That Morning
At 10 a.m., opening Google Sheets on the Windows desktop, 140 order requests collected by Hamsters (automation bot) overnight were waiting. As usual, I started scanning through them one by one to spot anomalies, when suddenly the idea came to try Claude Code.
The instruction was simple. "Review the order data and find cases where the quantity the buyer requested doesn't match the actual items in the order."
Exactly 1 minute 23 seconds later, the result appeared.
Errors Found: 4 cases
- Order #2847: Requested 1,200 units, actual total 950 units (250 short)
- Order #2891: Buyer requested "2 types," but order form shows 3 types
- Order #2908: Color code mismatch (buyer requested "BLU-001" but "BLU-002" entered)
- Order #2951: Delivery date error (requested: 30 days, entered: 60 days)
Scanning 140 orders by eye would take at least 30 minutes. The margin for error was also high.
Why Just One Minute?
The Limitations of Rule-Based Automation
Until now, our approach was "input conditional formulas in the sheet to flag errors."
=IF(SUMIF(range)≠input_value, "Error", "OK")
This method is precise but rigid. Every time a new type of error emerges (like color code mismatches), we have to add another formula.
What Claude Code Does
AI operates differently. It writes code to scan all 140 items in a single execution. Throughout the process, it:
• Understood the "context" of each order (did the buyer really want that color?)
• Remembered error patterns it had seen before
• Even detected unexpected error types
What Came Next?
The most surprising part came after. Once Claude Code found the errors, it automatically asked me:
"Of the 4 errors, #2847 and #2891 appear to be buyer-side entry mistakes. Should I draft confirmation emails first? I'll prepare templates."
When I said yes, multilingual confirmation email templates appeared in 3 minutes. They were even customized to match each buyer's previous communication style.
What We Learned
1. **Time savings are a side effect**. The real value is the confidence that "nothing gets missed."
2. **Corrections and solutions connect in one flow**. When problem detection and solution proposal happen automatically in sequence, the entire workflow changes.
3. **AI agents aren't the same as bots**. Hamsters only do "what they're told to do." Claude Code "judges what needs to happen and proposes it."
Not every trading company needs automation this sophisticated. But if your team handles hundreds of data entries daily, it's worth trying once.
Next week, we're planning to roll out this process to the main device as well.