fidzu : programming

As agentic AI shifts from prototypes to enterprise production, Java emerges as a powerful alternative to Python-centric stacks. This article looks into building robust agentic applications using LangChain4j for orchestration, Quarks for high-performance deployment, Model Context Protocol (MCP) for standardized tool and data access, and OpenTelemetry for comprehensive observability. Through practical code examples - including tool definitions, agent creation with memory, RAG integration, and production patterns - the guide demonstrates Java's advantages in type safety, low-latency execution, deep system integration, and audit-ready tracing. This is ideal for developers seeking scalable, reliable agentic solutions in mission-critical environments.

Agentic AI - autonomous systems that reason, plan, use tools, remember context, and execute complex multi-step tasks - is moving from experimental prototypes to production workloads in enterprises. While Python ecosystems (LangChain, LlamaIndex, CrewAI) led the early wave, Java is emerging as a serious contender for mission-critical agentic applications.

09 Apr 2026 4:00pm GMT

Modern APIs often need to support dynamic filtering, sorting, and pagination without creating dozens of custom endpoints. One of the most widely used standards for this is OData (Open Data Protocol). OData has established itself as a powerful standard for building and consuming RESTful APIs. It provides a uniform way to query and manipulate data, offering clients unparalleled flexibility through system query options like $filter, $select, and $expand.

Example:

09 Apr 2026 3:00pm GMT

When working on modern software, a developer will often use hundreds or thousands of dependencies. Кeeping an accurate and consistent bill of materials is essential for license compliance and for security.

Motivation

In a large organization, the scope of dependencies review given by build-time scanning has some limitations.

09 Apr 2026 2:00pm GMT