Imagine you're building an e-commerce application. You want to use Django and bring all the benefits of that framework. But there are issues. Django's service-oriented architecture doesn’t play well with the event-driven nature of what you need to build. You need to automatically send a welcome email when a new user registers, instantly update inventory levels when an item is purchased, and notify users when their orders are shipped.

Let’s start with a statement everyone can agree on: AI coding is now a permanent fixture of the software development lifecycle. Even if your team hasn’t introduced it officially yet, it’s only a matter of time before one of your peers kicks off the discussion or pushes a PR that, perhaps even unbeknownst to you, is entirely AI-generated. Now, let’s rub some folks the wrong way: AI coding in a microservices architecture is a recipe for disaster.

Check out Scout Monitoring's ollama-rails GitHub repo for samples on how to use ollama-ai to communicate with Ollama. Large Language Models (LLMs) have emerged as a game-changer, enabling machines to understand, generate, and process human language with unprecedented accuracy and fluency. One such tool that has gained significant attention is Ollama, a cutting-edge platform that allows developers to run LLMs locally without relying on cloud services.