Humans vs LLMs

Product Introduction

1. Humans vs LLMs is a diagnostic tool that analyzes how large language models (LLMs) like ChatGPT, Gemini, and Claude interpret website content, structure, and accessibility elements. It identifies gaps in AI readability caused by JavaScript dependencies, missing metadata, and poor semantic markup.
2. The product provides actionable insights to optimize websites for AI-driven search and discovery, ensuring content is fully visible, interpretable, and rankable by LLMs. It bridges the gap between human-centric design and AI crawler requirements.

Main Features

1. The tool detects JavaScript-only content by rendering client-side elements like dynamic product lists or reviews, which LLMs cannot process, and flags them as invisible to AI crawlers.
2. It identifies missing alt text for images and empty ARIA labels for buttons or icons, replacing them with placeholders like "[Image: No Alt]" to highlight accessibility and SEO vulnerabilities.
3. The analyzer evaluates semantic structure by exposing misused heading tags, landmarks, or sections that cause LLMs to collapse content into unreadable blocks, harming AI summarization.
4. It strips away overstyled or decorative markup such as custom fonts, shadows, and background images, revealing only the text and structural elements LLMs actually parse.
5. The tool calculates content-to-code ratios by highlighting excessive nested divs and non-semantic wrappers that dilute meaningful content, reducing AI indexing accuracy.
6. It exposes invisible elements like hidden text, deferred scripts, or dynamically injected content not present in raw HTML, which LLMs cannot access during initial crawling.

Problems Solved

1. Websites risk losing visibility in AI-generated answers due to JavaScript-reliant content, poor semantic structure, and missing metadata that LLMs cannot process.
2. The product targets SEO professionals, web developers, and digital marketers who need to optimize sites for AI-driven search engines and chatbots like Gemini or ChatGPT.
3. Typical use cases include auditing e-commerce product pages for AI readability, fixing accessibility barriers that also hinder LLMs, and restructuring content to improve AI summarization accuracy.

Unique Advantages

1. Unlike traditional SEO tools, Humans vs LLMs simulates how multiple LLMs (ChatGPT, Gemini, Claude) process content, providing side-by-side comparisons of human vs AI views.
2. The tool innovates by combining accessibility audits with AI readiness checks, since missing alt text and ARIA labels impact both screen readers and LLMs.
3. It offers competitive advantages by focusing on emerging AI SEO factors like content-to-code ratios and semantic collapse, which standard crawlers ignore.

Frequently Asked Questions (FAQ)

1. How accurate is the LLM preview compared to real AI crawlers? The preview uses secure iframe rendering to approximate LLM processing but should be treated as a reference rather than a definitive representation due to variations in AI model updates.
2. Does this tool replace traditional SEO audits? No, it complements them by adding AI-specific checks like JavaScript content visibility and semantic structure analysis that conventional tools don’t prioritize.
3. Can it detect content loaded via AJAX or delayed scripts? Yes, it flags any content not present in the raw HTML during initial load, including elements injected via asynchronous scripts or lazy-loaded components.
4. How does it handle authentication-walled or paywalled content? The tool analyzes only publicly accessible HTML, so restricted content remains invisible to both LLMs and the audit.
5. What technical SEO factors does it prioritize for AI? Key focus areas include reducing JavaScript-dependent rendering, eliminating hidden text, and ensuring heading hierarchies align with LLM summarization patterns.