Prompt Builder — See Then Build

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Learning compounds → reinforcing loop → paper cutout → presentation visual.

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Learning compounds: a paper-cutout loop connecting Read, Apply, Reflect and Choose next — See Then Build generated example. One result does not establish repeatability across models or prompts.

Idea: use what you learn to guide your next attempt.
Explanation: a reinforcing loop makes the repeated relationship visible.
Style: cut-paper texture adds a tactile treatment while keeping labels and arrows clear.
Make: use the example in the builder, copy the prompt, then refine the result with your AI.

Check that every arrow says what you mean, the loop closes correctly, and the labels remain readable.

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Prompt used to generate this example

Use case: infographic-diagram.
Asset type: square presentation visual and worked example for a learning workflow.
Primary request: create an original finished paper-cutout diagram titled exactly "Learning compounds". Explain a repeating learning feedback loop through four clearly connected stages. The meaning of the diagram must drive the composition.
Composition: a perfectly square canvas with a warm cream paper background and generous margins. Put the title at the top in large, crisp, highly legible dark forest-green type. Below the title, arrange four distinct tactile paper-cutout stations around a large open square loop: upper left "Read", upper right "Apply", lower right "Reflect", lower left "Choose next". Four large unambiguous curved cut-paper arrows connect the stations CLOCKWISE, in this exact order: Read to Apply, Apply to Reflect, Reflect to Choose next, Choose next back to Read. All arrowheads must point in that correct direction. Keep the center quiet and open.
Visual meaning: Read shows a small open booklet with an orange bookmark; Apply shows two clearly interlocking cut-paper pieces being fitted together; Reflect shows a simple hand mirror with an abstract reflected mark; Choose next shows a branching path with one forward route highlighted. Use these as compact symbols; no humans, no tree, no book-with-tree subject. Keep the four icons subordinate to the clear stage labels and arrows.
Style/medium: photographed layered cut-paper construction, clean scissor-cut contours, visible paper fibers, shallow dimensional shadows, restrained tactile craft, polished editorial presentation. A coherent limited palette of deep forest green, muted leaf green, warm cream, and small burnt-orange accents. Use dark green labels on pale cream areas for strong accessible contrast. No tiny type, no decorative border, no dense background texture, no additional text.
Text (verbatim), each appears exactly once and correctly spelled: "Learning compounds", "Read", "Apply", "Reflect", "Choose next".
Constraints: keep every label horizontal and legible; provide ample space around every label; no overlapping arrows or text; four stages only; a closed clockwise loop; no numerical data or claims; no logos or watermark. All content remains inside the square with generous safe margins.

Generated 2026-09-12. This is the exact prompt for the pictured result; the builder creates an adapted prompt for your own idea.

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Create a 45–60 second explainer video that makes the following idea easy to understand.

Subject: How compounding turns small habits into big results
Audience: Curious professionals.

Features:
- Build 4–6 scenes, showing one cause-and-effect step at a time.
- Use short accurate labels, readable on a phone.
- End with the central mechanism and one useful application.

Use relevant context you actually know about me and my work. Do not invent personal details. Ask only for essential missing inputs; otherwise state reasonable assumptions and start.

Deliver: A scene-by-scene storyboard, voiceover script, visual directions, and first render if supported. Otherwise provide an editable implementation or production handoff with timing and asset prompts.

Include the tools and inputs needed, a short sequence of production steps, and checks for meaning, readability and factual accuracy.

Keep factual claims accurate and distinguish assumptions from supplied information. Optimize for clarity and usefulness. This is an adaptable See Then Build recipe, not a claim that a single prompt can reproduce an example exactly.

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