Our team has been delivering outstanding talks at conferences and leading quarterly training sessions for Java developers, SRE engineers, Performance QA engineers, and DevOps engineers. Over the past year, we’ve also been running a series of webinars, where our very own Ram Lakshmanan shared deep insights into Java performance and troubleshooting. We recently celebrated this journey in our Java Performance Webinars Milestone Blog.
Now, we’re excited to take this initiative to the next level. Moving forward, our monthly webinars will not only feature in-house expertise but also bring in renowned external speakers from the global Java community. These sessions are designed to deliver valuable techniques, best practices, and tools to help you optimize Java performance and solve complex troubleshooting challenges.
This blog category will keep you updated with details on upcoming events as well as recaps of past sessions. Stay tuned for expert insights, practical takeaways, and new learning opportunities every month!
Upcoming Webinar
- Date: September 09, 2026
- Time: 8:30 AM PDT
- Duration: 30 Minutes
Title:
Context Engineering with Spring AI
Description:
Many discussions around AI applications focus on prompt engineering. But in practice, prompts are only one piece of the puzzle. The quality of an LLM-based application depends on all the information we provide to the model: instructions, external knowledge, tools, memory, and the current state of the application.
In this webinar, we’ll introduce the concept of context engineering and explore how Spring AI can help developers put it into practice. We’ll look at the different sources of context that shape a model’s responses and see how features such as memory, retrieval, and tool calling can be combined to build AI applications that are more reliable and easier to maintain.
The session includes live demos of Spring AI applications, illustrating how a few well-designed context mechanisms can make a significant difference in the quality of an AI assistant.
Key Takeaways:
- Understand why prompt engineering alone is not enough to build robust AI applications.
- Explore the main sources of context that influence an LLM’s responses.
- Learn how Spring AI supports concepts such as memory, retrieval, and tool calling.
- Discover practical architecture and design patterns for building Spring AI applications.
- See through live demos how context mechanisms can improve the quality and reliability of AI assistants.
- Participate in a live Q&A with Boni García and get expert insights around context engineering and Spring AI.
Speaker Bio
Boni García is an Associate Professor of Telematic Engineering at Universidad Carlos III de Madrid, where he teaches software engineering and conducts research in browser automation, software testing, and AI-assisted software development.
He is a member of the Selenium Technical Leadership Committee (TLC) and the creator of WebDriverManager, an open-source project used by Java developers worldwide. Boni is also the author of the forthcoming Manning book Context Engineering, which explores the principles and techniques behind building reliable applications powered by LLMs and AI agents.