World Congress 2026 Europe - Virtual Stage • Jul 2, 2026 • Session details

Building Agentic Applications: A Deep Dive into Zooka, an AI Cardiologist Assistant

Ahmad Adel

Are you building true AI agents or just glorified RAG? Learn to build an autonomous AI cardiologist using the orchestrator-worker pattern, ReAct framework, and long-term memory.

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#1 about 3 min

Defining agentic workflows versus traditional generative AI applications

Distinguishing true agentic autonomy from basic prompting, retrieval-augmented generation, and fixed sequences.

#2 about 3 min

Implementing the orchestrator-worker pattern in agentic workflows

How delegating tasks among specialized agents drives lower costs and higher accuracy in enterprise processes.

#3 about 2 min

Applying the ReAct framework for continuous reasoning and acting

How agents use a continuous loop of thought, action, and observation to automate complex enterprise tasks.

#4 about 3 min

Choosing the right runtime environment for hosting AI agents

Understanding the trade-offs between managed services and custom platforms for agent logging, tracing, and memory management.

#5 about 4 min

Managing working, short-term, and long-term memory in orchestration

How the orchestration layer handles internal monologues, session history, and persistent facts across multiple user turns.

#6 about 2 min

Integrating foundation models and specialized tools for agent actions

Extending the capabilities of multimodal large language models using functional execution tools and natural language database queries.

#7 about 2 min

Standardizing tool integration with the Model Context Protocol

Using an open protocol to create a unified API interface between AI agents and external data systems.

#8 about 3 min

Evaluating frameworks and abstraction levels for building AI agents

Comparing development approaches from low-level LangChain protocols to higher-level frameworks like LangGraph and the Agent Development Kit.

#9 about 5 min

Configuring the Zuka cardiologist assistant using the Agent Development Kit

Examining the Python codebase to define agent profiles, connect tools, and establish a remote server session.

#10 about 6 min

Demonstrating medical diagnostics and long-term memory persistence in Zuka

Interacting with the agent interface to process patient symptoms, search knowledge graphs, and recall medical history across sessions.

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Utilizing the ADK framework for agent logic

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