🦋 PathDiverge: Career Butterfly Simulator

"In just 3 small decisions, your career trajectory can shift by $2M or 15 years. PathDiverge quantifies that chaos."

🚀 The Problem: Career Uncertainty

Traditional career planning assumes a linear path. In reality, careers are stochastic systems influenced by thousands of micro-variables—promotions, layoffs, market shifts, and pure luck.

Most people optimize for the average outcome. PathDiverge helps you optimize for the distribution.

By running 5,000 Monte Carlo simulations in parallel, this application reveals the hidden probability distributions of your career, showing not just what might happen, but how likely extreme outcomes (good or bad) really are.

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🏗️ Architecture & Tech Stack

This project is built as a modern, full-stack data application designed for performance and interactive visualization.

Frontend (The "Dashboard")

• Framework: React (Vite) for high-performance rendering.
• Styling: Tailwind CSS with a custom "Matrix/Sci-Fi" aesthetic (Dark Mode) & Professional SaaS theme (Light Mode).
• Visualization: Recharts for interactive data storytelling (Probability distributions, Comparative analysis).
• State Management: React Hooks for real-time simulation parameter handling.

Backend (The "Engine")

• Framework: FastAPI (Python) for asynchronous, high-concurrency simulation handling.
• Simulation Logic: Custom Monte Carlo engine capable of modeling complex career state transitions (Promotion, Stagnation, Layout, Pivot).
• Statistical Analysis: Real-time computation of Confidence Intervals (95% CI), Standard Deviations, and Comparative Deltas (pp difference).

Key Features

• 🦋 The Butterfly Effect Engine: Models how small changes in initial conditions (risk tolerance, specialization) compound over 40 years.
• 📊 Comparative Analysis: "What-If" machine that runs parallel simulations to compare a user's chosen strategy against a baseline control group.
• 🎨 Dual-Theme UI: A polished interface offering both a futuristic data-viz mode and a clean executive dashboard mode.

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🛠️ How It Works (The Math)

The simulation engine treats a career as a Markov Chain-like process where state transitions are probabilistic but influenced by "Strategy Cards":

1. Base Probabilities: Every role (Junior -> CEO) has base promotion/attrition rates.
2. Multipliers:
   • Specialists get a 1.5x promotion multiplier early but 0.8x flexibility later.
   • Generalists maintain a steady 1.0x but gain 1.2x exit opportunities.
3. The "Pivot": Unemployment or stagnation triggers a "forced pivot," simulating real-world resilience.

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📷 Screenshots

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📦 Installation & Setup

Prerequisites

• Node.js & npm
• Python 3.10+

1. Clone the Repository

git clone https://github.com/Yash55-max/PathDiverge.git
cd PathDiverge

2. Backend Setup

Navigate to the backend directory and fire up the simulation engine:

cd backend
python -m venv venv
# Windows:
.\venv\Scripts\activate
# Mac/Linux:
source venv/bin/activate

pip install -r requirements.txt
uvicorn main:app --reload

The API will be live at http://127.0.0.1:8000

3. Frontend Setup

Launch the visualization dashboard:

cd frontend
npm install
npm run dev

Open http://localhost:5173 to start simulating.

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🔮 Future Roadmap

• Salary Projection Models: Integrating real-world salary bands (Levels.fyi data).
• Industry-Specific Simulations: Tech vs. Finance vs. Healthcare tracks.
• User Accounts: Save and share simulation runs.

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👨‍💻 Author

Yashwanth Ponnam
Building systems that model the real world.
GitHub Profile