Assignment Planner

Inspiration

We have faced time management issues in the past and have seen it as a recurring theme in our generation amongst friends and classmates, where everyone tends to have a lot of assignments in their day but struggles to know where to start.

What it does

It is a web app where the user enters: how many study hours they have available that day, their assignments, and a priority level for each assignment on a scale of 1 to 5. Based on these metrics, we create the best estimated assignment planner where we rank the order in which the assignment tasks should be done and an estimated time on how long each task will take.

How we built it

We implemented this using agentic AI. We created a planner agent and gave it a defined role, goal, and instructions — essentially telling it to act like a student study planning assistant. The agent takes the user’s input and returns a practical study schedule, while also considering priorities and realistic task durations.

Challenges we ran into

One of our biggest challenges was figuring out how to get started, especially since this was our first hackathon and we are beginners. We also ran into technical issues while setting up dependencies and integrating different tools. Another major challenge was converting our original hardcoded logic into a user-friendly Streamlit app with a clean interface. Debugging package imports, API key setup, and framework compatibility took time, but it helped us better understand the full development process.

Accomplishments that we're proud of

We are proud that we were able to build a fully working AI-powered assignment planner from scratch during our first hackathon. We successfully turned our idea into an interactive web app that takes real user input and generates a useful study plan. We’re also proud that we kept improving it despite setup and debugging challenges.

What we learned

Through this project, we learned: how to build and deploy a simple web app interface using Streamlit, how agentic AI works (roles, goals, and task-based prompting), how to connect a frontend UI to backend planning logic, how to debug dependency, environment, and API key issues, and how to collaborate effectively under hackathon time pressure. We also learned that even a simple idea can be impactful if it solves a real, everyday problem.

What's next for Assignment Planner

In the future, we want to expand Assignment Planner with more personalization and smarter planning features, such as: due dates and deadlines, subject-based difficulty estimation, having it plan a whole week instead of a day, maybe calendar integration, and a more advanced UI. We also want to improve the AI’s time estimation accuracy and make the app more visually polished and mobile-friendly so that more students can use it easily.

Built With

• agenticai
• crewai
• gpt4
• openai
• python