AgentsSeptember 16, 2026via AWS Machine Learning Blog
Optimizing agent system prompts with Amazon Bedrock AgentCore
Why it matters
AgentCore's system prompt optimizer addresses a critical agent reliability challenge: production agents often fail silently or degrade over time. This tool automates the feedback loop from deployment traces to configuration changes, letting practitioners optimize agents without constant manual tuning.
Key signals
- AgentCore feature: system prompt optimizer with reflector engine
- Workflow: production traces → proposed config changes → validation before promotion
- Includes benchmarks for Single Agent and Sub-Agent Reflectors
- Targets agent reliability and performance optimization in production
- Part of Amazon Bedrock agent platform
- AgentCore feature: automated system prompt optimization from production traces
- Reflector engine validates proposed changes before promotion to production
- Benchmark results included for Single Agent and Sub-Agent Reflectors
- Targets enterprises running agents at scale, not early pilots
- AWS Bedrock product line; part of agent platform maturation
The hook
Amazon's reflector engine turns agent failures into auto-fixes—no manual prompt engineering required.
AgentCore optimization turns production traces into proposed configuration changes, then validates them before promotion. This technical companion to the launch post explains how the system prompt optimizer's reflector engine works and shares benchmark results for the Single Agent and Sub-Agent Refl…