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World Congress 2026 Europe - Virtual Stage • Jun 30, 2026 • Session details

Building and Deploying Multi-Agent Systems with ADK and Vertex AI

Saoussen Chaabnia

Monolithic prompts lead to fragile systems and context bloat. Discover how to build and deploy deterministic, debuggable multi-agent workflows using Google ADK and Vertex AI.

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#1 about 4 min

Workshop session outcomes and companion resource repository

The core outcomes of the session and where to find the companion workshop code.

#2 about 4 min

Defining AI agents and their autonomous capabilities

How AI agents perceive their environment, reason through decisions, and execute actions.

#3 about 5 min

Agent components, memory types, and execution loops

The fundamental building blocks of an agent including short-term context and long-term memory.

#4 about 5 min

Core capabilities of the Google ADK

How ADK enables deterministic control, agent communication, and model-agnostic execution in Python.

#5 about 6 min

Building specialized multi-agent hierarchies instead of monolithic prompts

The advantages of dividing complex workflows into organized trees of specialized agents.

#6 about 5 min

Workflow agents versus LLM reasoning agents in ADK

Choosing between dynamic reasoning capabilities and deterministic coordination patterns like sequential execution.

#7 about 4 min

Implementing logic hooks with ADK execution callbacks

How to inject operational logic like logging and authentication without modifying core behavior.

#8 about 3 min

Design patterns for child sub-agents and agent tools

When to pass full session scope to a child agent versus invoking it as a discrete functional tool.

#9 about 5 min

Bridging the gap from local development to production deployments

Resolving containerization, security, networking, and observability gaps before deploying agents to the cloud.

#10 about 7 min

Deploying applications directly to Gemini Enterprise Agent Runtime

How the managed runtime automatically handles scaling, context management, and tracing for workflows.

#11 about 2 min

Packaging ADK workflows with Python deployment scripts

Writing initialization logic to push code artifacts into registries and managed cloud endpoints.

#12 about 4 min

Connecting frontends via a FastAPI proxy backend layer

Using remote runners and server-sent events to safely proxy UI requests into deployed agent endpoints.

#13 about 5 min

Architecting a multi-agent content creation pipeline application

Mapping sequential, looping, and parallel agent responsibilities into a master orchestrator application.

#14 about 11 min

Live demonstration of the deployed multi-agent content application

Executing the content generation flow and reviewing workflow traces within the runtime console.

#15 about 4 min

Examining ADK Python configurations and sample class setups

Final walkthrough of the repository structure and sample Python class setups for custom tools.

Matching moments

46 sec

Introduction to distributed multi-agent systems

Saoussen Chaabnia Saoussen Chaabnia · Europe 2026 Virtual

1:29 min

Utilizing the ADK framework for agent logic

Saoussen Chaabnia Saoussen Chaabnia · Europe 2026 Virtual

2:43 min

Deploying a web application through an AI agent workflow

Mike Mike · WWC 2025

4:05 min

Testing the completed multi-agent database workflow

Chris Heilmann +2 · LIVE

4:56 min

Architectural setup for the agentic AI live deployment demo

Daniel Oh Daniel Oh · WWC Europe 2026

40 sec

Introduction to building real-world AI agent solutions

Dennis Zielke Dennis Zielke +1 · WWC 2025

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