Apparent – Make Gmail easier to read and manage

Hacker News

Built because I wanted Gmail to feel simpler. Built for myself, then realized why not give it to the world too. Nothing is badly broken, but a lot of small things add friction: conversation order, collapsed messages, visual clutter, and newer UI elements that feel more distracting than useful. It’s a small Chrome extension that changes a few of those things. Right now it mainly: * reverses conversation order * shows every message in a thread * reduces interface clutter * hides some of the newer AI/Gemini UI The goal wasn’t to heavily customize Gmail. I just wanted it to feel cleaner, easier to scan, and more straightforward to use. It runs locally in the browser, with no remote processing or data collection. No account either. Free. I’d love to know whether this matches problems other people have with Gmail, or whether I’ve mostly built something for myself. UseApparent@gmail.com

Visit product View on Hacker NewsMar 31, 2026

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Actual performance

2points

2comments

Did not reach leaderboard

Launch Intel predictions

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

81%81% 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: gemini · Missing: supports, reddit linkedin, podcasting

80%80% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

44%44% 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

38%38% 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

17%17% 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

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