nqzaiBlogTag archive
Fragmented Organization and LocalBusiness markup — a different logo on the pricing page, a stale address in the footer schema, a sameAs link to a dead Twitter handle — quietly breaks the entity signal AI search systems use to recognize a brand. Here's how to audit it and fix it.
PDFs, images, and API responses have no HTML head to hold a canonical tag — Google's Link response header fills that gap, and most sites never configure it.
Tagged reading order, real alt text, and searchable text aren't just accessibility requirements — they're the same technical fixes that let Google, Bing, and AI answer engines actually parse your PDFs. Here's the checklist, the standards behind it, and where it breaks down.
A table that looks fine in a browser can still be invisible to an AI answer engine if it isn't built with real semantic markup. Here's what the research on table parsing, accessibility, and generative-engine optimization actually supports — and what it doesn't.
Link rot doesn't just annoy human readers — it removes the retrievable evidence AI search engines need to verify and cite your content. Here's a research-backed process for auditing and fixing dead citations in evergreen pages.
A working robots.txt for AI crawlers isn't a file you write once — it's a policy you maintain as OpenAI, Anthropic, Perplexity, Google, and Apple keep splitting one bot into three with different rules for training, search, and live answers.
Most AI crawlers read your raw HTML and never execute JavaScript — so the page a human sees in a browser and the page an AI engine actually indexes can be two different documents. Here's how to test both.
Canonical tags tell Google which duplicate wins. AI crawlers don't confirm they even read the tag — here's what actually shapes citations.
A data-backed look at schema.org markup and AI search: what's proven, what's marketing, and when structured data is still worth your engineering time.
