Optimizing agent system prompts with Amazon Bedrock AgentCore
Amazon's reflector engine turns agent failures into auto-fixes—no manual prompt engineering required.
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.
The key facts
10 to knowAgentCore 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
Go to the source
AWS Machine Learning Blogaws.amazon.com
Publisher excerpt: 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…