Year: 2026

Multi-Agent Systems and Agentic AI Architectures "A single agent can solve a task. A team of agents can solve a business problem." Introduction In Part 7, we learned that an…

Building AI Agents: Reasoning, Planning, Tools and Autonomous Workflows "A chatbot answers questions. An agent solves problems." Introduction So far in this series, we have learned: Part 1 — LLM…

Spring AI Deep Dive: ChatClient, Advisors, Memory, Tool Calling and Structured Output "Spring Boot simplified enterprise development. Spring AI aims to simplify enterprise AI development." Introduction In our journey so…

Prompt Engineering for Enterprise AI: The New API Design "In traditional software, APIs define behavior. In AI systems, prompts define behavior." Introduction In our previous articles, we learned: Part 1:…

Building Your First RAG Application Using Spring AI "Theory teaches concepts. Projects teach engineering." Introduction In the previous articles we learned: Part 1 LLMs Tokens Transformers Part 2 Embeddings Vector…

Retrieval Augmented Generation (RAG): Building AI Systems That Know Your Data "The most valuable enterprise AI systems are not trained on the internet. They are built on your organization's knowledge."…

Tokens, Embeddings and Vector Databases for Java Developers "Databases store data. Vector databases store meaning." Introduction In the previous article, we learned: What an LLM is. How transformers work. Tokens…