AWS launches AgentCore Optimization for AI agent quality
Amazon Web Services (AWS) has introduced AgentCore Optimization, a new preview service designed to enhance the quality of AI agents over time through a feedback loop.

What happened?
AWS has unveiled AgentCore Optimization, a supplemental service to manage performance degradation in AI agents. Now available in preview, the service seeks to identify and rectify issues that arise as AI models evolve, user behaviours shift, or prompts are reused in new contexts.
Key facts
| Tjänstnamn | AgentCore Optimization |
|---|---|
| Status | Förhandsversion (Preview) |
| Plattform | AWS (Amazon Web Services) |
”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. Agent quality quietly degrades.”
Why it matters
The need for AgentCore Optimization stems from the tendency for AI agent quality to deteriorate over time due to dynamic factors such as model updates and changing usage patterns. Through an "agent quality loop", the service allows developers to systematically improve and validate their AI agents in production environments.
Who is affected?
This service is primarily aimed at developers and enterprises hosting AI agents on the AWS platform. This includes teams working on AI applications who wish to ensure continuous performance and relevance for their AI solutions.
Impact on the EU
Not applicable for EU status. The service is globally available as a preview via AWS cloud infrastructure.
What else you should know
AgentCore Optimization is built on generating recommendations from production traces, validating these via batch evaluation and A/B testing, and subsequently implementing improvements with greater confidence.
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