Faro Editorial
AI discoverability, explained.
Practical guides on AI readiness, structured data, llms.txt, and how to make sure AI agents find, understand, and recommend your business.
Structured Data for AI: The Properties That Actually Matter
AI agents now pull structured data directly from your site to answer user questions, bypassing traditional search results entirely. Get the properties wrong and you are invisible to ChatGPT, Perplexity, and Google AI Overviews. This guide tells marketers and SEO leads exactly which schema properties move the needle, which ones waste implementation time, and what Faro checks to catch the gaps before they cost you traffic.
How Claude Evaluates Business Websites for Recommendations
Claude and similar AI assistants are now shaping buying decisions at scale, yet most business websites are structured in ways that make them nearly invisible to these models. This article explains exactly what signals Claude reads when forming recommendations, why most sites fail those checks, and which practical fixes have the highest ROI. Marketers and SEO leads who act now have a real window to own positioning before their category becomes crowded.
The Complete Guide to AI Visibility for SaaS Companies
AI-referred traffic grew 10x in the past 12 months, yet most SaaS sites are structurally invisible to the agents generating it. This guide breaks down what AI visibility means for SaaS companies, what it costs to ignore it, and the specific steps marketers and growth leads should take right now. Practical, opinionated, and built on verified data.
AI Readiness Checklist: 10 Things to Fix Before Next Week
AI-referred traffic grew 10x in the past year, yet most brand sites still fail basic AI readiness checks. This practitioner-focused guide gives you a concrete AI readiness checklist you can work through this week, with specific fixes, tools, and the cost of doing nothing. If your site is invisible to AI agents, you are already losing ground to competitors who are not.
How Gemini Decides Which Businesses to Recommend
Gemini doesn't rank websites the way Google Search does. It selects businesses to recommend based on structured signals, entity clarity, and third-party corroboration. Most marketers are optimizing for the wrong thing. This guide explains exactly what Gemini looks for and gives you a step-by-step fix list.
AI Crawlers Ignore llms.txt 97% of the Time So Stop Making One
A 137,000-domain Ahrefs study published in June 2026 found that 97% of llms.txt files received zero requests from any bot or human. GPTBot, ClaudeBot, and their peers crawl HTML directly and ignore the file entirely. This article breaks down what the data actually shows, why llms.txt became a speculative SEO ritual, and which signals genuinely move AI citation frequency.
AI Readiness for B2B SaaS: What to Fix First
B2B software buyers are starting to let AI agents do the first pass of vendor research. This piece walks through exactly what a SaaS company needs in place so it doesn't get filtered out before a human ever sees the shortlist.
MCP's July 2026 Spec Deprecates Four Features Your Integration Probably Uses
The MCP 2026-07-28 specification formally deprecates four features: Roots, Sampling, Logging, and the legacy HTTP+SSE transport. Businesses exposing tools or data via MCP now have a 12-month countdown before Tier 1 SDKs drop support entirely. This guide explains what each deprecation means, what replaces it, and how to audit your integration before the clock runs out.
Schema Didn't Boost AI Citations. Here's What It Actually Does
A controlled study of 1,885 pages found adding JSON-LD produced no citation lift on ChatGPT, AI Mode, or AI Overviews. A separate retrieval test found five major AI systems read only visible HTML and ignored schema entirely. Schema is still worth publishing, but for accuracy rather than citations. The lever that actually moves is where you put your answer on the page.
42 articles published