AI UX Prompting and Interaction Glossary
How users and products instruct models, and how small wording changes shape outputs in chat, copilots, and agents.
8 terms
- Prompting and interaction
Chain of Thought
Chain of thought (CoT) is a prompting approach where the model shows intermediate reasoning steps before the final answer.
- Prompting and interaction
Context Assembly
Context assembly is how a product builds the full prompt stack before send: system rules, @-mentioned files, retrieved docs, memory, and the user’s message combined into one model request.
- Prompting and interaction
Few-Shot Prompting
Few-shot prompting includes a small number of example input/output pairs in the prompt so the model mimics your format, tone, or decision style.
- Prompting and interaction
Multimodal Input
Multimodal input lets users combine text with images, audio, video, or files in one request so the model can reason across media types.
- Prompting and interaction
Progressive Disclosure
Progressive disclosure reveals AI output in layers: summary first, details on expand, advanced controls only when needed.
- Prompting and interaction
Prompt
A prompt is the instruction or question you give an AI model: the user message, template, or form that tells it what to do.
- Prompting and interaction
System Prompt
A system prompt is the hidden instruction layer that defines the AI’s role, rules, tone, and boundaries before any user message appears.
- Prompting and interaction
Zero-Shot Prompting
Zero-shot prompting means asking the model to perform a task with instructions only, with no examples of desired input/output pairs.