Braintrust releases behavior specs for supervising long-horizon agents
The standard, developed with Basis, defines and evaluates agent behavior across trajectories, with open source tools at agentbehavior.dev.
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AI observability platform
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In short: Braintrust expanded its AI observability platform with automated trace clustering, sub-second querying, and new SDKs for Python and Java.
The standard, developed with Basis, defines and evaluates agent behavior across trajectories, with open source tools at agentbehavior.dev.
It enables querying massive datasets in under a second, overcoming limitations of traditional databases.
It provides immediate traces and updates, optimized trace loading, and full-text search across prompts and responses.
Evals define measurable AI product quality through tests, hillclimbing, and flywheels using production data. They shift PM roles to coding quality signals.
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