.png)
3 months ago
4
This is a literacy course aimed at onboarding someone with a holistic framework for understanding and leveraging AI. It’s not meant to be comprehensive, nor does it explore the many advanced prompting techniques. That can be pursued independently.
Rather, the reader has used a chatbot, is perhaps technical, but is not in the field of AI. He knows what a prompt is.
The course ascends 3 stages:
Each tier redefines what AI is in relation to you. In 101, it’s a tool—a kind of Iron Man suit that boosts your speed and strength when wielded deliberately. In 201, it becomes something more pliable: a teammate who can learn your preferences, adapt to your feedback, and help shape real work alongside you. At the 301 level, AI becomes infrastructure. It’s not a single assistant—it’s a small team in disguise. You plug it into multiple roles across the system: one AI drafts content, another refines structure and tone, another prepares it for final output—formatting, tagging, and staging it for publication. Each wears a different hat, but together they form a cohesive unit. What emerges isn’t just efficiency—it’s the shape of a new kind of team, built from language, logic, and delegation.
Though I am a professional developer, I’m not an AI expert. What you’ll find here comes after putting a colossal effort into absorbing beginner and intermediate materials. It attempts to make sense of it in practical terms, to bring others up to a similar understanding, and build on fundamentals that hold up across use cases.
In the process, I’ve started to see just how remarkable LLMs can be. Some of the use cases are surprising because they challenge how we work and think. What’s been more surprising, though, is how that spark doesn’t always catch. That’s part of why I wrote this. I wanted to help others see why I find them so compelling.
You’ll see ChatGPT referenced throughout, since it’s a widely accessible and concrete entry point. But this isn’t about one tool. The ideas here are meant to be platform-agnostic and useful no matter which system or interface you’re using. The references to ChatGPT are there to help make things easier to imagine. The underlying principles apply broadly — because in the modern era, AI often means anything built on the new underlying primitive: the large language model, or LLM.
This work doesn’t engage the ethical questions surrounding AI. Its focus is strictly utilitarian.
This is a work in progress. Thanks for taking the time to read it. I hope it proves useful. Of course, feedback is welcome.
Content authored by Mario T. Lanza. Shared with permission from the Unified Judicial System of Pennsylvania.
