multi-step goals with clarity and precision.
Execution Plans: Static vs. Dynamic Task Management
Coordinate complex agent activities through robust execution plans. Learn to balance the predictability of static workflows with the flexibility of dynamic, branching agentic behavior using Gemini ADK.
Handling Uncertainty: Ambiguity, Errors, and Clarification Loops
Equip your agents to handle the messiness of the real world. Learn strategies for resolving ambiguous user intents, managing missing information, and building interactive clarification loops in Gemini ADK.
Module 9: Multi-Agent Systems with ADK
Coordinate specialized agents using centralized orchestration and decentralized collaboration strategies.
Why Multiple Agents: Modularity, Expertise, and Division of Labor
Discover why the future of AI is multi-agent. Learn how to scale beyond 'Solo Agents' by implementing modular teams with specialized expertise and efficient division of labor using Gemini ADK.
Agent Roles: Supervisors, Workers, and Evaluators
Build a high-performance AI team. Learn to define and implement specific agent roles—from high-level Supervisors to specialized Workers and rigorous Evaluators—using the Gemini ADK.
Coordination Strategies: Centralized vs. Decentralized Communication
Master the patterns of inter-agent communication. Learn the trade-offs between centralized supervision and decentralized peer-to-peer hand-offs, and implement shared-state 'Blackboard' architectures with Gemini ADK.
Module 10: Human-in-the-Loop Design
Integrate human checkpoints and approval loops for high-risk and ambiguous agent decisions.
Environment Setup: API Keys and SDK Installation
Get ready to build. Step-by-step instructions for obtaining your Google Gemini API keys, installing the development SDK, and configuring your local workspace for agent development.
Hello World Agent: Your First Interactive Chatbot
Cross the starting line of agent development. Build a simple, interactive CLI agent with a custom persona and learn the mechanics of maintaining a conversation state using the Gemini ADK.
Hello World with Tools: Giving Orbit a Calculator
Transform your chatbot into a functional agent. Learn to bind Python functions as tools, enabling your Gemini agent to perform precise calculations and access external data dynamically.
Module 11: Safety, Security, and Compliance
Enforce AI safety principles, data security, and enterprise compliance in agentic systems.
Building Agents that See: Image Reasoning and Visual Analysis
Give your agents eyes. Master the native visual intelligence of Gemini to build agents that can interpret diagrams, extract data from photos, and reason about the physical world through image inputs.
Building Agents that Hear: Audio Processing and Emotion Detection
Give your agents ears. Explore Gemini's native audio capabilities to transcribe speech, identify multiple speakers, and detect emotional nuances in spoken language without external STT services.
Building Agents that Watch: Video and Temporal Reasoning
Unlock the fourth dimension of AI agency. Master Gemini's video capabilities to build agents that understand events over time, detect specific actions, and perform complex temporal reasoning on hour-long recordings.
Module 12: Evaluation and Testing
Define KPIs and testing strategies for non-deterministic, long-running agent behaviors.
Building Robust API Connectors: Auth and Error Handling
Bridge the gap between your agent and the world. Learn to build production-grade API connectors with secure authentication, robust retry logic, and resilient rate limiting for Gemini ADK tools.
Dynamic Tool Discovery: Scaling to 100+ Tools
Master the art of large-scale tool management. Learn how to implement dynamic tool discovery, semantic search for tools, and hierarchical toolkits to prevent agent confusion and optimize context window usage.
Testing and Debugging Tools: Mocks, Fakes, and Observability
Master the developer workflow for AI tools. Learn a rigorous methodology for unit testing your functions, mocking external APIs, and debugging the 'Hand-off' between Gemini and your code.
Module 13: Observability and Debugging
Trace decision paths, log state transitions, and continuously improve agent behavior.
Beyond Basic RAG: Agents as Intelligent Retrievers
Elevate your Retrieval-Augmented Generation. Learn how to transform agents into intelligent retrievers that can self-query, re-rank results, and perform multi-hop reasoning across massive knowledge bases.
Chunking Strategies for Agents: Optimizing for Logic and Reasoning
Prepare your data for intelligent consumption. Explore advanced chunking strategies—from semantic splits to hierarchical structures—that ensure your Gemini agents maintain the logical context of large documents.
Knowledge Graphs and Structured Data: The GraphRAG Paradigm
Move beyond simple vector search. Learn how to connect your Gemini agents to Knowledge Graphs to enable precise, relationship-aware retrieval and complex multi-hop reasoning over structured data.
Module 14: Deployment and Operations
Ship agents to production using cloud-native environments, scaling, and version control.
Prompt Caching: Reducing Latency and Cost in Long-Context Agents
Master the most powerful optimization tool in the Gemini ecosystem. Learn how to use Context Caching to reuse massive datasets across multiple agent turns, drastically reducing both latency and operational costs.
Latency Optimization: Building High-Speed AI Agents
Master the race against time. Learn techniques for optimizing Time-to-First-Token (TTFT), implementing parallel execution, and selecting the right Gemini models to build agents that respond in milliseconds.
Monitoring and Observability: Tracking Tokens, Costs, and Success
Build confidence in your production agents. Learn to implement comprehensive monitoring for token usage, operational costs, and agent success rates using Google Cloud and custom observability patterns.
Module 15: Enterprise Integration
Automate business workflows by integrating agents with existing APIs, databases, and internal tools.
Deploying Agents to Production: Serverless vs. Containerized
Take your agents from local scripts to production scale. Explore the pros and cons of Serverless (AWS Lambda/GCP Functions) and Containerized (Docker/K8s) deployment models for Gemini ADK projects.
Managing Agentic State at Scale: Distributed Sessions and Redis
Solve the statefulness puzzle. Learn how to maintain persistent agent conversations across horizontally scaled servers using distributed databases like Redis and advanced history hydration patterns.
Security and Governance: Redaction, RBAC, and Guardrails
Protect your users and your infrastructure. Learn advanced security patterns for AI agents, including PII redaction, Role-Based Access Control (RBAC) for tools, and robust audit logging strategies.
Module 16: Advanced Agent Patterns
Implement self-reflection, long-horizon persistence, and adaptive learning patterns.
Future of Video: Project Astra and Live Multimodality
Step into the next frontier of AI. Explore the future of real-time, low-latency visual agents through the lens of Project Astra and the evolving native video capabilities of Gemini.
Agentic Hardware: Wearables, Robotics, and IoT
Take AI out of the browser. Explore the integration of Gemini ADK with physical hardware—from smart glasses and wearable sensors to industrial IoT and autonomous robotics.
The Path to AGI: Generalized Intelligence and the Evolution of ADK
Look beyond the horizon. Explore the trajectory from specialized AI agents to Artificial General Intelligence (AGI) and learn how the Gemini ADK is laying the groundwork for self-evolving systems.
Module 17: Capstone Agent Design Project
Design and implement a production-ready Gemini ADK agent system from scratch.
Responsible Agent Design: Ethics, Bias, and Transparency
Build agents that are not only powerful but also fair and transparent. Master the principles of responsible AI design, including bias mitigation and decision-explaining architectures in Gemini ADK.
The Guardrail Architecture: Multi-Layered AI Safety
Engineer safety into the core of your agents. Learn how to implement multi-layered guardrails—from model-level filters to custom middleware and behavioral checks—to prevent agentic drift and failure.
The Future of Interaction: Human-AI Collaboration
Experience the ultimate transition in human-computer interaction. Explore the paradigm shift from using 'AI as a Tool' to working with 'AI as a Partner', and discover your role in the era of collaborative agency.
Course Overview
Format
Self-paced reading
Duration
Approx 6-8 hours
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