AI movie recommender based on your Letterboxd profile

Hacker News

We built YourTaste — an AI-powered movie recommender that analyzes your Letterboxd profile (likes, ratings, reviews) and gives you suggestions tailored to your taste. You can also search by vibe (e.g. “slow but emotionally intense”) or use prompts like "movies similar to Aftersun but with a hopeful ending." It’s a non-commercial MVP — we wanted to see if we could build a system that really understands movie taste using LLMs and user's data. We’d love feedback from the community — both on the product idea and the technical direction.

Visit product View on Hacker NewsJun 22, 2025

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

84%84% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

AppSumoMay struggle as an AppSumo deal · Strong signals: reviews · Missing: plus, platform, intuitive

48%48% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

34%34% predicted probability of success on Indie Hackers, 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

28%28% 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 · Missing: mobile apps, ios, personal

22%22% 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 · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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