Case study

SquadBrain: making roster memorization feel like a competitive game.

A mobile product build that combines practice loops, quick-match competition, achievements, ELO-style movement, and validation-sensitive game logic.

Live demo GitHub repo

SurfaceMobile practice loop

LogicAdaptive card priority

GuardrailCompetitive result validation

Proof25 tests + CI

Product loop debugger

Not just a demo screen — a loop with rules behind it.

SquadBrain is presented as a product system: fast mobile interaction, adaptive practice priority, match selection, and validated competition outcomes.

01Practice signals: due state, misses, stability, prompt mix.

02Match signals: rating gap, wait time, team overlap.

03Trust boundary: recompute score before rank movement.

Code pathAdaptive practicePriority is explained by state, not random cards. GuardrailResult validationCompetitive submissions are recomputed and risk-flagged. Proof98.3% coverageCoverage summary for the public example suite. Decision trailADRsTradeoffs around local play, competition, and recomputation.

The problem

Roster knowledge is usually treated like static trivia. The product opportunity was to make memorization repeatable: short rounds, visible progress, competition, rank movement, and reasons to return.

System decisions

Local-first gameplay

Fast mobile interactions stay local so the practice loop never feels blocked by network latency.

Trusted competition boundary

Competitive submissions are recomputed and risk-flagged before ranking updates.

Adaptive practice

Practice priority uses due state, misses, stability, recent exposure, and prompt mix rather than random questions.

Code worth inspecting

adaptive-practice.ts — prioritizes practice cards and explains the reasons.
result-validation.ts — validates session submissions and risk-flags suspicious results.
matchmaking.ts — ranks same-team candidates by rating gap and wait time.
CI workflow — type-checks and runs the example test suite.

Capabilities demonstrated

Product UX plus competitive-system logic.

Mobile product sense, TypeScript organization, game-state modeling, ranking logic, validation boundaries, testing discipline, and the ability to package a consumer app for evaluation.