Li

Listicle Club – Convert Any Blog to an X Listicle

Hacker News

Listicle Club – Convert Any Blog to an X Listicle

I have been working on this project for quite a while. Here is what is happening in the background: - Scraping the entire page content, run it with ChatGPT to test if it can be converted into a listicle. - Send the job into the queue. - Scrape the entire page again, and pass it to LangChain with ChatGPT to create a formatted JSON of name, description, features, and URL. - Iterate over all the URL, take a screenshot with Puppeteer, and send it to Remotion to make a video. - Craft the main post of the thread using all the other posts - Save everything to a serverless Postgres and present it. This works over serverless so that it can scale (I didn't want to work with scaling servers) Here is an example Original blog: https://links.github20k.com/blog Thread: https://listicle.club/preview/U2FsdGVkX189pQBKMKMvQwOQSrvVRN... I still need to work on the post size. Sometimes it passes 280 chars. Thinking about waiting for gpt-4-32k; hopefully, the results will be much better. Let me know what you think!

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Actual performance

3points
1comments
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
78%78% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: chatgpt, using · Missing: mac, agents, macos
75%75% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
73%73% 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 · Strong signals: video · Missing: mobile apps, ios, personal
49%49% 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
38%38% 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
17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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