My Approach

In developing TaskGenie, I focused on creating a seamless integration between frontend and backend systems to automate task generation using AI. By combining Django, Node.js microservices, and Anthropic’s API, I aimed to build a responsive platform that simplifies task management and boosts productivity.

Vision and Innovation

TaskGenie envisions transforming how users generate and manage tasks by leveraging AI to automatically create actionable task lists. The platform integrates smart automation with user-friendly interfaces, enabling users to focus on what matters most while the system handles routine task creation and organization.

Identifying Unique Challenges

During development, I encountered challenges such as handling inconsistent API responses from Anthropic’s Claude model, determining which tasks are actionable for users, and ensuring smooth communication between Django and Node.js microservices. Additionally, designing a dynamic UI that supports task rendering and database storage required careful planning.

Resolving Complex Problems

To overcome these issues, I implemented structured message requests using the Anthropic SDK, applied regex and JSON repair techniques to parse non-standard API responses, and developed logic to identify executable tasks. Finally, I built robust task and subtask storage mechanisms to maintain data integrity.

User-Centric Design

TaskGenie’s interface supports real-time task generation, clear visualization, and easy saving of tasks. The login system was enhanced to handle edge cases like duplicate user information, ensuring a smooth user experience. By focusing on usability and automation, TaskGenie empowers users to manage their workload efficiently.

Conclusion

TaskGenie represents a practical blend of AI and full-stack development to automate task management. Through continuous iteration and problem-solving, the platform is evolving into a reliable tool that increases user productivity and satisfaction by simplifying complex workflows.