HN Watercooler – listen to HN threads as an audio conversation

Hacker News

Hi HN, here's something fun to play with. It takes any HN thread and turns it into an audio conversation so you can listen to the thread while doing other things. I've seen many previous attempts to turn HN threads into podcasts, but they all shared a common issue IMO: trying to reduce the very rich back-and-forth into a single-thread single-reader boring podcast. Instead, I wanted to hear the actual debate from the actual thread! So I asked Claude 3.7 to build this for me as a browser-only app. It just needs a thread URL and an Elevenlabs API key (this all remains in your browser, you can check the source code, it's only 3 files, there is no server storage of anything). To make the resulting audio experience as natural as possible, each commenter has a different voice. Commenters who appear multiple times in the thread have the same voice, and introduce themselves. A bit of context is also introduced when coming back "up" from deeply nested comments. You can play the resulting audio or download it for later listening. I'm planning to later add the ability to load multiple threads so I can have a playlist generated for listening in the gym! Any comments or improvement suggestions are appreciated!

Visit product View on Hacker NewsApr 17, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: claude, context, elevenlabs · Missing: mac, agents, macos

92%92% 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

91%91% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

58%58% 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 · Missing: mobile apps, ios, personal

48%48% 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

33%33% 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

18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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