Juno

A one-button autorunner for 5-7 year-olds with learning minigames (similar teaching DNA to Word Tag). I owned preproduction design work and built a level generation proof of concept to enable fast content turnaround while keeping designers in control.

Quick Facts

• Role: Game Designer (preproduction owner)

• Context: Preproduction for new project

• Tools: Unity, C#, Excel, Confluence, Jira, Miro

• Status: Unreleased - project ended due to company bankruptcy (design package and tooling concept completed; later implementation work was done by others while I was on leave)

What I owned / delivered

• Progression systems: world map, levels awarding up to 3 stars, regions unlocked by star totals, and quickplay modes.

• Reward and economy systems: reward loop, currencies, pacing assumptions, and incentives designed for young players, short sessions, and daily play.

• Game mechanic design: autorunner/platformer mechanics and interaction rules supporting readable one-button play.

• Character controller design: feel targets and behavior definitions for one-button action platforming.

• Learning pacing design: rules for dynamically placing learning minigames (“Tagging Spots”) so pacing could be controlled by parents/teachers.

• Level generation tool (proof of concept): modular level generator designed for very fast level turnaround while keeping designers in control.

Context

• Player Goal: Run through short, playful obstacle sequences using one-button actions, then complete quick learning interactions at Tagging Spots - designed for ~6-year-olds with high clarity and low friction.

• Core Loop: Play a level → encounter Tagging Spots at a controlled pace → earn up to 3 stars → unlock new regions by star total → repeat, with quickplay modes for short sessions.

• What makes it distinct: This project was designed around a production reality: lots of levels, fast iteration, simple inputs without a simplistic experience. The core design challenge was building a system that could generate levels quickly while still letting level designers shape the experience intentionally.

Level Generation System (the core preproduction feature)

• Design Intent: Enable very fast turnaround per level while keeping level designers in control of pacing, mechanics, and difficulty - rather than generating “random” levels.

• How it Worked:

  • Modular authored pieces: predesigned level modules that fit together seamlessly.

  • Designer-facing rule controls: generation could be guided by rules such as:

    • target difficulty range

    • focus on specific mechanics

    • preferred module types or pacing patterns

  • Procedural Tagging Spots placement: learning minigames were placed by the system so parents/teachers could control pacing and distribution.

  • Dynamic theming: each module received an art pass so it could be reskinned to match a level theme (junkyard, beach, harbor, etc.).

• Optional Player-facing Idea: We discussed making generation player-facing: enter a seed (like your name) to generate a shareable level for classmates/friends.

Design goals

• One-button clarity and feel: a readable action platformer experience tuned for ~6-year-olds.

• Scalable progression: clear short-term wins (stars) and long-term goals (regions/modes) supporting repeat play.

• Content at speed, with intent: modular level generation that supports fast iteration without losing authored pacing.

• Learning pacing control: Tagging Spots placement rules that allow adults to shape curriculum cadence without breaking play flow.

Constraints

• Late-stage ownership in an established organization: this was preproduction intended to carry into production during my paternity leave, so designs had to be clear, structured, and implementable by the team without constant designer presence.

• Audience constraints: tuned for 5–7 year-olds: clarity, readability, and low frustration.

• Project discontinuation: the company bankruptcy ended development before a full production implementation.

Deliverables

• Progression spec (stars, regions, quickplay)

• Economy/reward model

• Level module taxonomy + tagging spot placement rules

• Level generation proof-of-concept prototype

• Preproduction design docs