I made a browser tab management extension

Hacker News

Hello Again HN ! My name is Tafita, and I'm back with my second launch: Tag my Tab The indie hacker journey hasn't gotten easier (spoiler: the imposter syndrome is real), but seeing people actually use something I built? That feeling never gets old. Meet Tag my Tab – Never Lose a Tab Again So here's the thing: while building and marketing my other products, I found myself drowning in browser tabs. Research articles, competitor analyses, design inspiration, documentation, customer feedback. I'd have 30+ tabs open, my browser grinding all my RAM and I was living in constant fear of that accidental "Close All" click. Sound familiar? That's why I built Tag my Tab, a browser extension that helps you organize your tab chaos with tagging, comments, and powerful search. What Makes It Different: Tag It: Categorize any tab in one click with custom tags Comment It: Add notes so you never wonder "why did I save this?" again Find It: Search by title, tag, or comment to find anything instantly Close It: Confidently shut tabs knowing they're saved forever Sync It: Access your organized tabs across all your devices How It Works: Install the extension from the Chrome Web Store Click on any tab and add a tag or comment Close saved tabs with confidence, search and restore them anytime No more RAM screaming for mercy. No more tab hoarding out of fear. Pricing: Free: Unlimited tabs, 3 tags, dated comments, full search, cloud sync Pro: $4.99 one-time payment (not subscription!) for unlimited tags and comments If you're drowning in tabs like I was, I'd love for you to try Tag my Tab. And as always, I'm hungry for feedback—the good, the bad, and the "here's a bug" reports. Drop a comment or email me at tafita@tagmytab.com. Let's chat! Thanks for being here for launch #2. Here's to many more. — Tafita

Visit product View on Hacker NewsNov 28, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: email, notes, open · Missing: mac, agents, macos

89%89% 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

87%87% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

37%37% 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

30%30% 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: way · Missing: mobile apps, ios, personal

28%28% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

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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