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feat(blog): add Physical AI blog post#739

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agent-tasks/736
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feat(blog): add Physical AI blog post#739
Unshure wants to merge 3 commits intomainfrom
agent-tasks/736

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@Unshure Unshure commented Apr 3, 2026

Summary

Adds the "Building intelligent physical AI: From edge to cloud" blog post to the Strands documentation blog section, republished from the AWS Open Source Blog with proper canonical URL attribution.

Changes

  • New directory: src/content/blog/physical-ai/ with 6 media assets (1 GIF, 5 PNGs)
  • Authors: Added 3 new authors to authors.yaml: cagatay-cali, rachita-chandra, aaron-su
  • Blog post: Created src/content/blog/strands-physical-ai.mdx with full content, local image references, and Python syntax-highlighted code blocks
  • Internal links: Converted all strandsagents.com documentation URLs to internal relative paths (e.g., /docs/user-guide/concepts/multi-agent/agents-as-tools/) matching the pattern used by existing blog posts

Content sections

  • Introduction to physical AI and edge-cloud architecture
  • The edge-cloud continuum (System 1 vs System 2 thinking)
  • Progressive code journey: Ollama on edge → visual understanding → sensor integration → VLA models (NVIDIA GR00T) → SDK control (Boston Dynamics Spot) → edge-cloud bridging
  • Fleet learning with AgentCore Memory and Observability
  • Resource links

Resolves #736

- Create physical-ai/ subdirectory with 6 media assets
- Add 3 new authors (cagatay-cali, rachita-chandra, aaron-su)
- Create strands-physical-ai.mdx with frontmatter and placeholder

Resolves #736
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github-actions bot commented Apr 3, 2026

Documentation Preview Ready

Your documentation preview has been successfully deployed!

Preview URL: https://d3ehv1nix5p99z.cloudfront.net/pr-cms-739/docs/user-guide/quickstart/overview/

Updated at: 2026-04-06T21:12:37.922Z

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Unshure commented Apr 3, 2026

/strands can you copy the blog content yourself?

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Unshure commented Apr 6, 2026

/strands can you fix the links in the blog post that point to other pages on the docs page? They should follow this pattern when linking to another page on the docs site: Hooks

Convert 6 external strandsagents.com documentation links to internal
relative paths following the /docs/... pattern used by other blog posts:
- bidirectional streaming quickstart
- steering (plugins/steering, not experimental/steering)
- Ollama provider
- llama.cpp provider
- agents-as-tools
- Strands Agents homepage
@github-actions github-actions bot changed the title feat(blog): add infrastructure for Physical AI blog post feat(blog): add Physical AI blog post Apr 6, 2026
@Unshure Unshure closed this Apr 6, 2026
@Unshure Unshure reopened this Apr 6, 2026

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 complex reasoning while maintaining millisecond-level responsiveness for physical sensing and actuation?

This year has been transformative for agentic AI at AWS. We [launched Strands Agents in May 2025](https://aws.amazon.com/blogs/opensource/introducing-strands-agents-an-open-source-ai-agents-sdk/), bringing a simple developer experience and [model-driven approach](https://aws.amazon.com/blogs/opensource/strands-agents-and-the-model-driven-approach/) to agent development. In July, [we released version 1.0](https://aws.amazon.com/blogs/opensource/introducing-strands-agents-1-0-production-ready-multi-agent-orchestration-made-simple/) with multi-agent orchestration capabilities and [introduced Amazon Bedrock AgentCore](https://aws.amazon.com/blogs/aws/introducing-amazon-bedrock-agentcore-securely-deploy-and-operate-ai-agents-at-any-scale/) to accelerate AI agents to production at scale. At re:Invent 2025, we expanded Strands with the [TypeScript SDK](https://github.com/strands-agents/sdk-typescript), [evaluations](https://github.com/strands-agents/evals), [bidirectional streaming for voice agents](/docs/user-guide/concepts/bidirectional-streaming/quickstart/), and [steering for guiding agents within boundaries](/docs/user-guide/concepts/plugins/steering/). Today, we're exploring how these capabilities extend to the edge and physical AI, where agents don't just process information but work alongside us in the physical world.
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Issue: Cross-blog link uses external AWS URL instead of internal path

Line 21 links to the "model-driven approach" blog via the external AWS blog URL (https://aws.amazon.com/blogs/opensource/strands-agents-and-the-model-driven-approach/), but this blog post already exists internally at /blog/strands-agents-model-driven-approach/. Other blog posts in this repo (e.g., the steering blog) use internal cross-references for content that lives on this site.

Similarly, the "Strands Agents" and "version 1.0" blogs referenced in the same paragraph also exist as internal blog posts (introducing-strands-agents, introducing-strands-agent-sops, etc.).

Suggestion: Convert cross-references to other blog posts in this repo to internal paths (e.g., [model-driven approach](/blog/strands-agents-model-driven-approach/)) to keep readers on-site and ensure links don't break if the external URLs change.


This year has been transformative for agentic AI at AWS. We [launched Strands Agents in May 2025](https://aws.amazon.com/blogs/opensource/introducing-strands-agents-an-open-source-ai-agents-sdk/), bringing a simple developer experience and [model-driven approach](https://aws.amazon.com/blogs/opensource/strands-agents-and-the-model-driven-approach/) to agent development. In July, [we released version 1.0](https://aws.amazon.com/blogs/opensource/introducing-strands-agents-1-0-production-ready-multi-agent-orchestration-made-simple/) with multi-agent orchestration capabilities and [introduced Amazon Bedrock AgentCore](https://aws.amazon.com/blogs/aws/introducing-amazon-bedrock-agentcore-securely-deploy-and-operate-ai-agents-at-any-scale/) to accelerate AI agents to production at scale. At re:Invent 2025, we expanded Strands with the [TypeScript SDK](https://github.com/strands-agents/sdk-typescript), [evaluations](https://github.com/strands-agents/evals), [bidirectional streaming for voice agents](/docs/user-guide/concepts/bidirectional-streaming/quickstart/), and [steering for guiding agents within boundaries](/docs/user-guide/concepts/plugins/steering/). Today, we're exploring how these capabilities extend to the edge and physical AI, where agents don't just process information but work alongside us in the physical world.

![Robot demonstration](./physical-ai/edge-ai-1.gif)
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Issue: The GIF is 4.5MB which will impact page load time, especially on slower connections.

Suggestion: Consider compressing the GIF (tools like gifsicle can significantly reduce size) or converting to an optimized video format (MP4/WebM) wrapped in an HTML <video> tag with autoplay loop muted attributes, which typically achieves 80-90% size reduction over GIF.

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github-actions bot commented Apr 6, 2026

Assessment: Comment

This is a well-structured blog post republication that follows established patterns in the repo. The frontmatter, internal link conversions, image organization, and code formatting all look correct.

Review Details
  • Internal links: All /docs/ paths verified as pointing to valid pages. The pattern matches existing blog posts. However, cross-references to other blog posts on this site (e.g., the model-driven approach blog) still use external AWS blog URLs — these could be converted to internal /blog/... paths for consistency with how the steering blog cross-references other posts.
  • Media assets: The 4.5MB GIF is worth optimizing for page load performance, though there is precedent for large assets in the repo.
  • Content: Canonical URL is correct, authors are properly added, code blocks have appropriate syntax highlighting, and all image alt texts are present.

Overall the PR cleanly addresses the acceptance criteria in #736.

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[NEW CONTENT] Strands Physical AI

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