PlayNext

PlayNext reads a user’s Steam library, playtime statistics, recent sessions and unplayed backlog to build a profile of the games they actually enjoy, finish, replay or abandon quickly. Using this data it generates a short, prioritized list of titles that match the player’s identified habits, such as short combat loops, deep RPG sessions or low‑commitment evenings. The interface presents the suggestions in a format similar to a streaming app, showing a brief rationale for each pick (e.g., “because you replay fast combat”).

The software is aimed at Steam users who want a quick answer about what to play next rather than browsing the store or their entire collection. It is useful for those who have large libraries and prefer data‑driven recommendations that reflect their real playing patterns. The decision engine highlights both owned games that deserve another try and titles that may be worth purchasing on sale.

PlayNext is currently in an experimental stage, offering a minimal but functional workflow: connect a Steam account, let the system detect playing habits, and view the strongest recommendations. The focus is on delivering a concise, habit‑based decision rather than an exhaustive catalog.