# Strands Agents Published articles for Strands Agents. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Improving HCLS AI reasoning with open-source agent skills DevFeed: [Improving HCLS AI reasoning with open-source agent skills]() Original publisher: [Read original article]() Author: Michael Hsieh Published: 2026-09-16T19:00:00Z Content type: article Language: en Sources: [Artificial Intelligence]() Topics: [Agent Skills](), [Artificial Intelligence](), [foundation-models](), [Open Source](), [Bioinformatics](), [Medical imaging]() Tags: [agent-skills](), [agents](), [ai](), [ai-agents](), [amazon-bedrock](), [amazon-quick-suite](), [announcements](), [artificial-intelligence](), [foundation-models](), [generative-ai](), [healthcare](), [healthcare-and-life-sciences](), [intermediate-200](), [kiro](), [life-sciences](), [medical-imaging](), [open-source](), [strands-agents]() ### AI overview This post presents 38 open-source agent skills spanning 11 healthcare and life sciences domains. The skills encode domain decision procedures for AI agents, and the reported evaluation found a 70-86% head-to-head win rate over agents without the skills. ### Source excerpt AI agents on foundation models often misapply healthcare and life sciences decision frameworks, citing the right guideline but applying it incorrectly. This post shares 38 open-source agent skills across 11 HCLS domains that close this gap, with installation steps, three worked use cases, and a 410-prompt evaluation showing a 70-86% win rate. ## From zero-shot forecast to purchase order with Amazon Bedrock AgentCore DevFeed: [From zero-shot forecast to purchase order with Amazon Bedrock AgentCore]() Original publisher: [Read original article]() Author: Hyunsoo Kim, Ph.D. Published: 2026-09-11T14:08:01Z Content type: article Language: en Sources: [AWS Architecture Blog]() Topics: [AI Bots](), [Training AI Models](), [SDKs]() Tags: [advanced-300](), [agents](), [amazon-bedrock](), [amazon-bedrock-agentcore](), [automation](), [best-practices](), [orchestration](), [strands-agents](), [time-series](), [training](), [zero-shot]() ### AI overview An architecture article on using Amazon Chronos2 zero-shot forecasting and Bedrock AgentCore multi-agent orchestration to turn demand forecasts into validated purchase orders without per-product model training. ### Source excerpt Combine zero-shot forecasting with Amazon Chronos2 and multi-agent orchestration on Amazon Bedrock AgentCore to turn demand forecasts into validated purchase orders. No per-product model training, with business rules, auditability, and cost that scales to zero. ## Introducing strands-dynamodb-storage: Durable agent storage for the Strands Agents SDK DevFeed: [Introducing strands-dynamodb-storage: Durable agent storage for the Strands Agents SDK]() Original publisher: [Read original article]() Author: Lee Hannigan Published: 2026-09-02T15:48:06Z Content type: release Language: en Sources: [AWS Database Blog]() Topics: [AI Development](), [Database](), [SDKs](), [Amazon Bedrock](), [AWS Lambda]() Tags: [advanced-300](), [ai-agents](), [amazon-dynamodb](), [announcements](), [memory](), [open-source](), [python](), [storage](), [strands-agents](), [typescript](), [vector]() ### AI overview Amazon Web Services announces strands-dynamodb-storage, an open-source DynamoDB backend for the Strands Agents SDK. It stores agent session state, long-term memories, and transcripts in one DynamoDB table and supports semantic memory recall through a vector index. ### Source excerpt Announcing strands-dynamodb-storage, an open source Amazon DynamoDB storage backend for the Strands Agents SDK. Back a Strands agent's session state, long-term memories, and transcripts with one DynamoDB table in your own account, and give the agent semantic recall with a vector index on that same table. ## Extend Amazon Bedrock Guardrails to Tool Interactions Using the Strands Agents SDK DevFeed: [Extend Amazon Bedrock Guardrails to Tool Interactions Using the Strands Agents SDK]() Original publisher: [Read original article]() Author: Stephan Traub Published: 2026-08-27T16:20:05Z Content type: tutorial Language: en Sources: [AWS Security Blog]() Topics: [AI Bots](), [AWS IAM]() Tags: [ai-agents](), [amazon-bedrock](), [amazon-bedrock-guardrails](), [artificial-intelligence](), [aws-identity-and-access-management-iam](), [expert-400](), [generative-ai](), [model-context-protocol](), [security-blog](), [security-identity-compliance](), [strands-agents](), [tools](), [validation]() ### AI