Workplace AI reference
How AI Models Work in Plain English
Large language models are pattern engines trained on large amounts of text and other data. They do not know your workplace by default; they respond to the context and instructions you provide.
The practical model mental model
For workplace training, the most useful mental model is simple: an AI tool predicts a useful next response based on your prompt, the conversation, its training, and any connected tools it is allowed to use.
- The prompt tells the model the task, role, source material, constraints, and output shape.
- Context reduces guessing by giving the model the facts it should use.
- Examples show the model what a good answer looks like.
- Review catches missing facts, invented details, tone issues, policy concerns, and risky recommendations.
Why AI can sound right while being wrong
AI tools are built to produce fluent responses. Fluency is not the same as accuracy. Training should teach users to ask what the model used, what it assumed, what it could not know, and what a human should verify.
- Ask the model to label assumptions and missing information.
- Keep source material visible while reviewing the answer.
- Use primary sources for policy, legal, financial, medical, safety, or technical claims.
- Route higher-risk work through the correct human approval path.