Building reliable AI applications involves more than writing effective prompts. While prompt engineering focuses on how instructions are phrased, an LLM’s response also depends on the broader context provided to it, including external knowledge, memory, tools, instructions, and the current state of the application.
In our recent webinar, “Context Engineering with Spring AI,” Boni García explored how developers can move beyond prompt engineering and use context engineering to build more reliable and maintainable AI applications. Through practical examples and live demos, the session demonstrated how different context mechanisms can work together to improve the quality of AI assistants.
For a deeper look at the concepts discussed in the webinar, Boni has also published a detailed technical article on Context Engineering with Spring AI, which explores the context engineering stack and its implementation with Spring AI.
Why This Topic Matters
An AI application rarely operates with a prompt alone. It may need to remember previous interactions, retrieve relevant information, access external tools, or understand the current state of a user’s request.
Managing these different sources of information effectively is what makes context engineering important. For developers building AI applications with Spring, Spring AI provides abstractions and features that can help bring these concepts together in a structured way.
Key Takeaways
- Understand why prompt engineering alone is not enough for robust AI applications.
- Explore the different sources of context that influence an LLM’s responses.
- Learn how Spring AI supports memory, retrieval, and tool calling.
- Understand practical architecture and design patterns for Spring AI applications.
- See how context mechanisms can improve the quality and reliability of AI assistants.
- Get practical insights into context engineering through live demonstrations.
Slide Deck
Want to revisit the concepts discussed during the webinar? You can access the presentation slides below.
Webinar Recording
Watch the complete webinar recording to explore context engineering with Spring AI, including the concepts, architecture patterns, and live demonstrations covered during the session.
Coming Soon…
Q&A Session
The webinar concluded with a live Q&A session, where Boni García answered questions around context engineering, Spring AI, and building reliable LLM-based applications.
Coming Soon…
Stay Tuned
Our monthly webinar series brings together Java performance experts and practitioners to explore practical techniques for JVM troubleshooting, performance engineering, observability, and emerging technologies.
Stay tuned for upcoming sessions covering real-world Java performance challenges and approaches to making production troubleshooting faster and more effective.
📌Click here to explore our upcoming webinars.
Don’t miss our next webinar!
Share your Thoughts!