#technical SEO
Cite Solutions briefs tagged technical SEO. Newest first.
How to Protect AI Retrieval During a Site Migration: Redirects, Canonicals, and Prompt QA
Most site migration checklists stop at rankings and broken links. This guide shows you how to preserve AI retrieval during a migration by protecting page purpose, redirect logic, canonical control, proof assets, and post-launch prompt QA.
How to Run an AEO Schema Audit That Aligns Entities, Answers, and Proof
Most schema work still stops at validation. This guide shows you how to audit schema for answer-engine performance by checking entity clarity, visible-answer parity, proof support, and page-type markup across the pages that drive AI visibility.
Google Just Defined a Second AEO. Here's What 'Agentic Engine Optimization' Means for Your Content.
Addy Osmani, Google Cloud AI's Director of Engineering, published a formal framework defining 'Agentic Engine Optimization' as distinct from Answer Engine Optimization. It covers five pillars, specific token budgets, and file-based discovery methods like llms.txt and AGENTS.md. Here is what B2B SaaS content teams should do about it.
How to Run a GEO Crawlability Audit That Improves AI Retrieval
A lot of teams keep publishing answer-engine content on top of weak technical foundations. This guide shows you how to audit crawlability, canonicals, internal links, sitemaps, and structured context so the right pages can actually be retrieved and reused by AI systems.
URL-Level Citation Tracking Is the Missing Layer in Most GEO Reporting
Domain-level citation counts are too coarse for serious GEO reporting. This guide shows operators exactly what to track at the URL level, why it makes recommendations defensible, and how to turn source intelligence into page-level fixes.
llms.txt: What It Is, What It Does, and Whether Your Site Actually Needs It
llms.txt is getting a lot of attention in GEO and AEO circles, but most of the commentary swings between hype and dismissal. Here's what the file actually does, what it cannot do, and when it is worth implementing.
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