AI Search & Visibility Strategist
Agentic AI doesn't browse. It retrieves, synthesizes, and acts. Winning the next decade of B2B means being in the agent's context window — not just the index.
Why This Matters Now
Three shifts have happened in rapid succession. Most SEO programs are built for the first one. I work across all three.
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.
What I Do
Six capabilities that compose into a complete agentic visibility program — from foundational content structure to real-time LLM monitoring.
Optimizing brand presence for AI agents that research and shortlist autonomously. Corpus management, entity authority, structured data, and third-party citation signals that make brands retrievable when agents are evaluating options.
Engineering content to be cited by ChatGPT, Perplexity, and Google AI Overviews. Structured FAQ architecture, NLP-aligned heading hierarchies, and answer-first content that wins placement in AI-generated responses.
Monitoring and shaping how brands appear inside AI-generated responses. Share of Voice tracking across LLMs, sentiment benchmarking versus category competitors, and content strategy to shift AI-generated brand perception.
Content programs for AI security, DSPM, and data protection vendors targeting security architects and technical buyers. Deep understanding of how AI security buyers research, evaluate, and shortlist — and how to be present at every stage.
Connecting AI search wins to MQLs, SQLs, and influenced pipeline. Executive dashboards that show organic's role in the buying journey — not traffic vanity metrics — built for CMO and board-level audiences.
The structural foundation that makes retrieval possible — schema markup, semantic HTML, crawl optimization, and content architecture built for how agents ingest information, not just how crawlers index pages.
Point of View
Agentic AI doesn't Google things. It retrieves, synthesizes, and acts.
The brands that win the next decade of B2B aren't the ones ranking #1. They're the ones being retrieved when an AI agent is assembling a shortlist on behalf of a buyer who may never click a single link.
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 a different discipline, different signals, and different success metrics. That's the work I do.
Read my writing on AI searchSelected Work
Programs where AI-first search strategy translated into measurable business outcomes.
Re-architected transactional intent coverage with AI-optimized content pathways, advanced structured data, and answer-first content frameworks to capture bottom-funnel buyers at peak purchase intent.
Built an LLM visibility program for a high-growth data security platform — corpus management, citation tracking across ChatGPT and Perplexity, competitive SOV benchmarking, and AI-optimized content clusters for AI security and data protection categories.
Developing a content program targeting security architects and technical buyers evaluating AI security and data protection platforms — including topic cluster architecture, AI-retrievable page structures, compliance content for GDPR, HIPAA, and SOC 2, and agent-readable FAQ frameworks.
Systematized FAQ schema, NLP-aligned heading structures, and concise answer blocks across 80+ pages to capture featured snippets and AI answer placements for high-intent B2B queries.
Identified and drove adoption of structured bio and FAQ content layers during a full-site rebrand for a Series C cybersecurity platform. The addition of these retrievable content formats created new entry points for AI answer engines that the existing site architecture completely lacked.
Designed a systematic program to monitor brand mentions across AI answer engines, benchmark sentiment versus category competitors, and execute tactical content updates to shift AI-generated brand perception over time.
About
I've spent 10+ years at the intersection of search and buyer behavior. The question that has always driven the work: where is the buyer's attention, and how do we earn a place in it?
That answer used to be: rank for the right keywords. Now it's: be retrievable when the agent is assembling the shortlist. I've built my practice around that shift — and I write about it regularly for others navigating the same transition.
Stack
Let's Connect
I'm always interested in conversations about where AI search is heading, what agentic visibility actually requires, and how B2B brands can build for the retrieval era. If you're thinking through any of these problems, reach out.