My tiny project MyTube Newsletter – daily AI digest of YouTube subs

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This is technically a Show HN for MyTube Newsletter — an email digest of new videos from the YouTube channels you subscribe to, AI-summarized. But the tech isn't very interesting. I'd rather talk about why I shipped it. Like many other developers, I have a huge backlog of projects I want to do but never get around to. I have a much smaller list of half-finished or "finished" projects that never see the light of day. This time around I'm hoping to take a project from not just code-complete and deployed but also with basic monetization and at least a minimal attempt at marketing. In the spirit of that, I purposely picked something small in scope. At the start of the year, I was aiming to do at least one of these every month, but as you can see it's end of May and this is still my first project of the year. In fact, I fell into a similar trap of "it works for me, so it's done" and procrastinated on telling anyone about it for a month. Oh well, better late than never. The motivation for this project specifically is that I've been watching YouTube videos less and less, and even when I do, I've already been doing this manually — opening YouTube, grabbing the transcript, sending it to an LLM. Felt absurd not to just have it delivered on a daily schedule and crush the FOMO. Curious to hear: - If you've shipped a small finished thing recently, what unstuck you? - Why do your half-finished projects stay half-finished? - Anyone else been manually transcripting + AI-summarizing YouTube videos? I figured I wasn't alone, but I'd love to know. The product: https://mytubenewsletter.com $9.99/mo (15 summaries/day) or $19.99/mo (40/day), 7-day trial.

Visit product View on Hacker NewsMay 31, 2026

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

72%72% 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

68%68% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: video, month · Missing: mobile apps, ios, personal

56%56% predicted probability of success on TrustMRR, 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

40%40% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

21%21% 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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