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# Debugging multi-agent AI: When the failure is in the space between agents

**[Sentry Engineering](https://daily.dev/sources/sentry)** · 13 min read · 0 upvotes · 0 comments

## Summary

Building multi-agent AI systems introduces debugging challenges that single-agent monitoring can't address. When agents orchestrate other agents, failures can originate silently in one agent's tool call and cascade through the pipeline, corrupting downstream outputs without any error being thrown. A concrete example traces a bug where a Skeptic agent's web_search returned weak results, causing a Synthesizer agent to produce lopsided analysis — a problem only visible by inspecting full cross-agent traces. Key debugging principles include capturing prompts and tool outputs at every agent boundary, naming agents clearly, comparing parallel agents for asymmetry in tool call counts and token usage, sampling at 100%, and alerting on per-agent tool failure rates rather than global averages. Sentry auto-instruments OpenAI Agents SDK and LangGraph, creating nested spans for agent invocations, tool calls, and LLM requests.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://blog.sentry.io/debugging-multi-agent-ai-when-the-failure-is-in-the-space-between-agents>

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---

Tags: [#devops](https://daily.dev/tags/devops), [#ai-agents](https://daily.dev/tags/ai-agents), [#observability](https://daily.dev/tags/observability)

[View this post on daily.dev](https://daily.dev/posts/debugging-multi-agent-ai-when-the-failure-is-in-the-space-between-agents-azkgweaxh)

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