LLM.txt & AI Crawler Setup Guide for Architecture firms

Create a text file at /architecture.txt with a concise introduction to your firm's specializations (e.g., sustainable design, urban planning, historical preservation).

Include markdown-style links to your most critical pages: 'Project Case Studies', 'Services', 'About Us', 'Team', and 'Contact'.

Add a 'Project Showcase FAQ' section to address common queries regarding project typologies, design methodologies, and sustainability certifications.

Implement `User-agent: ArchitectureAI Allow: /projects/ Allow: /services/ Disallow: /careers/ Disallow: /internal-memos/

Verify your crawler permissions using a simulated AI bot tester tool to ensure correct parsing of directives.

Monitor server logs for AI crawler activity (e.g., 'ArchitectureAI') to confirm they are accessing and indexing key portfolio and service pages.

Wrap individual project descriptions and case studies within `<article>` tags to denote distinct content units.

Use `<section>` tags with descriptive `aria-label` attributes for different project phases (e.g., 'Schematic Design', 'Construction Documentation', 'Post-Occupancy Evaluation') or service categories.

Ensure all project data tables (e.g., materials, dimensions, certifications) use proper `<thead>`, `<tbody>`, and `<th>` tags for structured data extraction by AI.

Maintain distinct project narratives or service explanations within coherent content blocks, ideally under 750 words, to facilitate precise RAG retrieval.

Avoid ambiguous references; explicitly state the project name, client type, or design challenge within each section summary.

Eliminate vague pronouns (e.g., 'it', 'this') and replace them with specific project names, building typologies, or architectural features for clarity in AI responses.