Make structure explicit
Pages with strong heading hierarchy, clear procedure lists and compact examples are easier to ingest well. Weak structure forces extraction tools to guess where meaning begins and ends.
Technical blogTechnical article
How to optimize websites for AI consumption
Optimizing websites for AI does not mean writing robotic prose. It means making meaningful structure easier to extract, reuse and compress into context windows.
Primary use
Practical guidance for turning browser-first pages into machine-friendly content for agents and RAG.
Recommended flow
Fetch, clean, measure tokens, then hand consistent Markdown to agents or retrieval systems.
Next step
Use the Playground to compare raw HTML against optimized output before integrating the API.
Reduce repeated clutter
If every page repeats the same promotional rail or giant footer, AI systems pay that cost every time. Cleaning that noise once at ingestion is often the highest leverage improvement.
Internal links
Related technical paths
Core positioning
AI ingestion infrastructure for websites
Normalize public web content into consistent, low-noise context that AI systems can index, retrieve and reason over.
Preparation layer
LLM-ready content from messy HTML
Prepare documents for models with clean headings, preserved code and lower-noise context windows.
Token efficiency
Context optimization for LLM retrieval
Reduce noisy HTML and preserve semantic structure so every prompt and chunk carries more useful signal per token.