This is the game mat design I chose for Reactor 21. The mat was created with the AI generated image as the backdrop, and the grid/text/mat sections were set up by me in Photoshop CC.


design courses, syllabi, schedules, resources and policies
The process of developing the graphics was AI guided, mostly because illustration is more of a weakness than a strength to me, and I couldn’t find a photo showing what I was looking for.
Unless stated otherwise, any AI image generation was done in ChatGPT.
I started by generating a reactor image that I could use as the base of the design, with both a normal and ‘post-apocalyptic’ vibe…


I decided to go with the post-apocalyptic vibe. This was the prompt that generated the image:
Prompt used:
A striking daytime photo captures a nuclear power plant beneath a brooding sky, with thick black smoke rising from two towering cooling structures. The scene is punctuated by a smooth-surfaced reactor building, a lattice communication tower, and flashing emergency vehicles, all framed by grim, muted grays and occasional vivid reds, enhancing the dramatic atmosphere of the image.
I knew I had to design red, yellow, and green markers for the gameplay, and I ended up with this AI graphic:

Prompt used:
Three small, glossy plastic game tokens arranged in a row on a dark matte background. Each token is embossed with a simple symbol: a red token with a nuclear hazard icon, a yellow token with an exclamation warning icon, and a green token with a leaf eco-symbol. Soft, even studio lighting, clean shadows, photorealistic texture, top-down view.
I decided that the box should look like the dark reactor photo wrapped around the box. I also included a deck of cards with the reactor wrapped around the box.

