In 2025–2026 your future customers will increasingly meet your product through AI agents, not Google. If ChatGPT cannot quote your docs and Perplexity cannot find your API spec — you are losing leads to competitors who optimised first.

⚠️ The Problem

Most SaaS sites are designed for humans browsing with JavaScript-heavy SPAs. LLM crawlers like GPTBot, ClaudeBot, and PerplexityBot do not run JS. They cannot follow your dynamic routes, parse your component-rendered tables, or trust your unstructured marketing copy. The result: when a founder asks Claude "what's the best tool for X?", you are not in the answer. Your competitor — with proper llms.txt, JSON-LD, and clean per-page Markdown — is.

💡 The Solution

I run a 26-criterion AI-readiness audit across five categories — Discovery (llms.txt, robots.txt, sitemap), Per-page artifacts (.md versions, JSON-LD, canonical), API spec (OpenAPI, examples, SDK), Content (curl examples, errors, glossary), and Hygiene (no-JS access, stable URLs, AI policy). You get a scored report with concrete fixes and an implementation roadmap to 75+/100.

For the implementation tier, I execute: llms.txt + llms-full.txt generation, JSON-LD TechArticle schema across the docs site, .md mirrors for SPA-rendered pages, OpenAPI cleanup, content rewrite under the CITABLE framework (source authority, recency, relevance, citations), and tracking of AI Visibility Score over time.

🎯 The Outcome

Your product becomes citable by AI agents. Concrete metrics that move: AI Visibility Score (typical lift from 18–40% baseline to 65%+), prominence in AI answers for category queries (0% → 50–70%), AI-attributed lead volume (3–5x in 90 days for typical B2B SaaS in our ICP). First-mover window in most niches is closing fast — competitors who move now own the AI answer surface for 12–18 months.