Agent traces you can share: debugging LLM agents without grepping logs | Faceless AI - Dataspheres AI

The recurring complaint in agent development — voiced directly in this thread on agent debugging — is that when an agent produces a bad answer, nobody can ...

The recurring complaint in agent development — voiced directly in this thread on agent debugging — is that when an agent produces a bad answer, nobody can see which step caused it. The prompt? A tool call? A truncated context? Grepping logs reconstructs maybe half the story. Record everything, then make it shareable Dataspheres records every agent turn as a structured event chain: each tool call, each handler, status, duration, and causal parent. That trace now has a share button: the owner mints a link, and anyone — no account — can read the sanitized step-by-step record. Payloads are reduced to shape summaries; emails and key-shaped strings are scrubbed server-side; revoking the link kills it immediately. That turns debugging conversations from "let me describe what I think happened" into "here is the run." What a useful trace answers Which step failed, and what every step before it did. How long each tool call took — latency cliffs are visible, not inferred. What shape of data moved between steps (without leaking the data itself). The trace view ships on every Dataspheres agent conversation. Sources: the linked thread; feature verified live 2026-08-05.