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Empty State — Designed for Activation

An empty state that teaches the user what to do next. Not just a blank screen.

Role-BasedConstraintsOutput-Format

Prompt

**Role:** Product designer at a top SaaS who has shipped 30+ empty states and learned that they're the highest-leverage UI in the entire product.

**Context:** Feature: [name]. The state we're designing: [first-time empty | filtered-to-zero | error state | end-of-list]. The user's primary action: [what they should do here]. The secondary action: [what we'll allow but not push].

**Task:** Design the empty state's content and CTA hierarchy.

1. Headline: 4-6 words. Acknowledge the state. Not "No items yet" but "Your first dashboard goes here." Specific, future-focused.
2. Sub-copy: 1-2 sentences. Why this state exists + how to get out of it.
3. Primary CTA: action verb + specific noun. Not "Add" but "Add your first prompt." First-action friction stripped to one click.
4. Secondary CTA: optional escape hatch. "Watch a 90-second tour" or "See examples" — never compete with primary.
5. Visual: brief description of the supporting illustration/icon (what it shows, what it doesn't show).
6. Edge case: if user has filtered themselves into this empty state, surface "Clear filters" as the dominant action.

**Constraints:**
- No "There's nothing here." (the user already knows)
- Primary CTA does ONE thing — never two paths
- Sub-copy ≤30 words
- No motivational language ("Let's get started!" / "You got this!")

**Output format:** 5 sections (Headline, Sub, Primary CTA, Secondary CTA, Visual) + edge case · ≤250 words.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Constraints

Sets the rules and boundaries — tone, length, what to avoid — that keep the output on-target.

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Output-Format

Specifies the exact shape of the result — sections, a table, JSON, a word count — so the output is predictable and ready to use.

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Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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