Building a revision scheduler for students in 5 hours

How I built a planner for test prep students to revise their syllabus in 2 days flat (with no help from my tech team)

The Challenge

As CEO of NEETprep.com, I constantly hear from students struggling with time management during their exam preparation. The most common complaint? “I don’t know how to fit all my revision into the remaining time before my exam.”

Traditional study planners are either too generic or too complex. Students need something that understands their specific syllabus, available time, and learning pace.

The Solution: AI-Powered Revision Scheduler

Instead of waiting for my development team to build this feature (which would take weeks), I decided to leverage AI to create a functional revision scheduler in just 5 hours.

What It Does

• Input Processing: Students enter their exam date, available study hours per day, and subjects with topics
• Intelligent Scheduling: AI analyzes the workload and creates an optimal revision timetable
• Adaptive Planning: Adjusts for different subject priorities and difficulty levels
• Progress Tracking: Allows students to mark completed topics and rebalances remaining schedule

Technical Implementation

Frontend: Simple HTML/CSS interface with JavaScript for interactivity AI Integration: Used Claude API for intelligent scheduling logic Data Processing: Custom algorithms to balance workload across available time Export Features: Students can download their personalized schedule as PDF

Key Features

1. Smart Time Allocation: Automatically distributes topics based on complexity and importance
2. Buffer Time Management: Includes break periods and buffer time for unexpected delays
3. Visual Timeline: Clean, easy-to-read calendar view of the entire revision plan
4. Mobile Responsive: Works seamlessly on phones for on-the-go planning

Results

Within 24 hours of launch:

• 500+ students used the scheduler
• Average planning time reduced from 2 hours to 5 minutes
• Student satisfaction increased significantly based on feedback

Lessons Learned

Speed Over Perfection: Getting a working solution out quickly allowed for real user feedback AI as a Force Multiplier: What would have taken weeks of development was accomplished in hours User-Centric Design: Focusing on the core problem led to a more effective solution

Technical Challenges Overcome

• Complex Scheduling Logic: Balancing multiple constraints while keeping the interface simple
• Data Validation: Ensuring realistic time estimates and catching user input errors
• Performance Optimization: Making the scheduling algorithm fast enough for real-time use

This project perfectly demonstrates how entrepreneurs can leverage AI to build functional solutions rapidly, without waiting for traditional development cycles.

This post is part of my series on “10xing with AI” - practical examples of how builders can leverage AI to accelerate their outcomes.