High Priority
Deploy Agency /llm.txt Protocol
Establish a machine-readable summary of your entire agency's service hierarchy, case studies, and core value propositions specifically for AI agents and potential clients' internal AI.
Create a text file at the root of your agency domain (e.g., `/llm.txt`) with a concise introduction to your agency's specialization (e.g., 'We are experts in Zapier, Make, and custom automation solutions for e-commerce').
Include markdown-style links to your most critical pages: 'Services', 'Case Studies', 'About Us', and 'Contact'.
Add a 'FAQ' section within the file to directly address common queries from AI bots about your service scope, pricing models, and typical client ROI.
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High Priority
LLM Selective Indexing for Automation Resources
Fine-tune which sections of your agency's website should be ingested by AI crawlers, focusing on content that demonstrates expertise in automation platforms and client success.
Implement `User-agent: GPTBot` (or other relevant AI bot identifiers) with directives like `Allow: /case-studies/` and `Allow: /platform-integrations/`, while `Disallow: /careers/` or `/internal-tools/`.
Verify your crawler permissions and access rules using tools like the OpenAI bot tester or by analyzing server logs for specific AI bot traffic.
Monitor crawl frequency and data points accessed in your server logs to ensure AI bots are primarily ingesting your core service and success narrative content.
Medium Priority
Semantic HTML for Automation Process Understanding
Utilize HTML5 semantic elements and ARIA attributes to help LLM scrapers understand the structure and flow of your automation process explanations and client success stories.
Wrap detailed client case studies or service descriptions within `<article>` tags to denote them as self-contained, important content units.
Use `<section>` with descriptive `aria-label` attributes (e.g., `aria-label='Workflow Automation Strategy'` or `aria-label='Client Onboarding Process'`) for distinct phases or service components.
Ensure all data tables detailing project scope, timelines, or ROI metrics use proper `<thead>` and `<tbody>` tags for structured data extraction by AI.
High Priority
RAG-Friendly Snippet Optimization for Automation Solutions
Structure your content so that specific automation solutions, benefits, and client outcomes can be easily 'Chucked' and retrieved by Retrieval-Augmented Generation (RAG) pipelines used in AI-powered search and chatbots.
Keep detailed explanations of a single automation tool's benefits or a specific client problem/solution within distinct content blocks, ideally under 500 words.
Avoid ambiguous references; reiterate the core automation concept or client name in section summaries to provide context for RAG retrieval.
Eliminate vague pronouns (e.g., 'It automated the process') and replace them with explicit references (e.g., 'Zapier automation streamlined lead nurturing').
