Refining the Agent Using Observability › Making Observability a Habit
Michael BrenndoerferAugust 10, 20252 min read
AI Agent HandbookAll chapters Part 12 of 15Observability and Debugging - Peering Inside the Agent
Refining the Agent Using Observability › Making Observability a HabitOne section · Sections in this chapter8 / 11 ↓
Sections in this chapter11
The best way to ensure continuous improvement is to make observability part of your regular workflow. Here are some practical tips:
Schedule regular reviews: Block 30 minutes each week to review logs. Make it a recurring calendar event.
Create a dashboard: Build a simple dashboard that shows key metrics at a glance. It doesn't need to be fancy. Even a script that prints a summary is helpful.
In[2]:
Codedef print_weekly_summary(logs):
"""Print a summary of the week's agent performance."""
print("=== Weekly Agent Performance Summary ===\n")
print(f"Total queries: {len(logs)}")
# Tool usage
tool_calls = [
log.get("tool_call", {}).get("name")
for log in logs
if "tool_call" in log
]
print(f"Tool calls: {len(tool_calls)}")
# Success rate
errors = sum(1 for log in logs if log.get("error"))
success_rate = (len(logs) - errors) / len(logs) if logs else 0
print(f"Success rate: {success_rate:.1%}")
# Average response time
times = [log.get("response_time_ms", 0) for log in logs]
avg_time = sum(times) / len(times) if times else 0
print(f"Avg response time: {avg_time:.0f}ms")
print("\n" + "=" * 40)
## Run this every Monday morning
print_weekly_summary(last_week_logs)Keep an improvement log: Maintain a simple document where you record what you observed, what you changed, and what impact it had. This creates a history of your agent's evolution.
Share insights with your team: If you're working with others, share interesting patterns you've discovered. Someone else might have ideas for improvements you haven't considered.