overview A tutorial on extending Amazon Bedrock Guardrails beyond model prompts and responses to validate AI-agent tool interactions with Strands Agents SDK lifecycle hooks. ### Source excerpt If you're running AI agents in production, Amazon Bedrock Guardrails protects the model boundary. But your agents also invoke tools, fetch external data, and communicate with other systems. That data flows outside the model boundary, where model-level guardrails can't reach. You can extend guardrail coverage to those interactions using three validation checkpoints built with the [...] ## How AgentFlo built AI sales agents with Amazon Bedrock AgentCore - Part 1 DevFeed: [How AgentFlo built AI sales agents with Amazon Bedrock AgentCore - Part 1]() Original publisher: [Read original article]() Author: Muhammad Musab Iqbal Published: 2026-08-20T00:32:52Z Content type: article Language: en Sources: [AWS Architecture Blog]() Topics: [AI Bots](), [AI Chat]() Tags: [ai-agents](), [amazon-bedrock-agentcore](), [customer-solutions](), [sales](), [scalability](), [strands-agents](), [whatsapp]() ### AI overview AgentFlo describes building always-on AI sales agents with Amazon Bedrock AgentCore and the Strands Agents SDK. Part 1 focuses on velocity, standardization, and scalability for commerce conversations. ### Source excerpt Learn how AgentFlo built always-on AI sales agents on Amazon Bedrock AgentCore and the Strands Agents SDK. Part 1 covers three pillars of production-grade agents--velocity, standardization, and scalability--including recipe-based deployment, tool routing through AgentCore Gateway, and elastic, stateful commerce conversations. ## Record, train, and deploy from one place with Strands Agents, LeRobot, and Hugging Face Storage Buckets DevFeed: [Record, train, and deploy from one place with Strands Agents, LeRobot, and Hugging Face Storage Buckets]() Original publisher: [Read original article]() Author: Sundar Raghavan; Steven Palma; Cagatay Cali; Arron Bailiss; Yin Song Published: 2026-08-13T17:16:04Z Content type: article Language: en Sources: [Hugging Face - Blog]() Topics: [lerobot](), [hugging face](), [cloud-infrastructure](), [dataset](), [SDKs](), [Command-line interface](), [Open Source]() Tags: [agents](), [apache](), [aws](), [cli](), [code](), [data](), [datasets](), [hub](), [hugging-face](), [lerobot](), [models](), [open](), [open-source](), [robots](), [storage](), [strands-agents](), [train](), [xet]() ### AI overview This article describes a continuous robotics data loop using Strands Agents, LeRobot, Hugging Face Hub, and Hugging Face Storage Buckets. It covers recording demonstrations, collecting episodes, training policies on growing datasets, deploying checkpoints, and using mutable Xet-backed storage to reduce repeated data transfers. ### Source excerpt Record, train, and deploy from one place with Strands Agents, LeRobot, and Hugging Face Storage Buckets You have an agent that can already record a demonstration and push it to the Hugging Face Hub. Now you want to run that loop continuously: collect episodes through the day, train a policy on the growing dataset, deploy it, and pull the next batch back to improve it. Run that loop once and every piece works. Run it every day and you start paying for the same byte transfers over and over. ## AWS Weekly Roundup: One-click Lambda setup prompt, OpenAI GPT-5.6 models on Bedrock, and more (July 20, 2026) DevFeed: [AWS Weekly Roundup: One-click Lambda setup prompt, OpenAI GPT-5.6 models on Bedrock, and more (July 20, 2026)]() Original publisher: [Read original article]() Author: Channy Yun (윤석찬) Published: 2026-07-20T16:37:34Z Content type: news Language: en Sources: [AWS News Blog]() Topics: [AI-assisted coding](), [Amazon S3](), [cursor](), [GitHub Copilot]() Tags: [ai-agent](), [amazon-bedrock](), [amazon-cognito](), [amazon-dynamodb](), [amazon-s3](), [amazon-simple-storage-service-s3](), [aws](), [aws-lambda](), [kiro](), [mcp](), [news](), [openai](), [serverless](), [strands-agents](), [week-in-review]() ### AI overview AWS weekly roundup covering a one-click Lambda prompt for configuring coding agents with serverless skills and an MCP server, OpenAI GPT-5.6 models on Amazon Bedrock, and same-day Amazon S3 storage-class transitions. ### Source excerpt Last week, my team visited Seoul to meet AWS Korea User Group (AWSKRUG) leaders. AWSKRUG is the largest cloud developer community in Korea, with 20 meetup groups organized by topic and area