10 analyses, dated and sourced.
Methods, audits, field notes on optimising for AI answer engines. One article when there is something worth saying. No recaps, no digests, no filler.
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Google AI Overviews: how to appear and optimise your presence
Actionable guide to being cited in Google AI Overviews. How the system works, source selection criteria, optimisation levers and operational checklist.
Read the article6 min Note · 01 -
Optimising for ChatGPT Search: technical guide 2026
How ChatGPT Search (OAI-SearchBot) indexes and cites sources. Differences with Perplexity, selection criteria, optimisation levers and action plan to appear in ChatGPT cited responses.
Read the article13 min Note · 02 -
Optimising content for Perplexity: technical guide 2026
How Perplexity retrieval works, which content it cites and why, and the concrete levers to maximise your visibility in its responses.
Read the article7 min Note · 03 -
Topical authority and LLMs: building thematic authority for AI engines
How topical authority influences source selection by LLMs. Difference with PageRank, pillar-cluster strategy, measuring thematic authority, and action plan to become a reference source.
Read the article13 min Note · 04 -
Entity SEO for LLMs: seven actions to disambiguate a brand
How LLMs recognise entities, why disambiguation is critical for AI visibility, and seven operational actions to achieve it, from schema.org to the knowledge graph.
Read the article12 min Note · 05 -
RAG and SEO: understanding retrieval augmented generation for AI visibility
Retrieval Augmented Generation is the central mechanism that determines which content LLMs cite in their responses. This guide explains how it works and how to exploit it.
Read the article8 min Note · 06 -
Schema.org and LLMs: the complete guide to structuring data for AI
How schema.org structured data influences LLMs and AI answer engines understanding of your site. Technical guide with JSON-LD examples ready to copy.
Read the article6 min Note · 07 -
E-E-A-T and LLMs: how AI answer engines evaluate expertise and trust
How LLMs and AI answer engines interpret E-E-A-T signals (Experience, Expertise, Authoritativeness, Trustworthiness) and concrete actions to strengthen each dimension.
Read the article12 min Note · 08 -
Measuring AI visibility: defensible KPIs and pitfalls to avoid
No unified AI console exists yet. What is directly measurable, what is not, available tools, and the most reliable proxy metrics for tracking AI visibility.
Read the article12 min Note · 09 -
robots.txt and AI bots: complete configuration guide 2026
Exact user-agent strings for every AI bot (GPTBot, OAI-SearchBot, PerplexityBot, ClaudeBot, Google-Extended), robots.txt syntax, ready-to-copy examples, and verification method.
Read the article12 min Note · 10