What to Watch – aggregated ratings across streaming services

Hacker News

I kept running into the same problem: trying to find something new to watch, opening multiple streaming apps, and Googling titles one by one because the apps don't tell you if something is actually worth watching. So I built What to Watch, which aggregates content across major streaming services and reduces discovery to a simple Watch or Skip decision using IMDb and community ratings. I hadn’t written code since high school — this was built over ~400 iterations using Claude and Replit. Still very early and mostly trying to learn how people actually decide what to watch and how broad this use case is. Would love feedback from the HN community.

Visit product View on Hacker NewsFeb 27, 2026

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44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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40%40% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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22%22% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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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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