ToolsThe story, in brief

Introducing the agent performance loop: AgentCore Optimization now in preview

AWS ships AgentCore Optimization: the first production feedback loop for AI agents. Batch eval + A/B testing built in.

Illustration of independent geometric mechanisms passing paper tasks along branching amber tracks.
AI agents and the coordination of work.AI illustration by KeyNews
The KeyNews take

Why it matters

AWS is addressing a real pain point for teams running agents in production—quality degradation over time. This tooling moves agent ops from manual tweaking to systematic optimization, lowering the bar for deploying reliable agents at scale.

The key facts

5 to know
  1. AgentCore Optimization now in preview

  2. Feature set includes production trace analysis, batch evaluation, A/B testing

  3. Solves agent quality degradation as models evolve and prompts drift

  4. AWS machine learning platform expansion into agent lifecycle management

  5. Product targets teams already shipping agents, not agents themselves

Go to the source

AWS Machine Learning Blogaws.amazon.com

Publisher excerpt: Generate recommendations from production traces, validate them with batch evaluation and A/B testing, and ship with confidence. AI agents that perform well at launch don’t stay that way. As models evolve, user behavior shifts, and prompts get reused in new contexts they were never designed for.…
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