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LazyWords
Your own dictionaries, now floating flashcards on Windows
Turn your own CSV, JSON or XLSX dictionaries into floating flashcards on Windows. Review vocabulary, technical terms or course notes while you work. Set the timing, mark familiar cards as learned, and keep decks and progress locally.
Hi Product Hunt, I'm Dzmitry, the developer of LazyWords.
The starting point is your own learning material: a vocabulary list, technical glossary or set of course notes. Put the short items you want to revisit into term/definition pairs, import a CSV, JSON or XLSX file, and LazyWords displays them as small flashcards over your Windows desktop.
You choose the position, text size, display duration and interval. You can pause the cards, request the next one, and mark familiar items as learned. Dictionaries and progress are stored locally, and the app works offline after installation without an app account.
Built-in English packs are included, but they are a starting point, not a limit on what you can put in your own deck.
This is a lightweight reminder alongside active study, not a full spaced-repetition system or a promise of learning without practice. It is Windows-only for now.
Version 1.0.2 focuses on reliability: long-card layout, settings persistence, dictionary switching and Windows startup behavior. I built it with Tauri, Rust and JavaScript, with Codex helping during development and testing. AI is part of the build story, not a requirement for using your decks.
I'd especially appreciate feedback on custom imports: what would you put in your first deck, and what card timing would fit your workday?
About LazyWords on Product Hunt
“Your own dictionaries, now floating flashcards on Windows”
LazyWords was submitted on Product Hunt and earned 2 upvotes and 1 comments, placing #40 on the daily leaderboard. Turn your own CSV, JSON or XLSX dictionaries into floating flashcards on Windows. Review vocabulary, technical terms or course notes while you work. Set the timing, mark familiar cards as learned, and keep decks and progress locally.
On the analytics side, LazyWords competes within Productivity, Education, Languages and GitHub — topics that collectively have 800.9k followers on Product Hunt. The dashboard above tracks how LazyWords performed against the three products that launched closest to it on the same day.
Who hunted LazyWords?
LazyWords was hunted by Dzmitry Salavei. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of LazyWords including community comment highlights and product details, visit the product overview.
Dzmitry Salavei
Hi Product Hunt, I'm Dzmitry, the developer of LazyWords.
The starting point is your own learning material: a vocabulary list, technical glossary or set of course notes. Put the short items you want to revisit into term/definition pairs, import a CSV, JSON or XLSX file, and LazyWords displays them as small flashcards over your Windows desktop.
You choose the position, text size, display duration and interval. You can pause the cards, request the next one, and mark familiar items as learned. Dictionaries and progress are stored locally, and the app works offline after installation without an app account.
Built-in English packs are included, but they are a starting point, not a limit on what you can put in your own deck.
This is a lightweight reminder alongside active study, not a full spaced-repetition system or a promise of learning without practice. It is Windows-only for now.
Version 1.0.2 focuses on reliability: long-card layout, settings persistence, dictionary switching and Windows startup behavior. I built it with Tauri, Rust and JavaScript, with Codex helping during development and testing. AI is part of the build story, not a requirement for using your decks.
I'd especially appreciate feedback on custom imports: what would you put in your first deck, and what card timing would fit your workday?