AnyTopic – X/Twitter bot that creates podcasts based on any tweet

Hacker News

hey HN, I’m the cofounder of AnyTopic. We create custom podcasts to help you learn about any topic in an audio format. A lot of tweets on X/Twitter mention something interesting I want to learn more about. I found myself bookmarking these tweets to find more information about them later but most times I end up not doing anything with them. We built a twitter bot (@getpodcastapp) that creates a podcast when you mention it in a reply. The bot finds information related to the content in the tweet and/or thread (news, blogs, social media, videos or even Wikipedia) to create a unique podcast that helps you dig deeper into that topic. This saves you time doing research and gives you the option to listen to your episode while multitasking. Here’s an example of how it works: https://x.com/getpodcastapp/status/1778223876792787193 Podcasts are the easiest way to explain what we do, but we’re not trying to replace what current podcasts do. We believe that podcasts are as much about the people sharing their thoughts as they are about the knowledge being shared. With this bot and AnyTopic, we want to help people who prefer audio content learn about anything online way faster. We'd love to hear your thoughts or answer any questions.

Visit product View on Hacker NewsApr 11, 2024

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

86%86% 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.

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

81%81% predicted probability of success on Product Hunt, 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

48%48% 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

34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

32%32% 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

14%14% 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 · 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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