that collectively host over 100 events each year, primarily in Seoul. My team regularly visits countries across the Asia-Pacific region, listens to feedback [...] ## Open Protocols with the Strands Agents SDK DevFeed: [Open Protocols with the Strands Agents SDK]() Original publisher: [Read original article]() Author: Madhu Samhitha Vangara Published: 2026-07-16T17:29:21Z Content type: article Language: en Sources: [AWS Open Source Blog]() Topics: [SDKs]() Tags: [ai-agent](), [apis](), [mcp](), [open-source](), [strands-agents]() ### AI overview An overview of how the Strands Agents SDK uses open agent protocols, including MCP, to connect AI agents with tools, APIs, other agents, user interaction, and payments. ### Source excerpt If you are building AI agents, you have likely encountered a growing list of protocol acronyms--MCP, A2A, UTCP, AG-UI, and x402--that can feel overwhelming. The open source community has converged on several complementary protocols. An AI agent is only as useful as the systems it can reach: internal tools and data, the external APIs your [...] ## Building secure AI agents at scale: Introducing Loom for AWS DevFeed: [Building secure AI agents at scale: Introducing Loom for AWS]() Original publisher: [Read original article]() Author: Heeki Park Published: 2026-07-09T21:16:33Z Content type: article Language: en Sources: [AWS Open Source Blog]() Topics: [AI Agent](), [Security](), [Amazon Web Services](), [Amazon Bedrock](), [Authorization](), [API](), [Serverless](), [Back end](), [Inference](), [Python](), [Low code](), [No-code]() Tags: [agentic](), [agents](), [ai](), [ai-agent](), [ai-agents](), [amazon-bedrock-agentcore](), [api](), [aws](), [backend](), [code](), [deployment](), [mcp](), [model](), [no-code](), [open-source](), [python](), [security](), [serverless](), [strands-agents]() ### AI overview Loom for AWS is an enterprise-grade platform for building, deploying, and operating secure AI agents at scale. It combines AWS Strands Agents with Amazon Bedrock AgentCore and provides management, authorization, identity integration, lifecycle controls, memory, MCP and A2A integrations, governance, and usage tracking. Loom supports low-code Python agents and no-code deployment through AgentCore's managed harness. ### Source excerpt As organizations move to adopt agentic capabilities to accelerate their business objectives, they are challenged with enabling those capabilities within a security and governance framework that complies with enterprise requirements. Some organizations lean into the promise of serverless capabilities, as those fully managed services enable them to build fast and deliver customer value quickly. Amazon [...] ## Protect AWS Strands Agents with Datadog AI Guard DevFeed: [Protect AWS Strands Agents with Datadog AI Guard]() Original publisher: [Read original article]() Author: Kola Akinnibi; Vijay George; Emmanuelle Lejeail; Alexa Levine Published: 2026-07-08T00:00:00Z Content type: article Language: en Sources: [Datadog | The Monitor blog]() Topics: [Strands Agents](), [Application Security](), [Security](), [Amazon Web Services](), [Orchestration](), [agent observability]() Tags: [agent](), [agent-observability](), [agentic](), [agents](), [ai](), [ai-agents](), [ai-security](), [app-api-protection](), [application-security](), [attacks](), [aws](), [monitor](), [orchestration](), [prompt-injection](), [responses](), [security](), [strands-agents](), [threat-detection](), [tool](), [tools]() ### AI overview Datadog AI Guard integrates with AWS Strands Agents through a Strands plugin that evaluates prompts, model responses, and tool interactions during agent execution. It uses Strands lifecycle hooks to monitor or block unsafe behavior, centralize enforcement, and detect multistep attacks in the context of a full agent session. ### Source excerpt Monitor and help protect AWS Strands Agents by using Datadog AI Guard to evaluate prompts, model responses, and tool calls inline. ## From the Hugging Face Hub to robot hardware with Strands Agents and LeRobot DevFeed: [From the Hugging Face Hub to robot hardware with Strands Agents and LeRobot]() Original publisher: [Read original article]() Author: Sundar Raghavan; Cagatay Cali Published: 2026-06-17T10:18:05Z Content type: tutorial Language: en Sources: [Hugging Face - Blog]() Topics: [AI Bots](), [SDKs]() Tags: [agents](), [hardware](), [hub](), [hugging-face](), [inference](), [integration](), [lerobot](), [mesh](), [robots](), [strands-agents]() ### AI