Databricks has introduced Agent Bricks, a generative AI-driven interface that simplifies agent development using technologies acquired from MosaicML. Unlike a mere rebranding of the Mosaic Agent Platform, Agent Bricks provides an advanced abstraction layer designed for data professionals. Users can select various tasks, define agent types, and incorporate knowledge sources. The platform then generates custom evaluation benchmarks to optimize agents through techniques such as synthetic data generation and prompt engineering, thus enhancing performance and reducing operational costs.
Agent Bricks leverages AI to streamline agent development, providing data professionals with advanced tools to automate tasks and enhance agent performance through optimization.
Users of Agent Bricks can initiate the creation of agents by selecting tasks, defining agent types, and attaching knowledge sources, simplifying the agent building process.
Databricks CTO Hanlin Tang emphasized the automatic creation of custom evaluation benchmarks, illustrating with examples how this capability enriches task-specific agent optimization.
The focus of Agent Bricks is on efficiency, employing advanced methodologies like synthetic data and prompt engineering to refine agent efficacy and operational costs.
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