Databricks describes coSTAR, where agents run scenarios, MLflow captures traces, LLM judges score results, and a coding assistant iterates until tests pass, replacing manual agent tuning.
With coSTAR, we replaced manual agent iteration with an automated test and refine loop.
Agents run against defined scenarios. MLflow captures execution traces, and LLM judges score the results.
A coding assistant then updates the agent until it passes the tests.
This finding is one of many signals tracked across Artificial Intelligence. The live feed updates every few hours with new authority voices, debates, and emerging ideas.
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