Uploaded April 2026 | Updated September 2026, 2 weeks ago
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The secret to great AI? It's all about context—the art of context window curation. In this hands-on session, we'll explore how Spring AI helps you master this art, taking you from fundamentals to best agentic patterns.
In the first part, we'll cover the fundamentals: ChatClient essentials, prompt engineering, and conversation memory. We'll explore how to extend LLM execution paths using Advisors (intercepting and enhancing AI interactions) and Recursive Advisors (enabling iterative workflows). Enrich your context with RAG, connect to external services using Tools, and use MCP for standardized integration.
The second part focuses on agentic patterns and how to turn an assistant into something that can reason, plan, and act:
- Agent Skills: Modular, LLM-agnostic capabilities loaded on demand
- AskUserQuestion: Gather requirements before acting
- Todo: Prevent "lost in the middle" failures with structured planning
- Subagent Orchestration: Delegate to specialized agents with isolated context windows
- A2A and ACP Protocols: Build interoperable agents that communicate across system boundaries
- Tool Search Tool: Dynamic tool discovery
- LLM-as-a-Judge: Automated response evaluation and quality control
Along the way, we'll address critical production concerns, including observability (metrics, logging, tracing) and security guardrails. You'll leave with a clear understanding of how to integrate generative AI into Spring applications, from your first prompt to a complete agentic architecture
Please subscribe to our YouTube channel @ youtube.com/@DevoxxForever
Subscribe to LinkedIn @ linkedin.com/company/voxxed-days-amsterdam
Follow us on Twitter @ twitter.com/voxxedamsterdam
The secret to great AI? It's all about context—the art of context window curation. In this hands-on session, we'll explore how Spring AI helps you master this art, taking you from fundamentals to best agentic patterns.
In the first part, we'll cover the fundamentals: ChatClient essentials, prompt engineering, and conversation memory. We'll explore how to extend LLM execution paths using Advisors (intercepting and enhancing AI interactions) and Recursive Advisors (enabling iterative workflows). Enrich your context with RAG, connect to external services using Tools, and use MCP for standardized integration.
The second part focuses on agentic patterns and how to turn an assistant into something that can reason, plan, and act:
- Agent Skills: Modular, LLM-agnostic capabilities loaded on demand
- AskUserQuestion: Gather requirements before acting
- Todo: Prevent "lost in the middle" failures with structured planning
- Subagent Orchestration: Delegate to specialized agents with isolated context windows
- A2A and ACP Protocols: Build interoperable agents that communicate across system boundaries
- Tool Search Tool: Dynamic tool discovery
- LLM-as-a-Judge: Automated response evaluation and quality control
Along the way, we'll address critical production concerns, including observability (metrics, logging, tracing) and security guardrails. You'll leave with a clear understanding of how to integrate generative AI into Spring applications, from your first prompt to a complete agentic architecture
![[VDBUH2026] Victor Rentea - Kenote: AI Didn’t Replace You. It Promoted You!](https://i.ytimg.com/vi/5hVlf9_G71Q/mqdefault.jpg "[VDBUH2026] Victor Rentea - Kenote: AI Didn’t Replace You. It Promoted You!
We’ve always been rewarded for writing code, debugging systems, and mastering frameworks. But today, AI no longer just assists – it builds, analyzes, debugs, and reasons, so our role gets upgraded to shaping systems, taking decisions, and achieving outcomes. But as our attention moves away from code, how can we remain in control and keep the quality high? That’s the tension many senior engineers feel. This talk explores how AI agents can offload our chores, preserve our mental energy, and amplify our impact across the system—distilling lessons from early adopters of agentic engineering.
But this is not a talk about tools. It’s a talk about identity.
Because the real question today isn’t: “Will AI change my job?”
It’s: “Will I evolve fast enough to stay relevant?”")
