This is a submission for the GitHub Finish-Up-A-Thon Challenge
What I Built
Every developer has at least one project that starts with excitement but gets left unfinished. For me, that project was The Tiebreaker App.
Originally, it was a simple tool designed to help users break ties between competing choices. While the concept worked, it lacked the depth, intelligence, and user experience needed to become truly useful.
Instead of letting the project remain dormant, I decided to revisit it with a new vision:
Transform a basic decision-making tool into an AI-powered decision intelligence platform.
The result is The Tiebreaker AI, an application that helps users evaluate complex decisions using structured analytical frameworks and AI-generated insights.
Rather than simply selecting a winner, the platform explains why a particular option is recommended through SWOT analysis, comparison tables, confidence scoring, probability assessments, and transparent AI reasoning.
Key Features
🤖 AI-Powered Decision Analysis
⚖️ Pros & Cons Evaluation
🧠 SWOT Analysis
📊 Comparison Table Generation
📈 Probability of Success Estimation
🎯 Confidence Scoring
💡 AI-Generated Verdicts
🔍 Decision Reasoning Trace
📱 Responsive Modern UI
✨ Gemini AI Integration
This project means a lot to me because it represents something many developers struggle with: returning to unfinished work and finally bringing it closer to the original vision.
Demo
🌐 Live Application
https://ai.studio/apps/1530db08-7c27-4fb5-a4ba-ffba6714c94e?fullscreenApplet=true
💻 GitHub Repository
https://github.com/rajamuhammadyasinkhan2019-lgtm/The-Tiebreaker-App
Decision Analysis Dashboard
Users can enter a decision question, provide context, and choose an analytical framework.
Examples:
Should I learn Python or TypeScript?
Should I pursue higher education or industry experience?
Should I launch Product A or Product B?
SWOT Analysis
The application automatically generates:
Strengths
Weaknesses
Opportunities
Threats
along with:
Confidence Score
Success Probability
Final AI Recommendation
Comparison Framework
Users can compare alternatives side-by-side and understand the trade-offs before making a decision.
AI Verdict
The platform provides a final recommendation supported by structured analysis rather than a simple guess.
The Comeback Story
Where the Project Started
The original version of The Tiebreaker App was built as a lightweight decision helper.
Its purpose was straightforward:
Help users choose between competing options.
Although functional, it lacked the depth required for meaningful decision support.
Initial Limitations
Basic functionality
Minimal user interface
No AI integration
No analytical frameworks
No confidence metrics
No probability modeling
No reasoning transparency
Eventually, development stalled and the project remained unfinished.
Why I Decided to Revive It
I realized that many unfinished projects fail not because the idea is weak, but because the implementation never reaches maturity.
Rather than creating another new project, I chose to revisit an existing one and see how far it could evolve.
The goal became clear:
Build a tool that helps people make better decisions—not just faster decisions.
What Changed
Before
Simple tie-breaking utility
Static outputs
Minimal interface
No AI assistance
No structured analysis
Limited practical value
After
Gemini AI integration
SWOT Analysis Engine
Pros & Cons Framework
Comparison Matrix Generation
Confidence Scoring
Success Probability Modeling
Decision Reasoning Trace
Modern Responsive Design
Improved User Experience
Before vs After
Before After
Basic tie-breaker AI-powered decision intelligence platform
Single outcome Multi-dimensional analysis
No AI integration Gemini-powered recommendations
No explanation Transparent reasoning process
Limited functionality Comprehensive decision support
Prototype Fully usable application
One of the most rewarding improvements was moving beyond simply generating an answer and instead helping users understand the reasoning behind that answer.
My Experience with GitHub Copilot
GitHub Copilot played a major role in helping me bring this project back to life.
Returning to an older codebase often means dealing with unfinished features, technical debt, outdated patterns, and ideas that never reached completion.
Copilot helped reduce that friction significantly.
Refactoring Existing Code
Copilot assisted with:
Component restructuring
Cleaner TypeScript patterns
Improved state management
Better code organization
This made the application easier to maintain and extend.
Accelerating Feature Development
Several major features were developed more efficiently with Copilot assistance:
SWOT Analysis
Copilot helped generate component structures and implementation patterns for SWOT generation workflows.
Comparison Tables
It accelerated UI development and data rendering logic for structured comparisons.
Decision Scoring
Copilot supported the implementation of:
Confidence metrics
Evaluation workflows
Probability assessment logic
AI Prompt Engineering
Since the platform relies on AI-generated analysis, prompt quality is critical.
Copilot helped refine:
Prompt structures
Response formatting
Consistent output generation
Error-handling scenarios
Debugging and Polishing
Copilot also proved valuable for:
Resolving UI inconsistencies
Improving responsiveness
Handling asynchronous API calls
Reducing repetitive coding tasks
Biggest Takeaway
The biggest benefit wasn't simply writing code faster.
It was being able to focus on improving the product itself rather than spending time on repetitive implementation details.
Copilot made it easier to return to an unfinished project, regain momentum, and finally transform an abandoned prototype into a polished application.
What I Learned
This project reinforced an important lesson:
Unfinished projects are not failures—they are opportunities waiting for another iteration.
Reviving The Tiebreaker App taught me the value of revisiting older ideas with fresh perspectives, better tools, and more experience.
What began as a simple tie-breaking utility evolved into a practical AI-powered decision intelligence platform capable of helping users make informed choices through structured analysis and transparent reasoning.
Most importantly, it reminded me that sometimes the best project to build isn't a new one—it's the one you've already started.
Tech Stack
React
TypeScript
Google Gemini AI
GitHub Copilot
Modern UI Components
About the Author
Muhammad Yasin Khan
Geologist | Geoscience and AI Practitioner| Open-Source Contributor
Passionate about applying artificial intelligence, computational thinking, and data-driven technologies to solve real-world challenges in Geoscience, Scientific Research, Education, and Decision Intelligence. I enjoy building AI-powered applications that combine domain expertise with modern intelligent systems.
🔗 GitHub:
https://github.com/rajamuhammadyasinkhan2019-lgtm
Thank you for reading and reviewing my submission! 🚀
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