Modern alternative to Google Dictionary, AI-powered and context-aware

Hacker News

I kept losing my reading flow every time I hit an unfamiliar word. The usual fix: open a new tab, search, scroll past ads, come back. Costs about 30 seconds of focus each time. Multiply that by 10 lookups in one article and it adds up fast. Google Dictionary extension solved the tab-switching problem but never went further than static definitions. I wanted something smarter. So I built QuickDef, a Chrome extension that sends the surrounding sentence to GPT-4o-mini alongside the word, so the definition matches what the word actually means in that context, not just the dictionary default. Stack: - Chrome Extension (Manifest V3) - Node.js + TypeScript + Express (backend on Railway) - OpenAI GPT-4o-mini - Supabase (auth + database) - Next.js landing page on Vercel Freemium: 10 free AI lookups/day, unlimited dictionary mode always free. Would love feedback from the HN community, especially on the freemium limit and anything technically questionable. Chrome Web Store: https://chromewebstore.google.com/detail/ioepkncpchchdiookgp... Website: https://www.quickdef.app

Visit product View on Hacker NewsApr 28, 2026

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2points

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Product HuntOn track for Day 1 leaderboard · Strong signals: google, new, context · Missing: mac, agents, macos

77%77% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

54%54% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: google, way · Missing: mobile apps, ios, personal

50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

25%25% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

18%18% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: smart · 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

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