Zaid Zaim
Developer Advocate EMEA at Neo4j | Microsoft AI MVP
Berlin, Germany
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As a Developer Advocate at Neo4j, I help developers harness the power of graph technology and AI. A Microsoft MVP and global speaker at events like TED, Microsoft Build, and WeAreDevelopers, I focus on making complex tech accessible through content, community, and hands-on support. My mission is to connect, empower, and inspire developers to build impactful solutions.
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Context Graphs: Agent Memory as a Super Power
AI agents can follow prompts and use tools, but often lack the institutional context needed to explain why a decision is made. That reasoning: policies, precedents, and past outcomes are usually scattered across systems and human memory.
Context graphs capture this missing layer by modeling decision traces over time, including causality and context. By giving agents access to just enough historical and organizational knowledge, context graphs enable more explainable, consistent, and auditable decisions.
Why AI Agents Love Knowledge Graphs?
AI agents are moving beyond simple prompt–response interactions toward architectures that reason over connected data. This session explores how Aura Agents leverage knowledge graphs to ground agent workflows in structured relationships, improving context integration, reasoning transparency, and response consistency. You’ll also see how Neo4j MCP tools enable agents to query graph data directly within their reasoning loop, turning connected data into an active cognition layer. Key takeaways include practical patterns for integrating graph-native context, using MCP-based tooling with agents, and building more reliable, context-aware AI systems that evolve beyond stateless interactions.
How to become AI Community Leader?
The Global AI Community—home to over 60,000 developers, experts, and enthusiasts—offers far more than just an online platform; it’s a thriving ecosystem for learning, collaboration, and breakthroughs in artificial intelligence. Hear firsthand from experienced chapter leaders as they share the challenges they’ve overcome, the pivotal moments in their career journeys, and the leadership principles that guide them. Gain invaluable insights into building and nurturing your own local chapter—from identifying key stakeholders and rallying early supporters, to organizing hands-on workshops, hackathons, and mentorship programs that spark curiosity and inspire innovation. Whether you’re a newcomer or a seasoned AI professional, discover how to foster a culture of inclusion and continuous growth, ensuring every member feels empowered to explore, create, and lead. Learn how to turn your vision for community engagement into practical, high-impact events that pave the way for future collaboration.
How Mixed Reality, Azure AI and Drones turned me into a Magician?
What happens when you combine a drone, an XR headset, and a multimodal AI copilot? You get magic. In this short and mind-bending session, I’ll show how I built an immersive system using Unity, Meta Quest 3, Azure OpenAI, and a real drone—where gestures summon flight, speech controls AI, and a digital twin mirrors reality. From obstacle-avoiding drones to an AI assistant (“Anna”) that sees, hears, and acts in XR—
Mastering Agents using Azure AI Foundry
Designed for developers, students, and AI enthusiasts with little to no prior experience in agent-based systems, this session combines conceptual grounding with practical implementation. Participants will learn how to build simple yet powerful AI agents that can plan, reason, and act in virtual environments. The workshop focuses on modularity, decision-making, and the fundamentals of intelligent behavior through code-based examples and guided labs, leveraging Azure AI Foundry as a platform for experimentation.
Whether you're curious about how intelligent agents work in games, simulations, or real-world applications, this workshop will empower you to design your first AI agent using Python and modern agent design principles.
By the end of this workshop, participants will be able to:
- Understand what AI agents are and how they fit within the broader AI ecosystem.
- Explore key concepts such as agent goals, beliefs, actions, and reasoning.
- Set up the development environment and navigate AI agent frameworks such as Semantic Kernel and Autogen.
- Implement simple rule-based agents and expand them to more complex behaviors.
- Use Python to model agent logic and simulate interactions in sandbox environments.
- Reflect on real-world applications of autonomous agents in fields like robotics, games, and digital assistants.
- Collaborate and share agent designs using GitHub and open-source workflows.
Context Graphs for Explainable, Decision-Aware AI Agents
AI agents can follow prompts and call tools, but they often lack the persistent organizational context needed to explain decisions, adapt over time, and maintain consistency across interactions.
In this session, you’ll learn how to build a knowledge layer for AI agents using Microsoft Foundry and Neo4j through context graphs. Instead of relying only on short-term conversation memory, context graphs model relationships, decision traces, historical interactions, and organizational knowledge in a structured and queryable way.
Through practical demonstrations, we’ll explore how to connect Neo4j with an AI agent stack in Microsoft Foundry to create agents that can retrieve relevant context, reason over prior interactions, and provide more explainable and auditable responses. You’ll see how graph-based memory enables persistent understanding, personalization, and context-aware decision-making without overwhelming the model with unnecessary information.
The session focuses on context engineering and the emerging role of knowledge layers as a foundation for scalable, explainable, and enterprise-ready AI agents.
Zaid Zaim
Developer Advocate EMEA at Neo4j | Microsoft AI MVP
Berlin, Germany
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