Beginner-Friendly Guide to AWS Strands Agents

I've been exploring AWS Strands Agents recently, it's their open-source SDK for building AI agents with proper tool use, reasoning loops, and support for LLMs from OpenAI, Anthropic, Bedrock, LiteLLM Ollama, etc.

At first glance, I thought it’d be AWS-only and super vendor-locked. But turns out it’s fairly modular and works with local models too.

The core idea is simple: you define an agent by combining

• an LLM,
• a prompt or task,
• and a list of tools it can use.

The agent follows a loop: read the goal → plan → pick tools → execute → update → repeat. Think of it like a built-in agentic framework that handles planning and tool use internally.

To try it out, I built a small working agent from scratch:

• Used DeepSeek v3 as the model
• Added a simple tool that fetches weather data
• Set up the flow where the agent takes a task like “Should I go for a run today?” → checks the weather → gives a response

The SDK handled tool routing and output formatting way better than I expected. No LangChain or CrewAI needed.

If anyone wants to try it out or see how it works in action, I documented the whole thing in a short video here:

Also shared the code on GitHub for anyone who wants to fork or tweak it: Repo link

Would love to know what you're building with it!