I made an LLM-powered HN digest personalized just for you

Hacker News

Hi HN, I've built My Hackernews ( https://www.i-made-an-llm-powered--hacker-news-digest-just-f... ), an AI-powered service that curates and personalizes Hacker News content just for you. With over 1,000 stories and around 10,000 comments posted daily on HN, staying updated can be overwhelming. Here's what My Hackernews does: - Uses Claude 3.5 Sonnet and GPT-4 to analyze and curate HN posts - Creates a personalized digest based on your interests - Delivers content in a customizable email format - Provides an ad-free experience You can try sending a sample digest for free, no sign-up required. If you like it, we offer a three-week free trial, followed by a $4.99/month subscription (cancel anytime). I built this to solve my own problem of staying informed without spending hours browsing. I'm curious to hear your thoughts: - What features would make this valuable to you? - How do you currently keep up with HN and tech news? - Any concerns about AI-curated content? Looking forward to your feedback and happy to answer any questions!

Visit product View on Hacker NewsJul 24, 2024

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Actual performance

3points

Did not reach leaderboard

Launch Intel predictions

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

76%76% 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: claude, new, email · Missing: mac, agents, macos

61%61% 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, month · Missing: mobile apps, ios, entrepreneurs

44%44% 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: lua, hacker news, ide · Missing: https docs, excited, just released

36%36% 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 · Strong signals: subscription · Missing: arr, mrr, revenue

13%13% 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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