-
-
TaskMaster Dashboard to track and manage workflow for freelancers
-
Control Center for adding task,mark complete or block tasks
-
TaskMaster AI Agent that manages task workflow
-
Project Intelligence checks health
Inspiration
Freelancers often have to manage many responsibilities at once—understanding client requirements, breaking projects into tasks, tracking progress, handling delays, and adjusting plans when something gets blocked. I wanted to build a project-management assistant that goes beyond simply displaying a task list.
This inspired TaskMaster AI, an autonomous AI project manager designed specifically for freelancers. The goal was to create an agent that can understand a project, break it into actionable work, identify blockers, and help adapt the plan when circumstances change.
What It Does
TaskMaster AI provides a centralized workspace for managing freelance projects. It can:
📋 Break project goals into actionable tasks 🎯 Assign task priorities 🔗 Track task dependencies 🚨 Identify blocked work 🔄 Replan tasks when blockers occur 📊 Monitor project progress 🧠 Provide project intelligence through an AI-agent workflow
The application includes a dashboard, task management interface, AI Agent section, and Project Intelligence view.
How I Built It
I built TaskMaster AI using Python and Streamlit for the user interface, with a modular agent architecture based on Google ADK and Gemini concepts.
The project is organized into separate components for the application, agent logic, and task-management tools. The workflow is designed around the idea of an autonomous project manager rather than a simple chatbot.
The main architecture is:
User → Streamlit → TaskMaster Agent → Task Tools → Project State
The TaskMaster agent is designed to:
Understand the user's project goal. Decompose the project into practical tasks. Prioritize the tasks. Identify dependencies. Monitor project state. Detect blockers. Replan the project when necessary.
The project is hosted using Streamlit, with the source code maintained in GitHub.
What I Learned
This project helped me understand how AI agents can be designed around actions and tools, rather than only generating text.
I learned about:
Building an agent-oriented application Structuring an AI project into modular components Using Google ADK concepts for agent workflows Designing task-management tools Connecting frontend interfaces with application logic Working with Git and GitHub Deploying Python applications with Streamlit Designing an interface that makes an AI workflow understandable to users
One of my biggest takeaways was that an effective AI agent should not just tell the user what to do—it should be designed to take meaningful actions on the project state.
Challenges I Faced
One of the biggest challenges was connecting the different parts of the application and making sure the frontend, backend, and agent workflow worked correctly together.
I also faced deployment and environment issues while moving the project from local development to Streamlit. Debugging API endpoints, environment configuration, GitHub synchronization, and Streamlit deployment required several iterations.
Another challenge was designing the application so that the AI functionality was clearly demonstrated rather than hidden behind a simple chat interface. I therefore focused on making the project's task creation, blocker detection, project health, and replanning capabilities visible in the UI.
These challenges taught me that building an AI agent is not only about the model—it also requires careful software architecture, tool integration, debugging, and user experience design.
Future Improvements
In the future, I would like to extend TaskMaster AI with:
Persistent database storage Real Gemini-powered task decomposition Automatic dependency analysis Deadline and time estimation Client communication assistance Multiple project support Calendar integration More advanced autonomous replanning Notifications for approaching deadlines
Ultimately, I want TaskMaster AI to become a reliable AI project partner for freelancers, helping them spend less time managing projects and more time delivering great work.
Log in or sign up for Devpost to join the conversation.