Get Better AI Outputs with This Multiple Choice Technique

Learn a universal multiple-choice prompting strategy for getting better outputs from AI models while reducing unhelpful context and token usage. You’ll also learn the basics of tokens and context windows, then use the technique to produce clearer AI-generated concepts.

• Marketers and designers who generate lots of images
• People who want to prompt better
• Anyone frustrated with lengthy AI chats that seem to go in circles

You’ll build a reusable multiple-choice interview prompt structure that helps an AI gather useful context before producing outputs. In the example workflow, you’ll use it to generate four distinct logo concepts.

• A goal, task, and next-steps prompt structure
• A multiple-choice AI interview for gathering context
• Four distinct concept directions generated from the interview answers
• A token-saving grid of logo concept options

• Access to any chat-based AI or AI image generator
• For this tutorial specifically: Nano Banana Pro in AI Studio and Google’s NotebookLM

• For more complex workflows like email copy ideas or blog post outlines, copy and paste each concept into a fresh chat and refine it there.
• If the interview method gives you strong results, export and reuse the context by asking the AI to extract the context as system instructions in markdown.