Yesterday I started this five-part course with n8n. The idea behind the series is that some of the most useful AI tools are not frontier models at all. They are the quieter tools sitting underneath the work, moving data, running models, connecting APIs, giving agents tools and keeping workflows alive after the chat window closes.
The first guide was about n8n, the wiring layer. It showed how to connect models, apps, APIs, triggers and actions into one working system.
Today is the second tool, and it fits almost perfectly beside n8n.
Ollama is the engine you can put behind that wiring.
Its open-source GitHub project now has around 179,800 stars. Its official integration pages include Claude Code, Codex, Copilot CLI, VS Code, Cline, n8n, OpenClaw, Hermes and several other agent and coding systems. The project reached v0.33.2 only a few days ago.
If you use AI regularly, this is one of those tools I think you should understand now before it becomes one of those things everyone suddenly assumes you already know.
Inside the full guide, I take Ollama from first install to real work: running open models locally, choosing the right model, connecting Python and n8n, building reusable AI workers, using tools, JSON, agents and memory, and knowing when local AI can cut cost and keep more work private. If you are building AI workflows now, this is one of those tools worth understanding before your stack gets more expensive and harder to control.
