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I challenged myself to build a quantitative trading bot from scratch in just 24 hours. The goal? To automate trading on Kalshi using real-time market data and make profit. I leveraged senior systems engineering principles to design the architecture, integrated the Coinbase API for data, and deployed a live Python bot to execute trades. This video documents the journey—the code, the strategy, the bugs, and the final results of letting an AI trade real capital. Whether you're interested in software engineering, ML, or algorithmic trading, this is a behind-the-scenes look at what it takes to build a complex system under extreme time pressure. 🚀 Want to build systems like this? Connect with senior mentors at Expert Circle to accelerate your engineering career: 👉 https://expertcircle.live ⚡ THE CHALLENGE Starting Balance: $39.79 Goal: $100.0 & Automate Profitability Status: Need Followup 🛠️ THE TECH STACK Language: Python IDE: Cursor (AI Code Editor) Market Data: Coinbase API Platform: Kalshi (Prediction Market) ML Model: Logistic Regression ⏱️ TIMESTAMPS 0:00 - Intro 0:11 - The 24-Hour Trading Bot Challenge 0:22 - What is Kalshi? 0:35 - Bitcoin Up or Down - 15 minutes 0:54 - Integrate CoinBase and Kalshi 1:30 - 1st Live Order 2:00 - Winning and Losing Bets 2:18 - Momentum Strategy 2:51 - ML Model 3:27 - Making Money! 4:56 - Losing Money... 5:46 - Next Step 6:26 - ExpertCircle.live DISCLAIMER: This video is for entertainment and educational purposes only. This is not financial advice. Algorithmic trading involves risk. #Kalshi #TradingBot #Python #MachineLearning #SystemDesign #CodingChallenge