Ez
Ezra Klein Books – Every Book Recommended on the Ezra Klein Show
Hacker NewsEzra Klein Books – Every Book Recommended on the Ezra Klein Show
Hey HN! If you're a listener of the Ezra Klein Show podcast, you know he asks his guests 3 books they recommend. This side project catalogues all those books into a searchable and sortable list. It was my first time hiring a designer from Upwork to do the design, and overall I'm pretty happy with how it turned out. It's built using django, htmx, alpinejs, and tailwind. Happy to hear any and all feedback! Thanks!
Share cardActual performance
7points
Made the leaderboard
Launch Intel predictions
Analyze your own launch →Hacker NewsStrong engagement from HN community · Strong signals: ide · Missing: https docs, excited, just released72%72% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting63%63% 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: using · Missing: mac, agents, macos56%56% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive52%52% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal45%45% 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, revenue17%17% 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, crypto7%7% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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