Why did a downstream agent get worse when its own code never changed?

Because the cause isn’t always where the failure shows up. In a multi-agent system, one agent’s output is another’s input, so a routing agent that starts summarizing differently, or a retrieval step that starts returning different documents, changes what a downstream agent has to work with, even though nobody touched that downstream agent’s code. Its own commit history stays clean and its own prompt hasn’t moved, so a search scoped to just that agent finds nothing, because the search is looking in the wrong place. Attribution has to walk the dependency graph, not just one agent’s change history: check what changed for every upstream system the failing agent depends on, in the same window, and test whether that change explains the shift. The fix usually belongs upstream too, in whichever agent’s output actually moved, even though the regression was first noticed somewhere else.

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Two ways to run Tessary.

Tessary is an open-source agent reliability platform. Cloud and self-hosted run the same workflow on the OpenTelemetry traces your agent already emits.

Tessary Cloud

We host it for you. Send your first trace with nothing to deploy and no model key.

what's includedper organization
traces
10,000 per calendar month
stored trace data
1 GB
retention
30 days
model credit
$10, one-time, for triage and root-cause analysis
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Self-hosted Tessary

Run the open-source code on your own infrastructure with one command. Add your own model key for triage and root-cause analysis.

Self-host Tessary for me by following https://github.com/tessaryai/tessary/blob/main/setup.md

docker compose -f oci://docker.io/tessaryai/tessary:compose up -d -y