Google is a leader in The Forrester Wave™: Public Cloud Platforms, Q3 2026
cloud.google.com·6d ago
Cloud & Infrastructure
The New Stack·2h ago·5 min read
Your AI agent failed. The model might not be the problem.
TL;DR
As AI agents are deployed in real-world applications, their unpredictability increases, revealing that failures often stem from issues beyond the model itself. Understanding these factors is crucial for improving AI reliability.
✦ Why It Matters
Evaluate your AI agent's environment and data quality to identify potential failure points today.
Key Takeaways
- Utilize OpenShell for better execution visibility in AI agents.
- Participate in SAFE to share and learn from agent failure insights.
- Focus on harness adjustments to improve agent performance.
- Capture detailed execution data to aid in debugging agent failures.
How It Works
OpenShell serves as a runtime environment that manages agent execution while capturing detailed information about the agent's decision-making process. This includes tracking the tools used, the reasoning behind decisions, and points where the agent encountered issues.
By analyzing this data, developers can pinpoint the source of failures more effectively.