Optimizing agent system prompts with Amazon Bedrock AgentCore

This article explains how Amazon Bedrock AgentCore's system prompt optimizer automatically improves agent quality by analyzing production traces and recommending configuration changes.

• Single Agent Reflector reviews all traces in one pass to propose system prompt edits, achieving 81.55% on AppWorld in 6 minutes
• Sub-Agent Reflector uses independent trace analysis by multiple agents to identify diverse failure modes, reaching 95.83% on AppWorld
• Guardrails prevent overfitting by limiting prompt growth, enforcing safety standards, and avoiding verbatim trace phrases
• Single Agent Reflector offers best quality-per-cost trade-off; Sub-Agent Reflector achieves highest quality on benchmarks
• Reflector agents use shell tools to inspect trace files, compare successes and failures, and synthesize findings into configuration updates
• Recommendations include explanations for review before offline evaluation and A/B testing on live traffic

AgentCore optimization automates agent improvement through trace-based evidence, evaluation signals, and validated configuration changes.