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Article 061 · Part 6
Explore Games, 3D Design, and Interactive Stories
Turn an attractive idea into an interaction someone can actually complete.
By Randy Salars · Published
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Turn an attractive idea into an interaction someone can actually complete.
An AI assistant proposes a floating library, a talking fox, and doors that open when a player solves riddles. The description sounds wonderful. Then someone asks a simple question: what happens when the player chooses the wrong door?
The answer is missing. So are the rules for collecting clues, retrying a choice, and recognizing the end of the game.
Creative AI can help you invent worlds quickly. Making an interactive experience requires a second kind of work: deciding exactly how the world responds. You can learn that skill with paper, a pencil, and a few cards before choosing a game engine or creating a single 3D object.
Start with one player goal
Write the experience in a sentence containing a person, an action, and a result. “A visitor chooses the correct storage drawer by reading two clues” is a workable starting point. “An immersive adventure about knowledge” still leaves most design decisions unresolved.
For this article, use an original fictional game called The Lost Seed. The player is helping an imaginary archive return a seed envelope to its drawer. This is a logic puzzle, not botanical guidance.
The brief is deliberately small: one player, three labeled drawers, two visible clue cards, no timer, and a session intended to last a few minutes. The goal is to choose the drawer matching both clues. The player can read the instructions, inspect the clues, choose a drawer, and restart after success.
Choose your first medium based on the question you want to answer. Paper can reveal whether the clues make sense. A clickable prototype can reveal whether people notice buttons. A game engine can test movement, collision, and performance. A rendered video can demonstrate an intended appearance, but it cannot establish that the interaction works.
Separate the pieces of production
The word “asset” can hide several different deliverables. Keep their roles explicit.
| Deliverable | What it can establish | What remains unproved |
|---|---|---|
| Concept image | Intended appearance and atmosphere | Working geometry or interaction |
| Story outline | Characters, stakes, and possible events | Complete branching behavior |
| 3D mesh | Object shape in three dimensions | Suitable materials, collision, or performance |
| Script | Proposed instructions for the software | Correct execution in the project |
| Playable prototype | An implemented interaction | Enjoyment, accessibility, or production readiness |
A picture of a drawer is not a drawer the player can open. A mesh that looks correct in a modeling application might need scale adjustments, materials, and collision setup in the destination engine. A generated script may reference an object that does not exist.
For readers moving into an engine, Godot’s official introductory 2D tutorial walks through building a complete small game and explains the project structure. Use documentation matching your installed version when translating a paper design into software. Godot: Your first 2D game.
Define the rules before requesting dialogue
Here is the entire puzzle specification for The Lost Seed.
The drawers have these labels:
| Drawer | Symbol | Storage label |
|---|---|---|
| A | Circle | Dry |
| B | Triangle | Dry |
| C | Triangle | Damp |
Clue one says: “The envelope belongs in a drawer marked with a triangle.” Clue two says: “Its record specifies dry storage.” The correct choice is B because it satisfies both conditions.
The player starts in the choosing state. Choosing A displays: “This drawer is dry, but its symbol does not match.” Choosing C displays: “The symbol matches, but the storage label does not.” Either choice leaves the player in the choosing state. Choosing B displays: “Both clues match. The envelope is home.” The game then enters the complete state.
In the complete state, additional drawer choices do nothing; a clearly labeled Restart action returns to the initial state. These rules prevent a late click from replacing the success message with an error.
Notice what the design leaves out: scores, lives, random clues, inventory, movement, and penalties. Those could become useful later. They are unnecessary for testing this first interaction.
Ask AI to inspect the design
A useful request gives the assistant something specific to criticize:
Review this small puzzle specification. List the player’s available actions in each state, the feedback for each action, and the next state. Check whether there is exactly one correct drawer and whether every unsuccessful choice permits a retry. Suggest two clearer instruction options. Do not add mechanics or claim that users have tested the game.
Audience: first-time players. Medium: paper prototype. Rules and drawer table: [insert specification].
The output should expose missing decisions. If AI proposes a “hint button,” ask what the hint says and whether it reveals the answer. If it proposes a timer, ask what user need the timer serves. An appealing addition deserves the same scrutiny as the original idea.
For an interactive story, replace drawers with decisions and track what each decision changes. If a character gives away a key in one branch, a later branch cannot assume the key remains in the player’s pocket. Maintain a small state sheet: key held, promise made, location visited. Branching prose needs continuity rules as much as a game needs movement rules.
Build the paper version
Create an instruction card, two clue cards, three drawer cards, and three feedback cards. Keep both clues visible. Write “Choose the drawer that matches both clues” above the drawer cards. Put a Restart card beside the success feedback.
One person operates the paper prototype by revealing the feedback associated with the player’s choice. The operator follows the written rules, without adding helpful explanations. This preserves the distinction between a working design and a creator rescuing a confused player.
Walk through A, C, B, and Restart yourself to catch missing materials. This is a designer check, not a user test. Then invite someone unfamiliar with the puzzle to try it. Ask them to describe what they are trying to do, and record where the instructions fail.
A test log needs only the attempt, observed action, exact confusion, and proposed revision. “Player selected A, reread the triangle clue, and then selected B” is useful. “Player loved it” tells you little unless they actually said so, and even then it does not show which design choice worked.
Check the digital and 3D versions differently
When you move to digital production, give each asset an acceptance condition. For a drawer model, specify intended dimensions, the side that faces the camera, the point around which it opens, and the destination format. Check the model in the destination application; an attractive preview is insufficient.
For a game scene, inspect whether buttons can be reached with the intended controls, whether text remains readable, and whether feedback is communicated without relying only on color or sound. Measure performance on the target device using the actual scene. Do not copy an arbitrary polygon limit from AI and treat it as a universal standard.
Keep an asset register identifying creator, source, permission terms, modifications, and attribution obligations. Software licensing and asset licensing are separate questions. Godot’s import documentation is a starting point for understanding the engine’s 3D import workflow; it does not certify a particular asset’s license or suitability. Godot: Importing 3D scenes.
For students: show the design decisions
A game project can connect writing, mathematics, art, and computing. Choose one learning objective so the project does not become an unmanageable collection of features.
A writing student might document a branching conversation and explain how choices affect characterization. A mathematics student might prove that the two clues identify exactly one drawer. A computing student might implement the state transitions and test repeated input. An art student might explain how labels and shapes support recognition.
Follow the assignment’s AI rules and identify what you generated, changed, and tested. Include a failed design and the revision it prompted. An honest prototype record is stronger evidence of learning than a polished screenshot accompanied by unsupported claims of functionality.
Practice: build and test one interaction
Make The Lost Seed or another equally small original scene. Write all rules before building it. Ask AI to identify ambiguity, then decide which suggestions to accept. Prepare a paper or simple digital prototype and run a session with a new user if one is available.
If you cannot arrange a session, submit the prototype and a test plan labeled not yet tested. Do not fill the observation table with imagined behavior.
Completion check: A new user can identify the goal and complete the interaction, unsuccessful choices have defined feedback, and your record distinguishes concepts, implemented features, and observed results. If no user session occurred, that final usability check remains open.
For a stretch exercise, add one mechanic—such as an optional hint—and compare confusion and completion with the earlier version. Keep the original so you can determine whether the added complexity earned its place.
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