Li

Live-updating version of the 'What a week, huh?' meme

Hacker News

Live-updating version of the 'What a week, huh?' meme

As a fun evening project, I made a live-updating version of the 'What a week, huh?' meme (based on a panel from The Adventures of Tintin comics [1]). There's a page for every timeframe: - 'What a day': https://tintin.dlazaro.ca/day - 'What a week': https://tintin.dlazaro.ca/week - 'What a month': https://tintin.dlazaro.ca/month - 'What a year': https://tintin.dlazaro.ca/year Current time is determined by a Cloudflare Worker using the request IP (not logged or stored). No JavaScript is sent to the browser. [1] https://knowyourmeme.com/memes/what-a-week-huh

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Actual performance

834points
154comments
Made the leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
61%61% 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.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
49%49% 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: month · Missing: mobile apps, ios, personal
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
42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: using · Missing: mac, agents, macos
29%29% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
15%15% 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.

Incorrect prediction on native model

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