Every great project starts with a spark, and for me, that spark was the realization that managing tasks shouldn't feel like a task in itself. That's why I built TaskTango.
What I Built with Google Gemini
TaskTango is a productivity application designed to help users streamline their workflow through intelligent task prioritization and automated scheduling. The core problem I wanted to solve was indecision,having so much to do that you don't know where to start.
Google Gemini played a crucial role as my pair programmer and AI architect throughout this project.
- Generate Boilerplate Code - It scaffolded the initial project structure, setting up the backend API and frontend components much faster than I could have manually.
- Intelligent Logic - I used Gemini to help design the algorithm that ranks tasks based on urgency and importance.
- Debugging - When I hit roadblocks with complicated state management, Gemini provided quick explanations and fixes for complex bugs.
Demo
What I Learned
Building TaskTango was a crash course in both technical implementation and product design.
- Technical Skills - I deepened my understanding of integrating AI models into web applications. I learned how to prompt effectively to get the code snippets I needed and how to refactor AI generated code to fit my specific architecture.
- Soft Skills - The biggest lesson was adaptability. Sometimes the AI suggested a different approach than I originally planned (like a specific library for state management), and learning to pivot based on that advice often saved me time.
- Unexpected Lessons - I realized that AI isn't just about writing code; it's about clarity of thought. To get good output from Gemini, I had to clearly define my problem first.
Google Gemini Feedback
Working with Gemini was a unique experience.
What worked well
The speed of iteration was incredible. Being able to ask, "How do I optimize this specific function for performance?" and getting an immediate, context aware response transformed my workflow. It felt less like searching for answers and more like collaborating with a senior engineer.
Where I encountered friction
There were moments where the context window seemed to drift, specifically when dealing with very large files in my project. Occasionally, I had to remind the model of earlier architectural decisions we had made. However, refining my prompts usually solved this.
Looking Forward
TaskTango is just the beginning. The immediate next step is to refine the user interface and potentially deploy the application on Google Cloud Run to ensure scalability. Longterm, I want to explore deeper integrations with Gemini's multimodal capabilities, perhaps allowing users to upload images of handwritten to-do lists that TaskTango can automatically digitize and schedule.
Top comments (1)
Great work on TaskTango, Kithmini. Your point about AI forcing you to have clarity of thought first is so true. I also ran into some context drift on larger files during my build, but stepping back and refining the prompts got me on the right track too