Running multiple AI agents (trading bots, content generators, monitors) quickly becomes chaos. I built a command center to manage them all from one place.
The Problem
If you're running AI agents like me:
- Trading monitor that runs 24/7
- Content bots that post on schedule
- Scraping agents that collect data
- Customer service bots
You end up with:
- Processes scattered across terminals
- No visibility into what's running
- Hard to restart/stop individual agents
- No centralized logging
- Memory/CPU usage unclear
The Solution
Agent Command Center provides:
1. Dashboard
Real-time view of all running agents:
- Status (running/stopped/error)
- CPU and memory usage
- Last action taken
- Uptime tracking
2. Process Management
# Start an agent
acc start crypto-monitor
# Stop gracefully
acc stop content-bot
# Restart with new config
acc restart scraper --config new_targets.yaml
# View logs
acc logs trading-agent --tail 50
3. Alerting
Get notified when:
- An agent crashes or hangs
- Memory usage exceeds threshold
- An agent hasn't produced output in X minutes
- Error rate spikes
4. Scheduling
Built-in cron-like scheduling:
- Run agents at specific times
- Set up recurring tasks
- Chain agents together (output of A feeds into B)
5. Logging & Analytics
- Centralized log aggregation
- Performance metrics per agent
- Cost tracking (API calls, compute time)
- Historical run data
Get the Agent Command Center and take control of your AI agent fleet.
How do you manage your AI agents? Would love to hear your setup.
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