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Overview

Unlock the full potential of Tempo with these tried-and-tested prompting techniques. These methods, drawn from our team’s experiences and user insights, can help you guide the AI to produce more precise and impactful results.

What is prompting?

Prompting is the process of giving written instructions to the AI to shape your project. Think of it as an interactive conversation—your prompts guide the AI to build or refine specific aspects of your design. Since Tempo utilizes advanced language models, the way you frame your requests can significantly influence the output. Taking time to craft clear, detailed prompts ensures you achieve optimal results.

Use your Mouse to Guide AI

One of Tempos’ standout features is the ability to click directly on individual components within the Canvas. This tells the AI exactly which element you’d like to update, and your selection appears in the chat to ensure clarity.

Prompting strategies

Below are a range of techniques to help you achieve the best results. These approaches are flexible—experiment with them and combine methods to suit your project’s needs.

Setting the Scene with Context

Providing relevant background information helps the AI better understand your requirements before diving into specifics. Example Prompt:

Incremental prompting

Instead of overwhelming the AI with a large, complex task, break it into smaller, manageable steps. Incremental instructions often yield better, more accurate results. Instead of: “Create a CRM app with authentication,Google Sheets export, and data enrichment.” Try these prompts sequentially:

Image Prompts

Tempo supports uploading images to guide the AI. Whether it’s a design layout or a wireframe, adding detailed instructions alongside visuals can enhance results. Detailed Visual Prompt

Avoid Vague Prompts

Vague instructions can lead to subpar results. Being specific and thorough helps the AI deliver what you envision. Avoid “Build a form” Instead use:

Prompt with constraints

Constraints can help focus the AI’s attention on what’s most important and avoid unnecessary complexity. Example with Constraints:

Fixing Errors with Prompts

When problems arise, the AI is more likely to fix them if you describe the issue in detail. Avoid: “The project is broken. Fix it.” Better:
For more detailed documentation, refer to Prompting Best Practices