System Prompt Optimization Introduced for Amazon Bedrock AgentCore

Amazon Web Services has detailed the AgentCore optimization capability designed to elevate the quality of AI agents under Amazon Bedrock AgentCore. Traditionally executed manually, this process can now be automated using production traces.

Automated Optimization Process

The optimization of low-scoring agents is automated through the use of production traces, and configuration changes are recommended.

The proposed changes are validated through offline batch evaluation and online A/B testing, deploying the ones that yield the best results.

Reflective Agent Mechanism

The system uses the AgentCore Observability feature to record agent traces, which are analyzed by a system prompt optimizer.

The reflective agent, reviewing evaluated behaviors, utilizes file system and shell tools to avoid exceeding context window limits.

Security and Variants

Before recommendations are applied, they are subjected to platform-level checks such as length limits, safety controls, and a prohibition on verbatim phrase reuse to prevent overfitting.

The system includes two variants: the highly efficient Single Agent Reflector and the Sub-Agent Reflector, which achieves higher success rates.