overview A tutorial for using the Strands Robots SDK and LeRobot to record simulated demonstrations, run policies, deploy the same agent code to physical hardware, and coordinate robot fleets. ### Source excerpt You have a robot, a folder of demonstration data on the Hugging Face Hub, and a new task you want it to learn. Today that takes five separate tools: one to record new demonstrations, another to train, a third to test in simulation, custom code to deploy on hardware, and yet another to coordinate when you have more than one robot. The pieces work on their own. They don't talk to each other. ## Introducing Strands Labs: Get hands-on today with state-of-the-art, experimental approaches to agentic development DevFeed: [Introducing Strands Labs: Get hands-on today with state-of-the-art, experimental approaches to agentic development]() Original publisher: [Read original article]() Author: Joy Chakraborty Published: 2026-02-23T18:24:30Z Content type: release Language: en Sources: [AWS Open Source Blog]() Topics: [AI, ML & Data Engineering](), [SDKs]() Tags: [agentic-ai](), [agents](), [ai-development](), [github](), [open-source](), [physical-ai](), [python](), [robots](), [strands-agents](), [typescript]() ### AI overview AWS introduces Strands Labs, a separate GitHub organization for experimental agentic AI projects built around the open-source Strands Agents SDK. Its launch projects include Robots, Robots Sim, and AI Functions. ### Source excerpt We're introducing Strands Labs, a new Strands GitHub organization designed to give developers the ability to get hands-on with experimental, state-of-the-art approaches to agentic AI development. The Strands Agents SDK - available for both Python and TypeScript - has gained incredible traction in the developer community since we released it as open source in May [...] ## Building intelligent physical AI: From edge to cloud with Strands Agents, Bedrock AgentCore, Claude 4.5, NVIDIA GR00T, and Hugging Face LeRobot DevFeed: [Building intelligent physical AI: From edge to cloud with Strands Agents, Bedrock AgentCore, Claude 4.5, NVIDIA GR00T, and Hugging Face LeRobot]() Original publisher: [Read original article]() Author: Arron Bailiss Published: 2025-12-12T21:03:04Z Content type: article Language: en Sources: [AWS Open Source Blog]() Topics: [AI Bots]() Tags: [ai-agents](), [amazon-bedrock](), [amazon-bedrock-agentcore](), [artificial-intelligence](), [best-practices](), [cloud](), [edge](), [embedded](), [generative-ai](), [inference](), [jetson](), [latency](), [nvidia](), [open-source](), [physical-ai](), [robotics](), [strands-agents](), [technical-how-to]() ### AI overview An AWS article explores physical AI agents that combine cloud reasoning with low-latency edge execution. It demonstrates a robotic arm and a quadruped robot controlled through Strands Agents on NVIDIA Jetson hardware. ### Source excerpt Agentic AI systems are rapidly expanding beyond the digital world and into the physical, where AI agents perceive, reason, and act in real environments. As AI systems increasingly interact with the physical world through robotics, autonomous vehicles, and smart infrastructure, a fundamental question emerges: how do we build agents that leverage massive cloud compute for [...] ## clickhouse.build: An agentic CLI to accelerate Postgres apps with ClickHouse DevFeed: [clickhouse.build: An agentic CLI to accelerate Postgres apps with ClickHouse]() Original publisher: [Read original article]() Author: Ryadh Dahimene; Pete Hampton; Al Brown Published: 2025-12-02T00:00:00Z Content type: article Language: en Sources: [ClickHouse Blog]() Topics: [clickhouse](), [Command-line interface](), [Databases](), [TypeScript](), [Open Source](), [Amazon Bedrock](), [Strands Agents]() Tags: [agentic](), [amazon](), [amazon-bedrock](), [cli](), [clickhouse](), [open](), [open-source](), [postgres](), [sql](), [strands-agents](), [typescript]() ### AI overview The article introduces clickhouse.build, an open source agentic CLI that helps integrate ClickHouse into existing Postgres-backed TypeScript applications. It identifies analytical queries, plans required tables, synchronizes data to ClickHouse Cloud, and rewrites application code while preserving transactional workloads in Postgres and adding a feature flag for compatibility. ### Source excerpt clickhouse.build is an open source, agentic CLI that accelerates the adoption of ClickHouse within your existing Postgres-backed TypeScript application.