Claude 4 Interleaved Thinking Enhances Strands AI Agents

Amazon Web Services (AWS) has unveiled how Claude 4's interleaved thinking beta feature enhances the capabilities of Strands Agents SDK, simplifying AI agent development for complex tasks.

Key Highlights:

• Model-Driven Approach: Strands Agents SDK eliminates rigid workflows by letting models like Claude 4 plan, chain thoughts, and call tools autonomously.
• Dynamic Event Loop: The SDK manages an event loop that:
  • Invokes the model
  • Handles tool execution
  • Updates context until task completion
• Example Use Case: Determining which city (Portland, Vancouver, Seattle, or New York) is closest to the International Space Station (ISS), including distance and vector calculations.

How Interleaved Thinking Works

Claude 4's new feature allows real-time reflection and plan adjustment during tool execution, reducing iterations and improving efficiency. Developers can enable this via Amazon Bedrock:

python from strands import Agent from strands.models import BedrockModel

model = BedrockModel( model_id="us.anthropic.claude-sonnet-4-20250514-v1:0", additional_request_fields={ "anthropic_beta": ["interleaved-thinking-2025-05-14"], "thinking": {"type": "enabled", "budget_tokens": 8000}, }, )

Benefits Over Traditional Methods

• Faster Execution: Interleaved thinking reduces redundant tool calls by allowing mid-loop corrections.
• Error Correction: Claude 4 can identify and fix calculation errors immediately (e.g., longitude miscalculations).
• Fluid Reasoning: Combines thought and action in single blocks rather than separate loops.

Additional Resources

AWS provides sample agents demonstrating interleaved thinking, including multi-agent systems. Developers are encouraged to explore the Strands SDK GitHub for more use cases.

Contributors: Jawhny Cooke, Vadim Omeltchenko, and Mark Roy