AI Search / AEO / GEO
I combine SEO, AEO, GEO, technical search strategy, AI visibility analysis, and agent-assisted workflows to help brands earn citations, mentions, and trust before buyers ever click.
What I Do
I help B2B brands build visibility across every layer of modern search, from traditional indexing to AI-generated answers, citations, and agent-assisted research.
Structuring content, entities, and signals so brands appear inside ChatGPT, Perplexity, Gemini, and Google AI Overviews. Citation strategy, entity authority, and corpus presence for the retrieval era.
Engineering content to be selected and cited by AI-generated answers. Structured FAQ architecture, NLP-aligned heading hierarchies, schema markup, and answer-first content frameworks.
Crawlability, indexation, structured data, information architecture, and JSON-LD for AI-first discoverability. Connecting organic performance to pipeline, conversion, and market expansion.
AI orchestration and automation for content operations, visibility monitoring, and reporting at scale. n8n, Make, and LLM-powered workflows that turn AI search data into action.
Wikipedia strategy, Wikidata, Reddit and G2 visibility, structured data implementation, and third-party citation building that establishes entity authority across AI knowledge systems.
Content programs for enterprise and cybersecurity brands targeting technical buyers. Topic cluster architecture, AI-retrievable page structures, and programmatic content at scale.
Why This Matters Now
Three shifts have happened in rapid succession. Most search strategies are still built for the first one.
Buyers stopped clicking ten results. They read a synthesized answer from ChatGPT, Perplexity, or Google AI Overviews and shortlisted from there. Ranking #1 no longer guarantees visibility.
Agentic AI now researches, compares, and shortlists autonomously on behalf of buyers. An AI agent evaluating AI security vendors doesn't browse your website. It retrieves structured signals from everything it can access about your brand.
The new optimization target is the agent's context window. Brand authority, structured content, third-party citations, and corpus presence now determine whether you're retrieved at all. This is a fundamentally different problem from traditional SEO.
Framework
AI search is often treated as an extension of SEO. It isn't.
SEO makes you discoverable.
AEO makes you selectable.
GEO makes you retrievable.
Most programs are still optimized for discovery alone. AI systems operate across all three layers, shifting the target from ranking in an index to being included in a context window.
AI Search Proof Lab
The AI Search Proof Lab is a public portfolio of experiments, audits, templates, and workflows showing how brands appear, disappear, and compete inside AI-generated answers.
A 15-prompt AI search benchmark showing which brands, domains, and content formats are cited for enterprise AI data security questions.
What it demonstrates: Prompt testing, citation analysis, brand visibility benchmarking, and SEO/AEO/GEO strategy.
A content brief format for building answer-first pages designed for AI search visibility, citations, and buyer-intent coverage.
A workflow for identifying where competitors are cited in AI answers, where a brand is missing, and what content to refresh first.
A reporting framework that connects AI citation visibility, share of voice, and organic performance to pipeline and revenue for executive audiences.
Point of View
Agentic AI does not Google things. It retrieves, synthesizes, and acts.
The next era of visibility will be shaped less by blue links and more by retrieval, synthesis, and machine-mediated selection. Being discoverable is no longer enough if AI systems cannot interpret, trust, and cite what they find.
Most SEO programs were architected for a world that no longer exists. Page-one rankings, click-through rates, session counts , these metrics measured influence over a human browsing experience. That experience is being replaced, faster than most teams are acknowledging, by agents that research autonomously and synthesize before a human ever enters the picture.
The optimization target has moved from the index to the context window. That shift requires different signals, different structures, and a more expansive understanding of what search visibility really means.
AI Search Workflows
I design agent-assisted workflows that help marketing teams operationalize AI search strategy, from citation monitoring and content gap analysis to reporting and prompt-based auditing.
Workflow models for tracking brand mentions and citation patterns across ChatGPT, Perplexity, and Gemini, surfacing visibility gaps and competitive shifts.
Scalable content workflows using n8n and LLM APIs for brief generation, content auditing, schema injection, and internal linking at scale.
Executive-ready dashboards in Looker and Tableau that connect AI visibility metrics, citation share of voice, and organic channel performance to revenue and pipeline influence.
Selected Search Programs
A selection of anonymized programs and search initiatives spanning SEO, AI visibility, content architecture, and technical search strategy.
Re-architected transactional intent coverage with structured content, schema, and answer-first frameworks to capture high-intent buyers during a peak seasonal campaign.
Built a framework for evaluating how brands appear across AI-generated answers, including citation tracking, competitive visibility patterns, prompt testing, and content gap analysis.
Developed content strategy frameworks for technical B2B audiences evaluating complex software categories, including topic cluster architecture, answer-first page structures, compliance-oriented content, and FAQ frameworks designed for AI retrieval.
Defined structured FAQ architecture that turns content into retrievable answer surfaces for search engines and AI systems.
Identified the need for structured bio, FAQ, and answer-first content layers during a website architecture review. These formats create clearer retrieval surfaces for search engines and AI answer systems.
Designed a model for monitoring brand mentions across AI answer engines, benchmarking sentiment versus category competitors, and identifying content updates that can improve AI-generated brand perception over time.
Certifications & AI Fluency
Formal credentials across AI systems, search strategy, analytics, and data security.
Foundation-level certification in AI systems, capabilities, and responsible use from Anthropic.
Prompt design, AI workflow planning, and agent-assisted process design for marketing and search operations.
Content optimization and AI search strategy certification from Surfer SEO.
Data Security Posture Management architecture certification, supporting deep content strategy in AI security and data protection categories.
Official Google certification in GA4, measurement strategy, and data-driven marketing analysis.
Advanced SEO strategy, technical auditing, and competitive analysis certification from Semrush.
Inbound SEO methodology, on-page optimization, and content strategy certification from HubSpot Academy.
About
My work sits at the intersection of search, AI, and buyer behavior.
As search shifts from ranking to retrieval, visibility is no longer determined by position, but by whether AI systems can interpret, trust, and surface your brand.
I design for that shift.
Stack