Using AI

An AI product with its own chat surface that you go to and ask, handling many kinds of task rather than one.

AI built into a tool you already use, offering help in place rather than asking you to go somewhere else and describe the work.

A vendor's bundle of models, tools and controls sold as one thing to build on, as opposed to a single finished application.

A vendor's catalogue of available integrations, which is the practical answer to whether a tool will fit your existing stack.

The documented way an organisation writes, which is what an AI tool has to be given before its output can be consistent with everything else you publish.

A side panel where a draft sits and is edited in place, so a document is revised rather than rewritten in the chat.

The intermediate reasoning a model works through before giving its answer, sometimes shown to you as thinking.

The link or reference an AI answer offers as the source of a claim, which is only useful once you open it and check.

Letting an AI drive a screen the way a person would, clicking and typing in ordinary software that offers no other way in.

The amount of text a model can consider at once: your conversation, any documents you attach, and its own replies.

What a product keeps from your previous sessions, which decides both how much it remembers and how much of your work it stores.

A saved assistant set up once with its own instructions and files, then reused by a team, sold under a different name by each vendor.

A mode that spends minutes rather than seconds gathering and comparing sources, returning a written brief with references instead of a quick answer.

Showing a model two or three worked examples inside your request so it can match the pattern you want.

Attaching a document or image to a conversation so the AI can work from it, and the first point at which a data question arises.

Tying a model's answer to a specific, checkable source: a search result, your uploaded document, a database record.

When a model states something false as if it were certain: an invented citation, a wrong date, a plausible-sounding statistic.

A feature that lets an assistant carry facts about you across separate conversations, rather than starting blank every time.

What you type to an AI assistant: the request plus any context you include.

The practice of writing and refining requests to get reliable results, which in practice looks more like briefing well than like engineering.

The hidden working a reasoning model produces on its way to an answer, which you usually pay for and count against limits without ever seeing it.

Asking for another attempt at the same request, which produces a different answer because the model does not work deterministically.

Standing instructions given to a model before your conversation starts, usually by the tool's developer: its role, tone, rules and boundaries.

A setting that controls how predictable a model's output is.

The unit models actually read and write: a short chunk of text, roughly three-quarters of an English word on average.

A record of a document's earlier states, which matters more once drafts are produced quickly enough that the previous one is easy to lose.

A loose label for building software by describing what you want and accepting the result, with little review of the code produced.

Asking for something with no worked examples at all, relying on what the model already learnt.