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A Hacker News Reader Built Using Gemini CLI with REFui
Hacker NewsA Hacker News Reader Built Using Gemini CLI with REFui
rEFui is my own Solid.js like frontend framework, no information about it should be present in the pre-trained data. 90% of the code is written by Gemini-2.5-Flash(not even Pro), with only documents about rEFui provided. Really impressive. This demo is built with official HN API, so each story/comment is fetched separately.
Share cardActual performance
2points
Did not reach leaderboard
Launch Intel predictions
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Product HuntOn track for Day 1 leaderboard · Strong signals: new, gemini, using · Missing: mac, agents, macos86%86% 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 · Strong signals: para, gemini · Missing: supports, reddit linkedin, podcasting82%82% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive52%52% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: hacker news, ide, io · Missing: https docs, excited, just released49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: para · Missing: mobile apps, ios, personal27%27% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue16%16% 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, crypto3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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