AI

As a senior software engineer primarily working in Ruby but with experience across Go, Node.js, and Python, I’m always evaluating tools and frameworks that promise to make our systems smarter, faster, or more adaptive. Recently, two acronyms from the world of LLMs and AI infrastructure have been gaining traction in mainstream development: RAG (Retrieval-Augmented Generation) and MCP (Model Control Plane). Both offer powerful abstractions that can benefit modern software architectures far beyond machine learning labs.

Alberto Fortin’s recent post on dialing back LLM usage resonated with me. Like many developers, I’ve found AI to be both a productivity godsend and a source of friction. It can feel like magic — until it quietly leads you down the wrong path.