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Takumi KuroyanagiPublished July 5, 2026AI translation
What we wanted to solve: The daily decision of "What should I wear today?" is a mundane but recurring cost that happens every morning. While conventional weather apps offer clothing advice and general guidelines like "wear this much layering for 16°C," which are frequently introduced on weather programs, these are merely general rules and inevitably diverge from individual body sensations and the clothes one actually has on hand...
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The daily question of "What should I wear today?" is a mundane but recurring cost that happens every morning. While traditional weather apps offer clothing advice and general guidelines like "wear this much layering for 16°C," which are frequently introduced on weather programs, these are merely general rules that inevitably diverge from individual body sensations and the clothes one actually owns. What I really wanted to know was "what did I actually wear on a day with the same temperature and weather as today?"—not the correct answer for everyone else, but the correct answer for myself. In other words, the core concept became: rather than creating an app that "provides the right answer for everyone," I wanted to create an app that "extracts the right answer for me" from past logs.
The trigger to create a new app wasn't armchair theorizing, but witnessing people close to me actually struggling with a real problem. Seeing family and friends quietly agonize each morning over "what to wear today" made me realize this wasn't just my personal feeling but a common need. When I actually had people close to me use it through TestFlight, I confirmed that the anticipated worries were being resolved, which became the decisive factor to move forward with development rather than leaving it as a hypothesis at the planning stage.
What I was particular about was UX that minimizes user effort. Since date and location information are recorded in EXIF data at the moment a photo is taken, I designed the system to automatically calculate the temperature and weather at the shooting date and location using that data as-is. I eliminated any manual input of dates or weather by users entirely, creating a design where "simply keeping photos" completes the record. I also made sure to differentiate the displayed metrics from typical weather apps. The reason users visit this app is not to learn the weather but to decide "what to wear." Rather than displaying general weather information like precipitation probability, I display metrics directly linked to clothing choices, such as UV intensity.
毎朝の「今日、何を着よう」という判断は、地味だけど毎日発生するコストです。従来の天気アプリの服装アドバイスや「16℃ならこのくらいの厚着」といった一般的な指針はお天気番組等でたくさん紹介されますが、それはあくまで一般論で、個人の体感や手持ちの服とは絶対にズレます。本当に知りたかったのは「今日と同じ気温・天気の日に、自分が実際どんな格好をしていたか」という、他人にとってではなく自分にとっての正解でした。つまり「みんなに正しい答え」を出すアプリではなく、「自分にとっての正解」を過去のログから引き出すアプリを作りたい、というのが最初のコンセプトの軸になっています。
新しいアプリを作ろうと思い立ったきっかけは、机上の発想ではなく、身近な人が実際に困っている場面を見ていたことでした。家族や友人が毎朝「今日何を着るか」で地味に悩んでいる姿を見て、これは自分だけの感覚ではなく共通のニーズなのだと気づきました。実際にTestFlightで身近な人に使ってもらったところ、想定していた悩みが解消される様子を確認でき、企画段階の仮説のままで終わらせず開発を進める決め手になりました。
こだわったのは、ユーザーの手間を最小限にするUXです。写真を撮った時点でEXIF情報に日付と位置情報が記録されているため、それをそのまま使って撮影日時・地点の気温や天気を自動で計算するようにしました。ユーザーが手動で日付や天気を入力する手間を一切なくし、「写真を残すだけ」で記録が完結する設計です。また、表示する指標も一般的な天気アプリとは切り分るように気をつけています。ユーザーがこのアプリを訪れる目的は天気を知ることではなく「何を着るか」を決めることです。降水確率のような一般的な天気情報ではなく、服装選びに直結するUV強度のような指標を表示するようにしています。
