// why matched
This post is highly relevant as it directly addresses strategies for optimizing content for AI models (Perplexity, GPT) and Query Fanout (QFO), which are core components of AI Engine Optimization (AEO) and ensuring content is 'CrawlProof' for AI crawlers. The discussion about getting cited and finding workflows for content discovery and optimization is precisely what 'AI crawler readiness' and 'get cited in ChatGPT&Perplexity' entail.
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This is an excellent question directly addressing AEO and AI readiness. Your approach of using Perplexity/GPT for query research is a solid starting point for understanding user intent as interpreted by LLMs. To optimize further for QFO and AI Overviews, focus on creating highly comprehensive, authoritative, and clearly structured content that directly answers questions. Incorporate structured data (Schema.org) where relevant. Consider the implications of `llms.txt` and how to signal your content's utility to AI models. It's about anticipating what an AI would deem a 'best answer'.