The Complete Guide to Modern AI Terminology: From Neural Networks to RAG, MCP, and Agentic Systems
Artificial Intelligence is evolving rapidly, bringing with it a wave of new concepts, acronyms, and technical jargon. Whether you are building AI applications, reading tech news, or evaluating tools for…
Spring Data JPA for Dummies: Persisting Data Like a Pro
Ever feel bogged down by writing tons of code just to interact with your database? If you’re a Java developer working with relational databases, Spring Data JPA is your new…
Bridging Knowledge and Action: How RAG and MCP Power the Next Era of AI Agents
As Large Language Models (LLMs) continue to evolve, two fundamental limitations persist: knowledge cutoffs and isolation from execution environments. An AI model may possess impressive reasoning capabilities, but without direct…
Integrating Drools with a Spring Boot Microservice
This blog post will guide you through integrating the Drools rule engine with your Spring Boot microservice. We’ll cover the necessary dependencies, configuration, and an example service to demonstrate its…
Mastering Retrieval-Augmented Generation (RAG) with Spring AI
Retrieval-Augmented Generation (RAG) has become the gold standard architecture for extending the capabilities of Large Language Models (LLMs) with enterprise domain knowledge. By combining the natural language understanding of LLMs…
Spring Data REST: Simplify RESTful API Development
Spring Data REST is a Spring module that automatically creates RESTful APIs for Spring Data repositories. It eliminates boilerplate code, allowing you to focus on your application’s core logic. Benefits:…
Integrating Model Context Protocol (MCP) Tooling with Spring AI
The Model Context Protocol (MCP), originally introduced by Anthropic, is an open standard designed to standardize how Large Language Models (LLMs) connect with external context sources—such as databases, local file…