Intermediate1h25m

Building Live Voice Agents with Google’s ADK

Instructors: Lavi Nigam, Sita Lakshmi Sangameswaran

Google logo

Earn an accomplishment with PRO · Updated Oct 28, 2025

  • Intermediate
  • 1h25m
  • 9 Video Lessons
  • 5 Code Examples
  • 1 Graded Assignment PRO
  • Earn an accomplishment with PRO
  • Updated Oct 28, 2025
  • Instructors: Lavi Nigam, Sita Lakshmi Sangameswaran
  • GoogleGoogle
  • Learn more aboutMembership PRO Plan

What you'll learn

  • Build real-time voice agents with Google’s Agent Development Kit (ADK) that can carry natural, real-time conversations while connecting to external tools and data.

  • Design multi-agent systems that use memory, tools, and orchestration patterns to coordinate specialized agents like planners, researchers, and writers.

  • Take agents to production by adding guardrails, persistent memory, automated evaluations, and review methods for deploying on Google Cloud’s Vertex AI Agent Engine.

Course recap

PRO

This course, built in partnership with Google, teaches how to build multi-agent AI applications using Google's Agent Development Kit (ADK). Starting from a simple voice agent, the course progressively builds toward a complete podcast production pipeline that takes user voice input, researches topics via web search, enriches findings with financial data, generates a structured report, and produces a two-person audio podcast using Gemini TTS.

Concept map

Concepts in Building Live Voice Agents with Google’s ADK and the courses that connect to themBuilding Live Voice Agents with Google's ADKBuilding Live Voice Agent…AI AgentsSession, State, and MemoryCallbacksMulti-agent orchestrationInstruction tuningBuilding AI Voice Agents for ProductionBuilding AI Voice Agents…Design, Develop, and Deploy Multi-Agent Systems with CrewAIDesign, Develop, and Depl…AI Agents for Image and Video GenerationAI Agents for Image and V…Building AI Browser AgentsBuilding and Evaluating Data AgentsBuilding and Evaluating D…Multi AI Agent Systems with CrewAIMulti AI Agent Systems wi…Concepts in Building Live Voice Agents with Google’s ADK and the courses that connect to themBuilding Live Voice Agents with Google's ADKBuilding Live V…AI AgentsSession, State, and MemorySession, State,…CallbacksMulti-agent orchestrationMulti-agent orc…Instruction tuningInstruction tun…

Key concepts

  • AI AgentsADK agents as constructs with an LLM brain and tools for real-world interaction
  • Session, State, and MemoryADK primitives: session as conversation container, state as short-term scratchpad, memory as long-term persistence
  • CallbacksBefore/after hooks for agent, tool, and model calls that enable deterministic guardrails on non-deterministic LLM behavior
  • Multi-agent orchestrationAgentTool pattern allowing one agent to delegate specialized tasks to another agent
  • Instruction tuningDetailed prompts that define agent identity, workflow steps, refusal mandates, and output schemas

Lesson highlights

  1. 1.Introduction — Overview of ADK and the podcast agent project
  2. 2.Build Your First Agent — Creating agents with Python/YAML, adding Google Search tool, instruction tuning
  3. 3.ADK Primitives — Session, State, and Memory - Theoretical foundations of agent data management
  4. 4.Tools for Your Agent — Custom Python tools (financial data via yfinance), tool description best practices
  5. 5.Adding a Research Agent — Background processing pattern, coordinator-dispatcher model, Pydantic schemas
  6. 6.Instruction Tuning and Guardrails — Before/after tool callbacks for domain filtering and source logging
  7. 7.Multi-agent Orchestration — Three-tier architecture with producer and podcaster agents, Gemini TTS for audio
  8. 8.Productionize Your Agent — Live bidirectional streaming, Memory Bank, evaluation, deployment, security
  9. 9.Conclusion — Course recap

About this course

Join our new short course, Building Live Voice Agents with Google’s ADK! Learn from Lavi Nigam and Sita Lakshmi Sangameswaran, Machine Learning Engineers at Google.

You’ll learn how to build and deploy AI agents with Google’s open source Agent Development Kit (ADK). ADK provides modular components such as models, tools, memory, and orchestration, that make it easier to create both simple and complex systems.

You’ll start by building a voice agent that takes speech input, reasons with an LLM, and responds with voice output. Then you’ll work with sessions, state, and memory, and extend your agents with tools and APIs to perform real-world tasks.

Next, you’ll add callbacks and guardrails for reliability and orchestrate specialized agents like planners and researchers. You’ll build a podcast agent that researches a topic, drafts a conversational script, and produces multi-speaker audio with Gemini text-to-speech models. Then, you’ll build in guardrails to secure and optimize your agents before reviewing methods for deploying them into production.

In detail, you’ll:

  • Build your first agent with ADK, connect it to Google Search, and test live voice interactions in the ADK Web UI.
  • Use sessions, state, and memory to manage conversations, share context between tools, and give agents short-term tracking and long-term recall across interactions.
  • Add custom tools and API, integrate them with ADK, and refine agent instructions so they follow defined workflows effectively.
  • Generate structured research reports by defining schemas, rewriting agent instructions to act as a coordinator, and saving results as markdown files for downstream use.
  • Add guardrails with callbacks to filter unsafe sources, enforce rules, and log tool activity, making your agents safer, more predictable, and production-ready.
  • Build a podcast agent by combining schemas, callbacks, and a dedicated audio agent, and generate multi-speaker episodes with Gemini text-to-speech in a scalable workflow.
  • Learn how to productionize your agents by giving them persistent memory, testing their reliability, deploying on Vertex AI, and adding security and monitoring for safe scaling.

Who should join?

This course is ideal for AI builders seeking to develop agents that extend beyond text. If you’re interested in building voice-based applications like a podcast, adding voice feedback to an agent, coordinating multiple agents, or building production-ready systems, this course will give you the hands-on foundation you need.

Course Outline

9 Lessons・5 Code Examples
Unlock certificates

Elevate your learning experience with Pro

Upgrade to Pro and gain unlimited accomplishments on your resume

Learn More

Instructors

Lavi Nigam

Lavi Nigam

Machine Learning Engineer at Google

Sita Lakshmi Sangameswaran

Sita Lakshmi Sangameswaran

Machine Learning Engineer at Google

Course access is free for a limited time during the DeepLearning.AI learning platform beta!

Want to learn more about Generative AI?

Keep learning with updates on curated AI news, courses, and events, as well as Andrew’s thoughts from DeepLearning.AI!