This video from SMB Capital explores how day traders can use the AI tool Claude to build “operational infrastructure” and gain a professional edge without needing to be a coder. The speaker emphasizes that the real advantage in modern trading isn’t just about the strategy itself, but the efficiency of a trader’s workflow.
The video outlines five specific practices to transition from a manual trader to a “Tier 3” trader who uses AI for institutional-level preparation and analysis:
1. Custom Price Alerts
Instead of relying on basic platform alerts (like simple price crosses), you can use Claude to write Pine Script (for TradingView) or ThinkScript (for Thinkorswim) code. This allows for “surgical precision” alerts based on complex criteria, such as a breakout of the 30-minute opening range combined with specific volume confirmation and VWAP positioning.
2. Pre-Market Game Plan Automation
You can create a reusable template in Claude to analyze your daily watchlist. By pasting in overnight news headlines and pre-market data, Claude can prioritize your stocks, identify key levels, and suggest potential setup types (e.g., VWAP bounce or momentum continuation). This reduces 60 minutes of manual research into a 5-minute automated process.
3. Custom Performance Analysis
The speaker demonstrates how to prompt Claude to write a Python script that analyzes your trade history (CSV files). This goes beyond basic P&L to find deep patterns, such as identifying which hours of the day or which specific setups are actually losing you money. This objective data helps remove “self-deception” and highlights blind spots that are hard to see manually.
4. Custom Order Entry and Exit Logic
Traders can use AI to build sophisticated exit strategies that aren’t standard on most platforms, such as a two-bar trailing stop that automatically moves up with market structure. This helps remove emotion from the selling process by making exits systematic and structural.
5. The AI Trade Autopsy
After the market closes, you can upload a screenshot of your trade and provide Claude with your entry/exit logic and emotional context. Claude acts as a “performance coach,” providing an objective report on whether you followed your rules, what mistakes were made, and what specific area you should focus on for improvement.
Key Principles for Using AI in Trading:
- Specificity is Everything: Vague prompts yield poor results. You must provide detailed technical requirements and context.
- Iterate and Refine: The first output is rarely perfect. You should expect to spend time “chatting” with the AI to tweak and test the code or analysis.
- Verify, Don’t Blindly Trust: Always test AI-generated code in a paper trading environment or “break it” to understand the logic before using real capital.
- Focus on Bottlenecks: The speaker suggests picking just one of these five practices—whichever solves your biggest current struggle—and focusing on it for two weeks to build a compounding advantage.