I’ve made a lot of routines for study and projects. Writing down the work was easy. The harder part was deciding what should happen each day without ignoring deadlines or filling every hour with an unrealistic plan.
Turning my method into rules
Plan Like Me asks what needs to be finished, how long it may take, when it is due, and how much time is available. It divides the work into sessions and places them across the selected days. I kept the scheduling rule-based rather than calling it AI, because I wanted each decision to be predictable and explainable.
The difficult cases
The project became more interesting when I tested plans that couldn’t fit. I had to handle early deadlines, uneven study time, unrealistic workloads, and unfinished sessions without pretending that everything was possible.
If the work doesn’t fit, the planner shows the shortfall. The user can then change a deadline, reduce the work, or add more available time.
What I learned
The scheduling logic took more thought than the interface. Small rules affected the whole plan, so I had to test edge cases and make the result easy to understand. Drafts and completed sessions stay in the browser, and a finished routine can be saved as a PDF without creating an account.