Prompting and interaction
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.
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.
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.
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.
Progressive Disclosure
Progressive disclosure reveals AI output in layers: summary first, details on expand, advanced controls only when needed.
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.
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.
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.