This session showcases how Gemini Code Assist revolutionizes end-to-end Java application development. Join us to learn how to accelerate each development stage – from backend to frontend and testing. Discover how to leverage Gemini code generation, completion, and debugging features. Explore how to enhance productivity and build robust, high-quality applications faster. And take away practical methods and techniques for integrating Gemini Code Assist into your workflow.

Build more capable and reliable AI systems by combining context-aware retrieval-augmented generation (RAG) with agentic decision-making in an enterprise AI platform, all in Java! This session covers everything from architecture, context construction, and model routing to action planning, dynamic retrieval, and recursive reasoning, as well as the implementation of essential guardrails and monitoring systems for safe deployments. Learn about best practices, trade-offs, performance, and advanced techniques like evaluations and model context protocol.

This talk demonstrates a fashion app that leverages the power of AlloyDB, Google Cloud’s fully managed PostgreSQL-compatible database, to provide users with intelligent recommendations for matching outfits. User-uploaded data of their clothes triggers a styling insight on how to pair the outfit with matching real-time fashion advice. This is enabled through an intuitive contextual search (vector search) powered by AlloyDB and Google’s ScaNN index to deliver faster vector search results, low-latency querying, and response times. While we’re at it, we’ll showcase the power of the AlloyDB columnar engine on joins required by the application to generate style recommendations. To complete the experience, we’ll engage the Vertex AI Gemini API package from Spring and LangChain4j integrations for generative recommendations and a visual representation of the personalized style. This entire application is built on a Java Spring Boot framework and deployed serverlessly on Cloud Run, ensuring scalability and cost efficiency. This talk explores how these technologies work together to create a dynamic and engaging fashion experience.

Java developers, join us to connect with your peers and explore best practices for building robust GenAI Java applications. We'll walk through sample apps as we discuss topics including cost reduction, efficient embedding generation, entity management, and testing. Then we'll dive deeper into the topics most relevant to you.

Level up your Java apps with the power of Gemini. This session explores how Java developers can easily integrate generative AI features into their applications using LangChain4j. We’ll cover everything from building chatbots and implementing in-context learning to creating agentic workflows and using advanced techniques like unstructured data extraction. Learn best practices and build smart, AI-powered Java applications with ease. No Python experience required.

Leverage Google Cloud Observability when instrumenting your code with logging, monitoring, and tracing capabilities. Try it out yourself in one of the popular programming languages, such as Java, Python, JavaScript, or Go.

Learn how AI-assisted coding and agents improve your development and modernization workflows. Observe Gemini Code Assist perform ticket review, code generation, code rewrite, and spec generation, as well as COBOL to Java mainframe code transformation.