Prompt:
A realistic product-photography scene on a solid black background. A large rectangular board game box titled “REACTOR 21” lies flat on the table. The box uses a military stencil font for all text. The artwork on the box is a dark, dramatic image of a nuclear power plant with cooling towers emitting thick black smoke and emergency vehicles below. The box is 18 inches long and dominates the left side of the frame.
To the right of the box is a standard-sized Bicycle-style deck of playing cards, standing upright. The deck has the same nuclear-reactor artwork framed inside the classic Bicycle-style layout, but with the title “REACTOR 21” in a military stencil font instead of the Bicycle logo. White borders and the familiar tuck-box shape are clearly visible.
In front of the box are multiple small game tokens, each exactly 0.5 inches in diameter, arranged closely together: four red tokens embossed with a radiation symbol, six yellow tokens embossed with an exclamation point, and five green tokens embossed with a leaf symbol. The tokens are thick like premium bingo chips. All tokens are proportionally tiny compared to the 18-inch box. Lighting is soft, even, and neutral to ensure the red, yellow, and green tokens are equally visible without glare.
The overall image has a dramatic but clean studio aesthetic, with sharp details, accurate object proportions, and a cohesive, cinematic tone.
The actual game board was composed mostly in Photoshop, and it will get a separate post as it was a completely different process.
Reactor 21 changed quite a bit as I tested different versions of it. The basic idea was always there—two players trying to keep a failing reactor stable—but it took some back-and-forth to figure out what actually made the game interesting. Early versions had the right intention, but some of the mechanics didn’t create the amount of teamwork or pressure I wanted. The game felt like it needed a bit more structure around how instability spreads, what happens during a meltdown, and how the players recover from setbacks.
Most of the improvements came from simply seeing how people reacted to certain moments in the game. Some rules felt too loose, and others were a little unclear in how they resolved. Adding the Nuclear Waste pile, tightening the meltdown rules, and clarifying how cards move between piles helped everything feel more intentional. The goal was always to keep the experience focused on communication and shared decision-making, and those adjustments moved the game in that direction.
During all of this, ChatGPT was helpful for keeping things organized. Any time I adjusted a rule or tried a different way of handling a reactor event, I used ChatGPT to help rewrite the sections cleanly, make sure the terminology stayed consistent, and compare versions so nothing got lost. It also made it easier to step back and look at each revision as a whole instead of just patching small pieces. The mechanics themselves still came from testing and intuition, but having a tool to structure everything made the development process a lot smoother.
Reactor 21 ended up feeling more balanced and readable because of that steady cycle of testing, revising, and tightening the language around the rules.
The three acts of the game are as follows:
Act 1 – Getting your footing
The game starts off pretty gentle. You’re drawing cards, placing them where they fit, and getting a feel for how the reactors behave. Most cards go somewhere without much trouble, and the token tracks are empty, so nothing feels dangerous yet. This is where you learn the rhythm: keep totals tight, stabilize when you can, don’t waste options.
Act II – Things start heating up
Now the reactors are filling up, and suddenly every card matters. A placement that was easy earlier now feels risky. You’re choosing between Instability and Meltdown more often, and both choices actually hurt. The Nuclear Waste Pile kicks in and you start to feel the deck thinning out. This is where the team talks things through, plans moves, and tries to stay one step ahead of the system.
Act III – Hold it all together
By the end, everything’s tense. One bad draw can end the whole run, and every card feels like it might be the last piece you need—or the thing that breaks the grid. You’re trying to lock down those last stabilizations before either track fills up. When the final reactor hits 21, it feels earned; if the system blows, it’s usually by a hair.
(Final thought created with the assistance of AI, using my input)
As I refined A Game About Colors, More or Less, the color system became one of the most important aspects of the design. Early versions relied on fully saturated colors, which made the comparisons visually clear and, in many cases, too easy. During testing, it became obvious that players could identify the stronger or weaker color channels with very little effort, which reduced the level of deduction the game was meant to encourage.
To address this, I shifted the palette to include added black (K) values between 30% and 70%. Lowering saturation created a more subtle, more challenging set of swatches. Colors that once felt predictable became more ambiguous, and players had to make more thoughtful evaluations based on small differences, rather than relying on obvious saturation cues. This adjustment aligned the visual experience more closely with the intentions of the mechanics.
Throughout the development process, ChatGPT was used as a collaborative tool to help build, refine, and organize the rule set. It played a role in structuring the language of the rules, maintaining consistency across versions, documenting changes, and evaluating how each update affected clarity and player experience. It was also useful for keeping a clean version history and ensuring that revisions—such as the shift to a reduced-saturation deck—were incorporated accurately and consistently. The core design decisions remained my own, but ChatGPT helped make the documentation process more efficient and reliable.
This combination of iterative testing and structured rule development resulted in a color system that better supports the game’s deductive, perception-based gameplay.
Act 1 – Getting a feel for the deck’s color language
Early on, players are mostly just getting acquainted with how the deck moves. They make a guess, flip the card, and start noticing which kinds of shifts catch their eye — a bump in brightness, a little pull toward red, or a change in saturation that didn’t seem obvious at first. It’s basically a warm-up for the eyes, where players start realizing that the game isn’t about naming colors; it’s about noticing how they behave.
Act 2 – Learning what actually matters in a swatch
Once everyone has a few cards in front of them, they naturally start leaning on simple bits of color theory — whether they mean to or not. Some players pay attention to value first, because brightness jumps out. Some start tracking saturation because muted colors hide shifts better. Others zero in on hue and notice how small moves between neighbors (like teal to blue-green) feel trickier than big jumps. This is where players start building their own internal system for judging the cards, one clue at a time.
Act III – Stay consistent with the system you’ve built
The game doesn’t suddenly get more intense toward the end — it just asks you to stick with whatever approach you’ve developed. By this point, players have their own way of reading the swatches, and the last part of the game is about trusting that instinct. Maybe you’re watching for low-saturation curveballs, or maybe you’re checking how the brightness sits against the last few cards you saw. It’s steady, calm decision-making — more about consistency than pressure — and the satisfaction comes from seeing how well your eye held up across the whole run.
Race to 65 didn’t change too dramatically as it developed. Most of the core structure was there from the beginning; the main work was just tightening the rules and making sure everything felt clear and consistent. A few of the early versions had small gaps or places where players weren’t totally sure how to handle certain situations, so the updates were mostly about smoothing out those rough edges.
The biggest adjustments were clarifying how tiles flip, how players advance toward the target number, and how the end-of-game callout works. These weren’t major changes, but they helped the game run more cleanly and made the turns feel more intentional without adding complexity.
ChatGPT was helpful mostly on the documentation side—rewriting sections for clarity, keeping the terminology consistent, and making sure each version lined up with the previous one. The game itself didn’t go through big mechanical shifts, but having support to organize the rules and clean up the language made the whole process easier.
The three acts of the game are:
Act I – Getting started
The game opens in a pretty relaxed way. Players start flipping tiles, getting a feel for their numbers, and easing into the rhythm. There’s no pressure yet—just settling in and seeing how the early moves shape things.
Act II – Building toward the goal
As the game moves along, players start paying closer attention to their totals and making more thoughtful choices. It’s still simple and approachable, but you do get that feeling of trying to outpace the hourglass a little. Small decisions start to matter, and players begin watching how close everyone is getting.
Act III – Making the final call
The endgame comes into focus once players approach the target number. At this point, the game turns into a light race against time and each other—just trying to hit the number cleanly without going over. It’s not intense or heavy; it’s more like that moment in a puzzle where you can feel you’re close, and you’re trying to line everything up just right before someone else finishes.
2 person game (Kaelin and Madison)
Rules:
Objective:
Be the first to finish your stack of ice cream dishes.
Materials:
1 deck of 60 cards
Setup:
Shuffle the Deck and deal each player 30 cards randomly
Gameplay:
Flip over two and place in between your deck of cards.
There are no “turns”. The players race to be the first to finish their deck by rapidly matching either the flavor, type of dish or number of dishes on their card to the respective ones on EITHER of the cards that are flipped up in the middle.
As the game progresses, obviously the cards will change based on what cards the players place on top. Keep placing matching cards as fast as you can, whenever you can.
Winning:
The game ends when one player finishes their stack. That player is the winner. Hooray!
Changes made:
There were edits made to the rules during prototyping to specify the simple mechanics – we had a moment that somehow the game was played but completely wrong so we tightened the wording
Changes TO make:
We’re going to tweak some of the coloring on the card to be more consistent – the blue ice cream cups threw a few people off on what type

Thoughts about Playtesting:
Most people understood the concept while one group totally didn’t so that was interesting – we clarified the rules so all people would understand. It’s interesting to see how people interpret rules or completely don’t read them when they think they know how it works.
Game Card Images:


Group: Maria Wack, Zach Dunlap