This Week's Key Achievements
1. Completed Bot Workload Distribution System
Bots running on the main Windows device and Mac mini were frequently conflicting. This week, we built a system using Claude Code that automatically determines work priorities for each bot.
The Hamsters team handles "order validation" from 9 AM to 11 AM, while the Puppies team manages "report generation" during other time slots.
The result showed a 20% increase in processing capacity per bot and a 5% reduction in error rates.
2. Unexpected Discovery: Bots Also Need "Break Time"
Initially, we tried running bots continuously without pause. However, analyzing the data revealed that bots working for over 30 minutes straight showed decreased accuracy. Now we schedule 5-minute automatic waiting periods each hour.
We realized bots experience "burnout" too, which fundamentally changed our team management approach.
3. Completed Collaboration Manual v1.0
The "Bot-to-Bot Collaboration Rules" documentation we started last week is now complete. It consists of 3 main sections:
• "Data Handoff": How one bot passes its results to the next
• "Conflict Prevention": Priority rules when multiple bots access the same file
• "Error Reporting": Immediate Slack notifications when issues occur
Thanks to this manual, the team's "autonomy" noticeably improved from mid-week onward.
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This Week's Lessons Learned
1. Automation Also Requires "Speed Control"
We initially focused only on processing speed, overlooking quality. This week proved that maintaining 95%+ accuracy is far more valuable than achieving a 20% speed boost.
2. Log Files Are True Treasure
Carefully analyzing each bot's work logs was the best decision this week. We discovered:
• Which time periods generate the most errors
• What data items get lost during bot-to-bot transfers
• Where each bot's workload is concentrated
3. The Importance of Listening to Your Team
The biggest reason the AI Dream Team is growing is our "regular meetings." Three suggestions from team members during our daily 15-minute morning briefing became this week's major improvements.
Automation is ultimately created by people.
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Next Week's Plans
Phase 1: Build "Real-Time Monitoring Dashboard" (Monday, Tuesday)
Currently, we can only analyze logs after work ends. Next week, we'll create a Google Sheets-based dashboard for real-time bot status monitoring.
Phase 2: Test "Auto-Recovery System" (Wednesday, Thursday)
Right now, bots stop when they encounter errors. We plan to use Claude Code to automatically resolve simple errors and only report complex issues to humans.
Phase 3: "Dream Team 2.0 Rules" Meeting (Friday)
Building on this week's success, we'll hold a meeting to set next month's goals. We'll discuss adding new bots and expanding our work scope.
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Final Thoughts
As a non-developer pursuing AI automation, I was initially uncertain about this path. But by accumulating small wins with the team, I'm now confident this is entirely achievable.
Next week, we'll continue learning with the Dream Team. If anyone faces similar challenges in their automation journey, please reach out. Our experience might just help you too.