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AWS's release is a developer-tooling story: a 2B-parameter model that picks among predefined options (with reported latency and a 72.3% score on its own JevBench evaluation) and a sandbox that enforces policy on agent actions. The benchmark is self-reported and the sandbox is in preview, so independent testing will matter more than the headline numbers. For practitioners, the notable part is the design direction: smaller specialized models for routing and guardrails, paired with OS-level controls on what agents can execute.
AWS Introduces Strands Decider 2B and Strands Box for AI Agent Development
AWS has introduced two open-source projects for AI agent development: Strands Decider 2B, a small model designed to make decisions within agent workflows, and Strands Box, a sandbox for controlling agent execution. Both projects address different aspects of building agents that use tools, execute code, and interact with external systems. By Daniel Dominguez
AWS has introduced two open-source projects for AI agent development: Strands Decider 2B, a small model designed to make decisions within agent workflows, and Strands Box, a sandbox for controlling agent execution. Both projects address different aspects of building agents that use tools, execute code, and interact with external systems. Strands Decider 2B is a two-billion-parameter model designed to select between predefined options rather than generate lengthy text responses. It supports…
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