A

A Japanese learning app focused on efficient vocab/grammar acquisition

Hacker News

A Japanese learning app focused on efficient vocab/grammar acquisition

Hey HN, it’s been 8 years since I posted on here about the launch of my Japanese dictionary app Nihongo [0] and I’m finally back with a new app: Nihongo Lessons! Think of Nihongo Lessons as the textbook to Nihongo’s dictionary. It’s an app for learning Japanese, specifically made for learners who are serious about becoming fluent, and want a guided set of content that will help them efficiently acquire vocabulary and grammar. The project came about when Adam Shapiro of Japanese Level Up (Jalup) [1] announced last April that he was shutting Jalup down. As a fan of Adam’s work I was bummed to hear the news, but realized I actually might be one of the few people in the world in a position to keep his work alive. So I reached out, and we came up with a deal where I would sell Jalup content in my apps. Originally it was envisioned as an add-on to Nihongo, but after starting to build this out it became clear that from a UX perspective it felt too bloated and tacked-on to just shove Jalup into Nihongo. Plus, given that Jalup is built around one-time content purchases, and Nihongo is a subscription, the purchases involved would feel convoluted, and people might be upset that they weren’t included in the Nihongo subscription. So, I started building a separate app that would become Nihongo Lessons. From a technical perspective, Nihongo Lessons is actually just a different entry point into essentially the same app bundle as Nihongo. This gives me a lot of the infrastructure (sync, error reporting, screenshot generation, etc.) of Nihongo for free, and makes it easy to share UI, which I do a fair amount of (flashcards, tutorials, settings). Everything that actually changes behavior between the apps is stored in a single file as an “app variant” configuration, so if I decide to create another companion app in the future, it should be even easier. It’s iPhone-only for now, but iPad will be coming soon. No plans for an Android release at the moment. Download: https://apps.apple.com/app/id1640204242 [0]: https://news.ycombinator.com/item?id=10094326 [1]: https://japaneselevelup.com

Share card

Actual performance

161points
116comments
Made the leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Strong signals: started, para, efficiently · Missing: supports, reddit linkedin, podcasting
92%92% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
TrustMRRFits verified-revenue profile · Strong signals: apps, para · Missing: mobile apps, ios, personal
64%64% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: apple, apps, new · Missing: mac, agents, macos
55%55% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
55%55% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: plus, soon, efficient · Missing: platform, intuitive, reviews
40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: subscription · Missing: arr, mrr, revenue
19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

KanjiHub
KanjiHub70%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Learning App, Learning Japanese, Full Stack

Indie Hackerscommitment-full-time
KanjiHub
KanjiHub69%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Learning App, Learning Japanese, Full Stack

Indie Hackerscommitment-full-time
JLPT monster
JLPT monster49%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

a japanese learning APP

Product Hunt+1
JapLab Kana
JapLab Kana17%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Kana Learning App

Indie Hackerscommitment-side-project
La
Lala – Learning Japanese App51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Lala – Learning Japanese App

Hacker News9
Learnosphere learning app
Learnosphere learning app35%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Learning Made Simple.

Product Hunt+6
Lantalk
Lantalk32%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Lantalk languages learning app for everyone!

Indie Hackers1ai
Memocards
Memocards44%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

US Citizenship Question Learning App

Indie Hackers1education
Gitasphere
Gitasphere17%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Emotion-mapped Bhagavad Gita learning app

Indie Hackers
Ap
App for learning how to write Japanese54%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

App for learning how to write Japanese

Hacker News55