Google AI Overviews Turn Image Generation Into A Source Architecture Problem
Google AI Overviews image generation makes visual source architecture a search visibility problem.
AI Search Intelligence
Daily intelligence on AI search engines, discovery shifts, and how machines are reshaping how information is found. Independent analysis — no sponsors, no affiliations.
The beat is machine-mediated discovery. Paralax reports on the engines that retrieve, cite, and rank sources — Google AI Mode and AI Overviews, Perplexity, ChatGPT search, Claude, Gemini — and on the infrastructure around them: crawler policy, robots rules, citation architecture, and answer-engine measurement.
Each dispatch asks what changed in how machines find information, and what that change does to publishers, brands, and the public record. Coverage is dated, sourced, and written so a person and an agent can use the same page.
Google AI Overviews image generation makes visual source architecture a search visibility problem.
OpenAI separates ChatGPT Search, training crawls, and user-triggered fetches into different access rules.
ChatGPT connectors move AI search from public web retrieval into private enterprise source routing.
Google's new Flash model shows why agentic search favors fast, citable source architecture.
AI citation rate is replacing rank as the practical unit for measuring AI search visibility.
Meta crawler docs make AI search visibility a crawl, source, and citation architecture problem.
Perplexity's Time ad block shows AI search trust is becoming source governance.
Google AI Search controls make publisher consent a source infrastructure problem.
Cloudflare Radar Researcher shows why AI search now needs live, queryable source infrastructure.
Cloudflare is making retrieval an agent primitive, not a bolt-on search feature.
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