SelecTube – Curated YouTube for Kids

Hacker News

Sharing a side project that was inspired by some here on Hacker News. Many parents realize that while YouTube does have some really good content (ie. Mark Rober), it also has a lot of junk. The YouTube Kids app was not better. My 8 year old would get sucked into watching mindless videos by the algorithm + autoplay. I don't mind some screen time, but want it limited and of quality and value. Some HN commenters mentioned how they carefully manage exactly what YT content their kids can watch. I thought "that sounds like way too much work". So instead I did the obvious thing and spent 10-100x more time building an app for my kids :) SelecTube is a curated set of quality YouTube creators that I'm ok with my kids watching. It doesn't autoplay and doesn't add any ads (totally ad-free with YT premium). It has worked well for my kids - they spend less time watching YT videos, and when they do it is typically educational. My other motivation was to play with AI tools, which I don't do much in my day job. This was built using Cursor. The landing page is mostly AI generated. Overall, for someone like me who can code, but does it infrequently enough to be super slow, Cursor was a super power. There were silly time consuming things it couldn't figure out, but also massive things it could. Now I'm trying to decide whether to leave this more or less as-is, as a tool serving my own kid vs. continue building. There is a lot I could make better: - Some actual design - Add accounts to enable things like watch history, parent customization of content - Add more content - Somehow improve discovery and personalization of content without just recreating the original problem :) Thanks for taking a look! Appreciate any and all comments.

Visit product View on Hacker NewsAug 30, 2025

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

96%96% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Hacker NewsStrong engagement from HN community · Strong signals: hacker news, ide, io · Missing: https docs, excited, just released

62%62% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

55%55% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

53%53% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: personal, video, way · Missing: mobile apps, ios, entrepreneurs

42%42% 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, 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 · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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