Debugging a silently failing AI workflow with Agent Core full-link observability

Description and use

The tutorial demonstrates using OTEL spans in openJiuwen Agent Core to detect silent failures in multi‑step AI pipelines.

Problem

A multi-step agent pipeline can silently return a wrong final output without raising errors, making the failure hard to detect until downstream teams notice.

Outcome

The tutorial demonstrates that full‑link observability via OTEL spans enables pinpointing silent failures in agent pipelines, improving debugging reliability.

Workflow

• Clone the tutorial repo and install dependencies
• Set required environment variables (OPENJIUWEN_API_KEY, etc.)
• Configure the ReActAgent with AgentCard and ReActAgentConfig
• Wrap each pipeline step in a custom OTEL span that records diagnostics
• Run the pipeline and collect spans via InMemorySpanExporter
• Query the exported spans for latency, token counts, and failure flags
• Identify the node where token count is zero or failure flag is set
• Fix the silent failure in that node
• Re‑run the pipeline to verify correct output

Evidence

The most difficult AI workflows to debug are the ones that don't crash.

Source

You will instrument a three-node pipeline (fetch → analyze → summarize) with OTEL-compatible spans

Source

Full-link observability in Agent Core means that every tool call, token count, and step latency is captured as a structured, OTEL-compatible span

Source