
何が起きたか
お笑い芸人・野田クリスタルが Google の Gemini を使って開発した「ペットカードジェネレーター」が 2025年12月16日の公開初日に130万アクセス、カード生成40万枚超を記録しましたが、AI利用料の高騰により一時停止。約半年後、レイドバトルやカードコレクション機能を備えた大型リニューアル版「うちのこカード伝説」として復活しました。
なぜ重要か
AI生成の不確実性と高コストという課題に直面しながらも、Gemini の Canvas 機能とGoogle Cloud を活用して、「毎回違うストーリーを展開するバトル」や「複数のペットが1枚に収まるカード報酬」など、従来のゲーム開発では実現困難な体験を実装しました。インディーゲーム開発の現場でAIの限界に向き合いながら課題を解決する実例として、AI導入を検討する他の開発者やビジネス関係者にとって参考になる可能性があります。
注目点
リニューアルは Google が Canvas 上で最新モデルを無料提供できるようになったことで初めて可能になりました。野田は「バズるほど赤字」だった時点では従量課金の最新モデルを使用していましたが、モデルのバージョンを下げて運営した後、高速生成が無料で使えるようになるまで待ちました。現在は制限なく何回でもカード生成でき、バトル中のペット褒め実況も実装されています。
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The Pet Card Generator's journey reflects a collision between viral success and the economics of AI inference. On launch day, 1.3 million accesses and 400,000+ card generations created a cost crisis: deploying a state-of-the-art generative model on a pay-per-use basis made Noda's operation proportionally more expensive the more users engaged with it. This is not a small-scale indie problem but a structural challenge for any AI-powered service relying on external model inference. Rather than abandoning the project, Noda's team made a deliberate gamble: they downgraded to a cheaper model to keep the service live and waited for the AI industry to move toward cheaper or free access to frontier capabilities. That bet paid off when Google began offering Canvas-based services with free access to advanced Gemini models, finally allowing the team to ship the experience they envisioned.
The relaunched game pushes Canvas—Google's no-code interface for building AI applications—to its limits. Noda noted that few developers have driven Canvas so far. However, Canvas alone lacked backend capacity for features like card collections and user data persistence, so the team layered Google Cloud Run Functions and Cloud Storage underneath to handle orchestration and storage. This hybrid architecture—lightweight frontend with heavy-lifting backend—mirrors how many production AI applications actually work in practice: the generative model and natural language understanding sit at the user-facing layer, while deterministic systems handle state and data integrity.
The most striking design choice is the raid battle mechanic, where AI reads the card's properties and improvises a unique story and outcome each time. This sacrifices the stability of traditional turn-based systems for expressiveness and replayability. Noda's framing—"indieGame developer" willing to accept "weird bugs" as a price of experimentation—captures why this kind of creative risk-taking is often easier in scrappy, small-team contexts than in corporate game development, where unpredictability in player experience can trigger legal and quality-assurance paralysis.
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