Game Mechanics as Product Mechanics: Lessons from Run and Jump

Product teams often study games for gamification ideas, but they usually take the wrong lesson. They copy points, badges, leaderboards, or streaks. Peter McDonald’s Run and Jump points to a more useful lesson: mechanics create meaning. The 2D platformer is powerful not because it adds rewards on top of activity, but because running, jumping, space, enemies, and collectibles form a coherent experience language.

The basic formula is simple: an avatar runs right, jumps, collects things, avoids enemies, and reaches the end of a level. Beneath that simplicity are emotions, attachments, worlds, and ideologies. The genre’s long life cannot be explained only by technical simplicity or nostalgia. We need to understand the elements inside the experience.

Every digital product has mechanics. A workflow tool has approvals, queues, notifications, and escalations. An AI writing assistant has prompts, generations, edits, and regenerations. A data platform has filters, dashboards, alerts, and drill-downs. These mechanics shape how users behave and what they believe the product is for.

The key product question is not “How do we gamify this?” but “What do our mechanics mean?” An AI assistant that automatically replaces user text creates a different meaning from one that suggests alternatives side by side. A predictive maintenance tool that marks equipment red without explanation creates a different meaning from one that shows signals and confidence.

Meaningful obstacles

Platformers also highlight movement and space. The organization of horizontal and vertical space affects how players understand possibility, danger, and progress. In business software, information architecture plays a similar role. What is visible first? What is hidden? Where can users go next? What feels like progress? What feels like a dead end?

Enemies and obstacles are another useful analogy. In enterprise software, friction can be harmful, but some friction is necessary. Approval gates, confirmation dialogs, explainability prompts, and human review steps may slow users down, but they can create safety and trust. The goal is not to remove every obstacle. The goal is to design meaningful obstacles.

For AI products, this matters because user agency is fragile. If automation takes over too aggressively, users may disengage or distrust the system. If the product gives users clear control loops, they can develop mastery. Good AI UX should feel less like a black box and more like a well-designed platformer: clear rules, meaningful feedback, recoverable mistakes, and satisfying progress.

Product mechanics are strategy. Before adding gamification, analyze the existing mechanics of work. Then design interactions that support the desired meaning: confidence, learning, speed, safety, creativity, or accountability.