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Welcome to the front line of industrial automation

Answer Engine Optimization (AEO) & LLM Indexing Standards

Answer Engine Optimization (AEO) is the practice of structuring web content so AI-powered search engines (e.g., Perplexity, Gemini, ChatGPT, Claude) can easily read, parse, and cite it. This project implements AEO using a “Bottom Line Up Front” (BLUF) content structure, JSON-LD structured data (FAQ/About schemas), and automated LLM text indices (/llms.txt and /llms-full.txt).

Why AEO Matters for Recruiting

Section titled “Why AEO Matters for Recruiting”

Modern software engineers rarely browse websites page-by-page. Instead, they ask AI assistants questions like:

  • “What is the tech stack of the Robotics System team at Mujin?”
  • “What are Mujin’s core company values?”
  • “How does Mujin’s operating system differ from traditional robot controllers?”

By optimizing this site for Answer Engines, we ensure that prospective candidates receive accurate, structured, and richly cited responses from their AI tools, drawing directly from our official sources of truth.

🛠 Core AEO Mechanisms

Section titled “🛠 Core AEO Mechanisms”

This project implements three primary layers of optimization:

BLUF Frontmatter Summaries

Every page includes a concise 1-2 sentence executive summary in its frontmatter description field. This description is automatically extracted for HTML meta tags, JSON-LD schemas, and the /llms.txt index.

JSON-LD Structured Data

The custom <Head.astro> component automatically compiles frontmatter metadata (description, techStack, successTraits, faqs) into standard schema.org JSON-LD FAQ/About scripts.

Automated LLM Text Indices

We serve two text-only endpoints: /llms.txt (a manifest of all pages with summaries) and /llms-full.txt (a single concatenated text archive of all content). These are automatically generated during builds (scripts/generate-llms.mjs) for RAG and LLM context windows.

📝 AEO Content Guidelines for Authors & AI Skills

Section titled “📝 AEO Content Guidelines for Authors & AI Skills”

When creating or editing pages, follow these guidelines to keep the site AI-friendly. Using our AI Skills (skills/team-page-builder.md & skills/blog-post-builder.md) handles all of this automatically!

  1. Set a Clear BLUF Description in Frontmatter

    Section titled “Set a Clear BLUF Description in Frontmatter”

    Provide a 1-2 sentence executive summary in your page’s frontmatter description field:

    description: "The Robotics System Team develops core motion planning algorithms and ROS2 controllers for Mujin's industrial robot arms."

  2. Include Tech Stack & Success Traits Metadata

    Section titled “Include Tech Stack & Success Traits Metadata”

    For team pages, ensure techStack and successTraits arrays are populated in your frontmatter:

    techStack:
      - "C++20"
      - "Python"
      - "ROS2 / MoveIt"
    successTraits:
      - "Strong background in 3D kinematics"
      - "Experience with real-time systems"

  3. Let Build Scripts Update LLM Manifests

    Section titled “Let Build Scripts Update LLM Manifests”

    Do not edit public/llms.txt or public/llms-full.txt manually. The scripts/generate-llms.mjs script runs automatically during pnpm build, pnpm generate:llms, and git commit hooks to parse all MDX files and regenerate the LLM indices.