Unverified50% confidenceFactExact time
Observability in software engineering relies on the three pillars of logs, metrics, and distributed tracing; because Agent decision paths are dynamically generated, Agents additionally need to record the reasoning process, tool call parameters, intermediate observation results, and the basis for decisions.
1
Sources
50%
Confidence
Long-term
Relevance
10/23/2026
First Seen
Sources
Getting Started with Agent Application Development: From Concepts to Practice, Understanding AI Agents
bilibili李宏毅agent10/23/2026
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VerifiedTraditional observability relies on three pillars—logs, metrics, and distributed tracing—while Agent systems additionally require capturing reasoning traces.79% similarVerifiedObservability refers to complete logging and tracing of the input and output, tool call results, time consumption, and costs of each step of an Agent, in order to locate faults, evaluate quality, and optimize costs76% similarUnverifiedThe industry is exploring dedicated observability solutions for Agents, including tracing prompts and outputs of LLM calls, recording tool-call input parameters and return values, and drawing dependency topology graphs among Agents.76% similarUnverifiedObservability (recording every step of reasoning and tool call), error recovery (tool timeouts, API rate limiting, format parsing failures), and cost control are key factors determining whether an Agent can truly go live.76% similarUnverifiedThe core research methodology was to have three agents each execute on a unified task set, recording the type, frequency, and sequence of each tool call to form comparable behavioral profiles.76% similar
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