Build Intelligent AI Agents With Context Engineering

Tuesday, October 7
9:00 a.m. IST | 11:30 a.m. SGT/HKT/CST | 12:30 p.m. JST | 2:30 p.m. AEDT
30 Minutes
If Agentic AI lacks the right context, it can’t reason well, make good decisions, or reliably carry out a task. Context engineering helps make effective use of LLM context windows by selectively choosing and preparing which information is crucial for fulfilling a given task.

In short, you engineer the right context to feed your LLM. And when it comes to context engineering, using a graph database allows you to provide more relevant and accurate information to act and reason upon.

Join us on October 7 for a 30-minute overview of how to build intelligent AI agents that can more reliably complete tasks.

You’ll learn how to:
  • Get started with context engineering using a graph database
  • Improve an agent’s reasoning and decision-making abilities
  • Integrate the Neo4j Graph Database with agentic frameworks, such as Google Agent Development Kit (ADK)


SPEAKER

  Michael Hunger Image

Michael Hunger
Vice President, Product Innovation

Michael Hunger is a Product & Innovation Leader and Java Champion with over 15 years at Neo4j, from an early employee to a key figure shaping the graph database industry. As co-founder of Neo4j Labs, he launched transformative integrations including Graph Data Science, GraphQL, and GenAI ecosystem tools, while building developer relations teams that support hundreds of thousands of users globally. He is an accomplished author and international speaker, having published books on Spring, Neo4j, and DuckDB. Beyond his technical expertise, Michael is passionate about mentoring emerging tech leaders, advocating for diversity in technology, and advising startups on product development and developer community building.

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