Why did an error one agent made become the next step's ground truth?

Because the wrong output gets treated as fact by whatever reads it next. A wrong intermediate result is consumed downstream as input, and the step receiving it reasons correctly from a false premise, so its own output looks internally consistent even though the chain is now wrong. Every span involved is telling the truth about itself; the defect lives in the relationship between spans, not inside any one of them.

The effect compounds with depth. A controlled study of agent pipelines found output consistency falling from 100 percent at direct execution to 23.5 percent at ten hops, with a standard deviation of 22.1 at that depth, nearly as large as the mean, so read it as a direction rather than a precise number.

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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.

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

what's includedper organization
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30 days
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$10, one-time, for triage and root-cause analysis
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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