The Context

I built 6 crypto trading bots using AI assistance. Most of that work was done with Claude Code, but I’ve also used ChatGPT (with and without Code Interpreter) for comparison.

This isn’t a general “which AI is better” post. This is specifically about building trading bots — writing Python, debugging exchange APIs, and iterating on complex financial logic.

Claude Code: What It Does Well

1. Working With Your Actual Codebase

Claude Code runs in your terminal. It reads your files, understands your project structure, and edits code in place. When I say “fix the trailing stop bug in bot_trendfollow.py line 342,” it opens the file, finds the line, understands the context, and makes a surgical edit.

This is a massive advantage for iterative development. You’re not copying and pasting code back and forth.

2. Complex Multi-File Changes

“Add separate long/short parameters across the bot and the backtest” — this touches 5+ files and 50+ locations. Claude Code navigates the project, finds all the relevant code, and makes consistent changes.

3. Debugging With Context

When my bot threw an error at 3 AM, I could paste the error and Claude Code would:

  • Read the relevant source file
  • Understand the full function context
  • Trace the call chain
  • Identify the root cause

Not just pattern-matching on the error message — actually understanding the code.

4. Iterative Refinement

“Now add error handling to that function. Actually, also make it retry on network errors. And log each attempt.” — Claude Code applies each change to the existing code without losing context.

Claude Code: What It Does Poorly

1. Strategy Design

Claude Code will implement whatever strategy you describe. It will not tell you the strategy is bad. I asked it to build a grid bot — it built a perfect grid bot that was structurally doomed in trending markets.

AI doesn’t have market intuition. You need to know what to build.

2. Statistical Judgment

“Is this backtest overfitting?” — Claude can list signs of overfitting, but it can’t look at your specific results and give you a confident assessment. It doesn’t have the experience of seeing hundreds of backtest results.

3. Very Long Sessions

After many iterations in a single conversation, context can drift. Variables from earlier discussions get mixed up. Starting a fresh conversation for new features often produces better results.

ChatGPT: What It Does Well

1. Explaining Concepts

“Explain the Choppiness Index in simple terms” — ChatGPT is excellent at educational explanations. When I needed to understand a new indicator before implementing it, ChatGPT was my first stop.

2. Quick Prototypes

For throwaway scripts and quick calculations, ChatGPT with Code Interpreter is fast. “Calculate the risk-reward ratio for these parameters” — done in seconds with a visual chart.

3. Research

“What are common crypto trading strategies for 5-minute timeframes?” — ChatGPT provides a broader survey of ideas. Good for the brainstorming phase.

ChatGPT: What It Does Poorly

1. Working With Your Files

ChatGPT doesn’t see your codebase. You have to paste code, which loses context. When your bot spans multiple files with shared state and config, this is painful.

2. Consistency Across Changes

“Add this feature to the bot” — ChatGPT gives you a code snippet. You paste it in. It doesn’t know about the other 500 lines in your file. Merge conflicts, inconsistent variable names, and subtle integration bugs are common.

3. Exchange-Specific Details

ChatGPT’s knowledge of Binance Futures API quirks is hit-or-miss. The algo order issue (STOP orders not being findable via normal endpoints) — ChatGPT didn’t know about this. Claude Code found it by reading the ccxt source.

What I Actually Use

Task Tool Why
Writing bot code Claude Code Direct file access, context awareness
Debugging Claude Code Can read actual error + source code
Strategy research ChatGPT Broader knowledge base
Concept explanation ChatGPT Better at teaching
Backtest implementation Claude Code Multi-file consistency
Quick calculations ChatGPT + Code Interpreter Visual output
Refactoring Claude Code Understands full project

80% Claude Code, 20% ChatGPT — that’s my actual split.

The Shared Limitation

Neither tool will:

  • Tell you if your strategy has real edge
  • Warn you about overfitting
  • Know the current market conditions
  • Replace your judgment on risk

AI is the builder. You are the architect.

The strategies that work in my portfolio weren’t designed by AI. They were designed by me, through reading, experimentation, and failure. AI just writes the code faster than I can.

Advice for Beginners

  1. Start with ChatGPT to learn concepts and build your first prototype
  2. Move to Claude Code when you have a project with multiple files that need to work together
  3. Never deploy AI-generated code without reading every line
  4. Test relentlessly — AI writes confident-looking code that sometimes has subtle bugs

The AI doesn’t know your risk tolerance, your account size, or your sleep schedule. It builds what you ask for. Make sure you’re asking for the right thing.

The best AI for trading bots is whichever one you verify most carefully.