Category: AI
You are here if AI showed up in your job and the names on the screen do not match the buttons. This category is practical. It is not a model-release calendar, and it is not one lesson pasted under a new product name. The series split the pile so a Claude post and a ChatGPT post can teach different work.
Everyday paths are for a person with no account yet, or a person whose chat forgot a file: setup, prompting, memory, agents, safety, and which product fits a job. Product paths stay on one tool: Claude, ChatGPT, Gemini, or Grok, from a first login to the surface you should not open. Open-weight paths are Llama, DeepSeek, Qwen, Kimi, and GLM: what the name refers to, and when a normal paid chat is the easier tool. Engineering paths are for running a model, retrieving from your own files, and fine-tuning. Several of those hubs are still waiting on a first live part, and the hub page says so.
Where to start: no account yet, use AI setup from zero. You already pay for one product, open that product’s series and use the first part. You want the idea before the brand, use Practical AI. You want every series in order, use Learn and the AI tracks.
What are large language models (LLMs), and what are they good for at work?
Large language models draft text by predicting tokens at scale. Plain definitions, analytics use cases, grounding with retrieval, and a review habit so polished answers do not become…
