A Beginner’s Guide to Setting Up Ollama with Docker Compose
Have you ever wanted to run a powerful large language model (LLM) like Llama 3 or Gemma right on your own computer, but you need a consistent and portable setup?…
Building Intelligent Apps with Spring AI
In today’s fast-paced world of software development, integrating artificial intelligence into applications is no longer just a trend—it’s a necessity. At the heart of this revolution is Generative AI, a…
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 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…
Enterprise AI at Scale: Why Spring AI and Java are Built for the Long Run
While Python remains the undisputed king of AI research, data exploration, and model training, the landscape shifts dramatically when moving from experimental notebooks to high-throughput, mission-critical production systems. For enterprise…
Vibe Coding the Next Generation: How We Built AIMUD Using an AI Ensemble
In the traditional world of software engineering, building a Multi-User Dungeon (MUD) is a rite of passage. It requires handling complex state, real-time networking, concurrency, and deep game logic. Usually,…
Scaling Streams: Mastering Virtual Threads in Spring Boot 4 and Java 25
As a software architect, I’ve seen the industry shift from heavy platform threads to reactive streams, and finally to the “best of both worlds”: Virtual Threads. With the recent release…