Turn your RSS feeds into a NotebookLM-style daily podcast

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About a year ago, I built an RSS reader than had some features I couldn't find elsewhere at the time (specifically topic/keyword muting). I recently added the ability to listen to a daily podcast, generated from an individuals personal RSS feeds. While I think the idea is cool, I am curious if others would listen to a podcast they know is AI generated, on a more permanent basis? Would anyone subscribe to a personal AI podcast within their regular podcast client? AI content within social media seems poorly received (passive consumption), but NotebookLM was praised (perhaps because it is not passive engagement). Any feedback or experiences would be amazing. Thanks!

Visit product View on Hacker NewsJun 26, 2025

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2points

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos

78%78% 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

69%69% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

58%58% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · 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

37%37% 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

19%19% 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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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