Use when working with AWS Strands Agents SDK or Amazon Bedrock AgentCore platform for building AI agents. Provides architecture guidance, implementation patterns, deployment strategies, observability, quality evaluations, multi-agent orchestration, and MCP server integration.
Use when working with AWS Strands Agents SDK or Amazon Bedrock AgentCore platform for building AI agents. Provides architecture guidance, implementation patterns, deployment strategies, observability, quality evaluations, multi-agent orchestration, and MCP server integration.
AWS Strands Agents & AgentCore
Overview
AWS Strands Agents SDK: Open-source Python framework for building AI agents with model-driven orchestration (minimal code, model decides tool usage)
Amazon Bedrock AgentCore: Enterprise platform for deploying, operating, and scaling agents in production
Relationship: Strands SDK runs standalone OR with AgentCore platform services. AgentCore is optional but provides enterprise features (8hr runtime, streaming, memory, identity, observability).
Key Concept: Strands Agents delegates orchestration to the model rather than requiring explicit control flow code.
# Traditional: Manual orchestration (avoid)whilenot done:
if needs_research:
result = research_tool()
elif needs_analysis:
result = analysis_tool()
# Strands: Model decides (prefer)
agent = Agent(
system_prompt="You are a research analyst. Use tools to answer questions.",
tools=[research_tool, analysis_tool]
)
result = agent("What are the top tech trends?")
automatically orchestrates: research_tool → analysis_tool → respond
Selection
Primary Provider: Anthropic Claude via AWS Bedrock
Model ID Format: anthropic.claude-{model}-{version}
Current Models (as of January 2025):
anthropic.claude-sonnet-4-5-20250929-v1:0 - Production
from strands import Agent
from strands.models import BedrockModel
from strands.session import DynamoDBSessionManager
from strands.agent.conversation_manager import SlidingWindowConversationManager
agent = Agent(
agent_id="my-agent",
model=BedrockModel(model_id="anthropic.claude-sonnet-4-5-20250929-v1:0"),
system_prompt="You are helpful.",
tools=[tool1, tool2],
session_manager=DynamoDBSessionManager(table_name="sessions"),
conversation_manager=SlidingWindowConversationManager(max_messages=20)
)
result = agent("Process this request")
from strands.observability import StrandsTelemetry
# Development
telemetry = StrandsTelemetry().setup_console_exporter()
# Production
telemetry = StrandsTelemetry().setup_otlp_exporter()
