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My most profitable AI trading bot turned $10,000 into $20,251—but it had one major problem that almost nobody in algorithmic trading talks about.

How do you know whether a trading bot is experiencing a completely normal losing streak—or whether its strategy has permanently stopped working?

In this complete guide, I’ll show you how to build your own automated AI trading system from a blank screen, backtest its strategies and connect everything to your broker.

Then I’ll make the system even better by adding an AI risk-management agent capable of monitoring every strategy, detecting abnormal performance and switching off bots that may have lost their edge.

You’ll see every tool, prompt and setup step required to recreate the complete system yourself—without needing to write the code manually.

## In this video, you’ll discover:

✅ Every tool required to build an automated AI trading bot
✅ How to connect Claude Code to TradingKit
✅ How to make Claude research and backtest strategies automatically
✅ How to use Claude’s scheduled loops to test new strategies continuously
✅ How to build a personal AI trading control panel
✅ How to inspect equity curves, monthly returns and backtest statistics
✅ How to verify every AI-generated strategy inside TradingView
✅ Why most profitable backtests fail when exposed to live markets
✅ How incubation and forward testing reveal unrealistic strategies
✅ How to connect TradingView alerts to your broker
✅ How to automate entries, stop losses, take profits and position sizing
✅ What happened when one of my best trading bots began to fail
✅ Why knowing when to switch off a bot is so difficult
✅ How the AI risk-management agent monitors strategy performance
✅ How equity-curve bands can identify abnormal drawdowns
✅ How rolling win rate and profit factor help detect a disappearing edge
✅ How Claude can disable a failing TradingView strategy automatically
✅ The rules I now follow before trusting any bot with real capital

## ⏰ Video Chapters

0: 00 – My Most Profitable AI Trading Bot’s Hidden Problem
0: 55 – The Complete AI Trading Roadmap
2: 00 – Tools Required to Build the System
4: 47 – Connecting Claude to the Trading Tools
6: 12 – Running the First Strategy Backtest
7: 00 – Making Claude Research Strategies Automatically
9: 28 – Building the AI Trading Control Panel
10: 46 – Verifying the Strategy in TradingView
11: 54 – Why Every Strategy Needs Forward Testing
13: 07 – Connecting TradingView to Your Broker
16: 34 – The Problem Almost Every Trading Tutorial Ignores
17: 00 – How One of My Best Trading Bots Failed
19: 00 – Building the AI Risk-Management Agent
20: 30 – The Rules Used to Switch Off Failing Bots
21: 47 – My Complete AI Trading Research Desk
22: 30 – What I Wish I Knew Before Trading Bots Live
24: 00 – Diversification and Final Lessons

## How the AI monitoring system works

The agent regularly checks each strategy against its original backtest and expected performance.

It monitors:

– Equity-curve deviation
– Rolling profit factor
– Rolling win rate
– Abnormal losing streaks
– Unexpected drawdowns
– Changes in live performance
– Active TradingView alerts

If a strategy moves outside its expected performance range, Claude can investigate the problem, send an alert and disable the corresponding TradingView automation.

This removes emotion from one of the hardest decisions in algorithmic trading: knowing when a previously profitable strategy should be switched off.

## Tools Used

👉🏻 Get the FREE Claude prompts, AI monitoring tools, workbooks, checklists and resources:
DM me “AI TRADING” on Instagram:
https://instagram.com/DaviddTech

Claude AI
Claude Code
TradingView
TradingKit
Strategy Factory AI
Trigger.trade
Bybit
MCP servers
AI trading agents
Strategy backtesting
Forward testing
Algorithmic risk management
Automated trading bots

⚠️ Everything shown in this video is for education and entertainment only—not financial advice.

A profitable backtest does not guarantee future results. Markets change, strategies lose their edge and even strong systems experience drawdowns. Every strategy should be independently verified and forward-tested using realistic fees and slippage before real capital is deployed.

Building a profitable trading bot is only the beginning.

The real edge is knowing when that bot is no longer profitable—and having a system capable of making that decision without emotion.

Trade smarter.
Test everything.
Let the data do the talking.

#AITrading #ClaudeAI #AlgorithmicTrading