Daniel Oh

Supercharge Agentic AI Apps: A DevEx-Driven Approach to Cloud-Native Scaffolding

What if a single prompt could transform your generative AI service into a fully autonomous agent? See how it's done.

Supercharge Agentic AI Apps: A DevEx-Driven Approach to Cloud-Native Scaffolding
#1about 5 minutes

Understanding the evolution and autonomy of agentic AI

Agentic AI evolves from traditional AI by autonomously deciding which external tools and resources to use, unlike systems with predefined workflows.

#2about 3 minutes

Exploring frameworks for building agentic AI applications in Java

While Python has many agentic AI frameworks, Java developers can combine tools like Quarkus, Spring AI, and LangChain4j to build similar applications.

#3about 5 minutes

Scaffolding a new agentic AI project with Quarkus

Use the Quarkus application generator to quickly create a new project with dependencies for OpenAI and MCP, then run it in development mode for live coding.

#4about 3 minutes

Defining the agent's behavior with a Java interface

A simple Java interface with LangChain4j annotations and a carefully crafted system prompt can instruct the AI model to autonomously utilize any available tools.

#5about 5 minutes

Configuring and auto-starting MCP servers in Quarkus

Configure external tools like search, maps, and messaging by defining MCP servers in the application properties file, which Quarkus automatically downloads and runs.

#6about 4 minutes

Demonstrating a multi-tool agent finding and sharing information

A live demonstration shows the agent autonomously using search, maps, and Slack tools to fulfill a complex user request for finding and sharing restaurant recommendations.

#7about 3 minutes

Using software templates to share agentic AI applications

Simplify multi-agent development and collaboration by using an Internal Developer Platform (IDP) like Backstage, with Quarkus automatically generating software templates from your project.

#8about 2 minutes

The future roadmap for MCP and key takeaways

The MCP roadmap includes a server registry and multi-modal support, and the key takeaway is that Quarkus simplifies complex agentic AI development for Java developers.

Related jobs
Jobs that call for the skills explored in this talk.

Featured Partners

Related Videos

Create AI-Infused Java Apps with LangChain4j29:18

Create AI-Infused Java Apps with LangChain4j

Daniel Oh, Kevin Dubois

Agentic AI Systems for Critical Workloads30:01

Agentic AI Systems for Critical Workloads

Mario Fusco

Agents for the Sake of Happiness39:11

Agents for the Sake of Happiness

Thomas Dohmke

Developer Joy with Quarkus28:21

Developer Joy with Quarkus

Daniel Oh

Infusing Generative AI in your Java Apps with LangChain4j32:02

Infusing Generative AI in your Java Apps with LangChain4j

Kevin Dubois

Application Modernization Leveraging Gen-AI for Automated Code Transformation41:17

Application Modernization Leveraging Gen-AI for Automated Code Transformation

Syed M Shaaf

Reimagining the Developer Experience: The AI Advantage27:43

Reimagining the Developer Experience: The AI Advantage

Anu Bharadwaj, Tobias Schlottke

On a Secret Mission: Developing AI Agents29:03

On a Secret Mission: Developing AI Agents

Jörg Neumann

From learning to earning

Jobs that call for the skills explored in this talk.