GenAI & BeyondConference50min
AI Agents, the New Frontier for LLMs
This session introduces intelligent agents as the next evolution for LLMs, covering agent definitions, limitations, and key patterns. Attendees will implement Java-based agents using LangChain4j and ADK, explore agent communication via MCP and A2A protocols, and learn how agents can deliver advanced, interactive responses beyond basic LLM capabilities.
Guillaume LaforgeGoogle
talkDetail.whenAndWhere
Wednesday, October 8, 16:40-17:30
Room 9
talks.roomOccupancytalks.noOccupancyInfo
Know Large Language Models at your fingertips?
Mastering Retrieval Augmented Generation to help an LLM search your documents?
It's time to dive into the wonderful world of intelligent agents, the next frontier for LLMs! In this session, we will first define what agents are, or at least what makes a system "agentic". We will explain the limitations of LLMs, key agent characteristics and patterns. Then, through concrete examples, we will implement various agents in Java, using the LangChain4j and ADK frameworks, to illustrate some typical agent patterns and to understand how to go beyond a simple LLM call to obtain responses that meet the needs of your users, or even to trigger actions with the surrounding system. But it’s not all we’ll learn about! An agent doesn’t live alone on a desert tropical island. Indeed it can communicate with other agents via tools that can be invoked thanks to the Model Context Protocol (MCP).
They can also interact with other remote agents from other platforms and ecosystems, thanks to the Agent To Agent protocol (A2A). Are you ready for the next hype on agents?
Come and discover it in this session!
Mastering Retrieval Augmented Generation to help an LLM search your documents?
It's time to dive into the wonderful world of intelligent agents, the next frontier for LLMs! In this session, we will first define what agents are, or at least what makes a system "agentic". We will explain the limitations of LLMs, key agent characteristics and patterns. Then, through concrete examples, we will implement various agents in Java, using the LangChain4j and ADK frameworks, to illustrate some typical agent patterns and to understand how to go beyond a simple LLM call to obtain responses that meet the needs of your users, or even to trigger actions with the surrounding system. But it’s not all we’ll learn about! An agent doesn’t live alone on a desert tropical island. Indeed it can communicate with other agents via tools that can be invoked thanks to the Model Context Protocol (MCP).
They can also interact with other remote agents from other platforms and ecosystems, thanks to the Agent To Agent protocol (A2A). Are you ready for the next hype on agents?
Come and discover it in this session!
talkDetail.shareFeedback
talkDetail.signInRequired
talkDetail.signInToFeedbackDescription
occupancy.title
talkDetail.signInRequired
occupancy.signInToVoteDescription
comments.speakerNotEnabledComments