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Curate a Mubi watchlist from stated criteria

ChatGPT Agent browsed the Mubi library, picked 10 films matching the user's criteria, gave quick verdicts and added them to the watchlist.

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Use case overview

ChatGPT Agent browsed the Mubi library, picked 10 films matching the user's criteria, gave quick verdicts and added them to the watchlist.

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Reported experience

  1. What they did

    The user gave ChatGPT Agent a set of film criteria: lesser-known movies from 2015–2025, varied countries and styles, and no Hollywood Oscar fare. The agent then browsed Mubi’s library on its own, selected 10 titles it judged fit, wrote brief verdicts on them, and added the picks directly to the user’s Mubi watchlist.

  2. How it went

    The user said it was very efficient and saved them from manually adding the films. They also said Deep Research might have found titles faster, but the agent’s advantage was handling the watchlist edits too.

  3. Worth knowing

    The main catch was speed: the user said another tool could probably have done the discovery faster, but the agent removed the manual watchlist work.

Example prompts

Try with ChatGPT Agent
Open my Mubi account at mubi.com and browse the library for films matching these criteria: [genres, decades, countries, length, mood, things to avoid]. Pick 10, give me a one-line verdict on each, and show me the list before adding anything. Once I confirm, add them to my watchlist and stop.

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