There is no shortage of discussion about AI, and LLMs in particular. This is my personal take on the debate: the claims I question, the concerns I share, and the questions I am still working through. Wild claims abound, from “Soon, we won’t need developers anymore” and “AI is taking over the world” to “LLMs are a dead end,” “LLMs are bad for the environment,” “LLMs commit plagiarism,” and “LLMs are unethical.” And the list goes on.
In the first part of this series, I described the most important lesson I learned while building a local AI storyteller:
A good LLM application is not a clever prompt. It is software architecture around a probabilistic component.
That sounds reassuringly architectural.
It also leaves one small question:
What exactly are we building around?
I wanted to understand what happens when you stop treating an LLM as a chatbot and start treating it as a component in a software system.
So I built a local AI storyteller using a local LLM through an OpenAI-compatible API.
