Looking back at the early ideas for my own project, I found it difficult for me to get around McPixel. It’s not because of how complex it is by design, but because it almost fully fulfills my original idea of “pure entertainment”: no clear meaning, no stable logic, and still keeping players interested. The research on McPixel was more of a look back than an inspiration—trying to understand why I was drawn to this way of designing in the first place, and where that attraction came from.

In McPixel, failure does not assume a punitive function, but is designed as a watchable, experiential content. Each choice quickly leads to a clear outcome, regardless of whether that outcome is considered “successful” or not. This design frees failure from “mistakes”, making it a source of curiosity.

Because of this, even if players have successfully cleared the level, they will still actively return to the game to try those “failed” options, just to see what else happens. Here, the motivation to play is no longer to achieve a goal, but to explore all possible outcomes.

From a purely entertainment standpoint, the McPixel’s appeal does not come from complex systems or narratives, but from extreme compression of the cost of failure. Players are constantly making choices in a very short period of time, and even if they lose, there is little frustration. This low-risk, high-feedback structure encourages players to experiment freely without understanding or mastering any rules.

At the same time, the game deliberately abandons stable causal logic, so that players no longer try to find the “right solution”, but focus on the accident and absurdity themselves. This design shifts the entertainment experience from “understanding systems” to “accepting uncertainty,” allowing games to remain engaging without providing meaning.

In McPixel, players are also faced with a set of options that cover different levels of intuition, and the system does not indicate in advance which one is “recognized”. This design made me realize that the reason why players choose those options that look normal is not induced, but because these options are inherently within the realm of human thinking.

Looking back at the early options designs, I realized that there was a non-intentional similarity between them and the McPixel. I didn’t explicitly distinguish between “normal” or “abnormal” options at first, but allowed different knee-jerk reactions to exist side by side. For example, when dealing with the same problem, the system presents both obviously unreasonable options and what seems reasonable, or even the most correct. This side-by-side is not intended to create inversions or mislead players, but rather a direct modeling of a real thinking path. When people face problems, they often think of absurd and reasonable possibilities at the same time, rather than completing the screening at the beginning.

This observation has had a lasting impact on my project. Rather than guiding players to make specific choices by design, I am more concerned about whether the system can accommodate and respond to these real and chaotic thinking paths. These seemingly reasonable options do not mean that they will be affirmed by the system, but rather that players will gradually realize that the system may not interpret their behavior consistently after making a serious judgment.