The complete library
AI visibility guides.
Every page, organized by purpose.
The complete map of Lynceus's AI visibility content — definitional pillars, technical mechanics for each AI assistant, vertical playbooks, measurement methodology, and honest competitor comparisons. Start with the cornerstone, then follow the path that fits your role.
By Sri · Last reviewed: May 2026
Cornerstone
Start here — the definitional pillar
The category-defining page. Read this first if you're new to AI visibility as a discipline.
Action layer
Diagnostic + action — find the gap, fix it
Three pages on diagnosing why your AI paragraph is broken and the methodology for engineering it.
Why your brand isn't in the AI paragraph
Seven concrete reasons ChatGPT, Claude, Gemini, and Perplexity skip your brand — and the engineering fix for each.
/why-your-brand-isnt-in-ai-paragraph/
How to optimize for AI citation
The complete 8-step framework. From prompt panel definition through monthly re-measurement, with worked examples and the four common mistakes.
/how-to-optimize-for-ai-citation/
How to run an AI visibility audit
Step-by-step methodology for running your own audit in 90 minutes. Six sections, interpretive playbook, plus the DIY-vs-hire decision framework.
/ai-visibility-audit-guide/
Technical mechanics
How each AI assistant works
Per-assistant deep-dives on the citation mechanics behind every AI surface. Read these to understand WHY a piece of content gets cited.
How ChatGPT cites brands
Training-data vs browsing-mode citation, source authority weighting, and the five signals that drive ChatGPT brand mentions.
/how-chatgpt-cites-brands/
How Claude cites sources
Anthropic's Claude weights primary sources heavily, requires evidence for brand recommendations, and reasons across long context. The mechanics behind Claude citation.
/how-claude-cites-sources/
How Perplexity works for brand citation
Search-native, citation-transparent, recency-rewarded. The three-stage pipeline behind every Perplexity response.
/how-perplexity-works/
How Gemini cites sources
Google integration, Knowledge Graph leverage, and the three Gemini surfaces — chat, AI Overviews, AI Mode. The mechanics that make traditional SEO authority compound here.
/how-gemini-cites-sources/
By industry
Vertical guides — by category
Category-specific playbooks for SaaS, ecommerce, and B2B. Same methodology, different prompt panels, different content priorities.
AI visibility for SaaS
Why technical buyers query AI more than any other category. The eight prompt patterns every SaaS should track, plus the four content types that win.
/ai-visibility-for-saas/
AI visibility for ecommerce
Where Reddit beats your product page (and how to fix it). The schema leverage, the unbranded query gap, and the four content types that win product-specific citations.
/ai-visibility-for-ecommerce/
AI visibility for B2B enterprise
6-18 month buying cycles, 6-10 stakeholders, compliance-intent prompts. The pre-RFP AI evaluation window and how to engineer for it.
/ai-visibility-for-b2b/
Field notes
Field notes — opinionated takes on recent shifts
Timely pieces on specific events in the AI search ecosystem. Less canonical than the pillars above, more reactive to what just happened.
Measurement layer
Measurement — what to track and how
Three pages on measuring AI impact, contrasting it with traditional traffic analytics, and choosing the right tooling tier.
How to measure AI visibility
The four core metrics — share of paragraph, mention frequency, citation source quality, competitive paragraph share — and the monthly measurement loop.
/how-to-measure-ai-visibility/
AI traffic vs Google traffic
AI assistants resolve queries without clicks, making most AI brand impressions invisible to traditional analytics. Why click-through is the wrong metric.
/ai-traffic-vs-google-traffic/
AI citation tracking tools
Complete landscape across five tiers — free, self-serve SaaS, enterprise platforms, done-for-you services. Pricing, features, and the choice framework based on team capacity.
/ai-citation-tracking-tools/
Definitions
Glossary — the category vocabulary
Definitional anchors for the AI visibility category's vocabulary. Short, citation-ready pages LLMs reach for when answering 'what is X' prompts.
Share of paragraph
The AI visibility primary metric. Formula, benchmarks, and how it differs from share of voice.
/share-of-paragraph/
Answer engine optimization (AEO)
Engineering content for answer engines. Definition, core tactics, and the relationship to GEO and LLMO.
/answer-engine-optimization/
Generative engine optimization (GEO)
Engineering content for ChatGPT, Claude, Gemini, and Perplexity. The four core tactics and SEO comparison.
/generative-engine-optimization/
LLM optimization (LLMO)
Engineering content for large language models. Citation mechanics and the LLMO vs prompt engineering distinction.
/llm-optimization/
Learn corpus
From the Learn corpus — short, question-led answers
The /learn corpus answers one question per page in under 1,200 words. These five sit closest to the guides above and are the ones the guides cite most.
How ChatGPT grounding works when it browses the web
What infrastructure browsing mode has historically drawn on, and what a publisher can verify from outside.
/learn/how-chatgpt-grounding-works
What is llms.txt, and what does it do?
A proposed plain-text map of a site's key pages for AI systems, and how it differs from robots.txt or a sitemap.
/learn/what-is-llms-txt
FAQ schema vs no schema: effect on AI citation
No AI answer engine publicly documents a citation benefit from FAQ schema. What the markup actually does, and why it might still be worth adding.
/learn/faq-schema-vs-no-schema-citation-impact
AEO vs. GEO vs. LLMO: what do they mean?
Three overlapping terms for optimizing content toward AI-generated answers, what each emphasizes, and where practitioners draw the lines.
/learn/aeo-vs-geo-vs-llmo
Citation vs. mention vs. recommendation, explained
Three different signals an AI answer can send about a brand, why they are not interchangeable, and how to tell which one a page is earning.
/learn/citation-vs-mention-vs-recommendation
Comparison pages
Lynceus vs the alternatives
Honest comparisons with named competitors. Each page covers positioning, pricing where published, ideal customer for each option, and the third-path framing.
Lynceus vs Profound
Enterprise tooling-only SaaS vs hybrid measurement + content engineering. When each fits.
/lynceus-vs-profound/
Lynceus vs Peec AI
Self-serve SaaS with transparent tiered pricing vs done-for-you services. Includes the Claude-coverage gap.
/lynceus-vs-peec-ai/
Lynceus vs OtterlyAI
Budget self-serve ($29-489/mo) vs full-service engagement. Agency-focused vs brand-direct.
/lynceus-vs-otterly/
Lynceus vs a traditional SEO agency
Conceptual comparison — why AI visibility methodology is overlapping but distinct from SEO methodology.
/lynceus-vs-seo-agency/
Lynceus vs AthenaHQ
Action-layer competitor — software-recommends vs services-ships, Shopify-native vs stack-neutral.
/lynceus-vs-athenahq/
Lynceus vs Evertune
Enterprise platform with 25M-user prompt panel vs mid-market services. When enterprise scale is required.
/lynceus-vs-evertune/
Lynceus vs Bluefish
Managed AEO platform vs done-for-you services. Transparency, pricing, and assistant coverage compared.
/lynceus-vs-bluefish/
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from real AI answers.
The free Lynceus check shows the AI search answers that already mention your domain (mostly Google AI Overview today, some ChatGPT): mention counts by surface, sentiment, and any whole sentences written about your brand. No reading required.