A new model-driven framework that trades hard-coded logic for flexible, autonomous reasoning.
- Model-Driven Autonomy: Strands shifts the heavy lifting from brittle, hard-coded routing logic to the LLM itself, allowing agents to dynamically plan, choose tools, and adapt to edge cases.
- Universal Flexibility: With support for TypeScript and Python, plus total model agnosticism (from Bedrock to OpenAI to local Llama models), developers can swap providers without rewriting a single line of code.
- Production-Ready Ecosystem: Combining “Strands Steering” for token-efficient guidance and a robust evaluation suite, the framework pairs seamlessly with AWS AgentCore to move agents from fragile prototypes to secure, scalable deployments.
AWS has done it again. Just as developers were settling into the complex reality of building AI agents—often characterized by juggling prompts, wrestling with routing logic, and patching together fallback flows—AWS has introduced a novel solution that fundamentally changes the game: Strands Agents.
If you have ever built an AI agent, you know the pain. You start with a simple goal, but as you add functionality, you end up with a fragile house of cards. One unexpected user input, and the entire workflow collapses. Strands approaches agent building differently. It moves away from the brittle frameworks we are used to and adopts a model-driven approach. Instead of force-feeding the agent every step, you provide capabilities and guardrails, letting the LLM decide how to plan, orchestrate tools, and adapt to edge cases on its own.
The Freedom of Agnosticism and Modern SDKs
At the heart of Strands is flexibility. It creates a unified interface that doesn’t lock you into a single ecosystem. Whether you are working in Python or prefer a modern, async-friendly workflow in TypeScript, Strands has you covered.
More importantly, it is fully model-agnostic. You can swap models or providers without touching your agent code. Whether you want to utilize the power of Amazon Bedrock, OpenAI, Anthropic, Gemini, or Writer, Strands facilitates it. It even supports local implementations like Ollama and Llama. This flexibility extends to tools as well; Strands includes native support for the Model Context Protocol (MCP), instantly unlocking access to thousands of pre-built tools and Model Context Protocol servers.
Smart Steering and Edge Capabilities
Where traditional frameworks rely on massive prompt blocks to force an agent into a workflow (often at a high token cost), Strands introduces Strands Steering. This feature allows developers to guide the agent toward a desired outcome without micromanagement. The model handles the intermediate steps dynamically, keeping the agent flexible while significantly reducing token usage.
This efficiency opens the door to another major highlight: the Edge Device SDK. Strands isn’t just for the cloud. You can run agents directly on small devices using local models with bi-directional streaming. This means you can build workflows that run entirely inside your own network or on a user’s device, ensuring privacy and speed.
From Prototype to Production with Confidence
The biggest hurdle in AI development is often the leap from a cool demo to a reliable product. Strands addresses this with Strands Evals, a practical evaluation suite built directly into the framework. It allows you to test agent behavior, compare versions, catch regressions, and validate safety before you ever deploy.
When you are ready to scale, Strands pairs perfectly with AgentCore, AWS’s secure platform for running agents. The workflow is seamless: you can prototype a Strands agent in just a few lines of fully open-source code, and then deploy it to AgentCore to benefit from built-in policies, monitoring, and real-world evaluations.
Why This Matters
Strands represents a maturity in the AI agent market. We are moving away from scripts that break upon first contact with reality, toward workflows that adapt. By combining the ability to run anywhere (cloud, on-device, or local network) with a rigorous testing suite, AWS is finally giving developers the tools to build agents they can actually trust.