AI Search, LLM Visibility and Agentic Commerce
AI search is reshaping how people discover information, compare products and choose who to trust. My work focuses on understanding how these systems retrieve, interpret and surface content, and how businesses can stay visible as traditional organic traffic naturally shifts towards LLM driven journeys.
This means understanding how LLMs see your content, how they decide who to cite and recommend, and how your existing SEO work feeds into that. It all sits on top of my CSSF framework, which keeps the thinking grounded and helps avoid the noise that often surrounds AI.
Common AI Search Visibility Problems
Most sites were built for classic ten blue links search. They were not designed for LLMs that generate answers, expand queries and call multiple APIs behind the scenes. The result is a gap between how you think you appear and how AI systems actually surface you.
I help you close that gap by understanding how models crawl, embed, group and cite your content, and by reshaping your site so that AI search systems can use it with confidence.
AI Search Strategy & Roadmapping- LLM Bot Tracking & Log Analysis
- GEO & AEO Alignment
- LLM Citation & Visibility Monitoring
- Embedding & Vector Space Mapping
- Agentic Commerce Readiness
- Structured Data & Entity Optimisation
- CSSF Framework Workshops
- AI Search Technical Audits
- Ongoing Testing & Learning Loops
Staying visible while AI search evolves
AI search is not a bolt on channel. It sits across everything you already do with SEO and paid media. LLMs use embeddings, entities, citations and behaviour to decide who they trust enough to surface and recommend. Ignore that and you risk drifting out of the conversation even if your organic rankings still look fine.
My role is to help you understand where you stand today, how LLMs are already using your content and what needs to change so that AI systems keep finding, citing and recommending you as they become more agentic.
Send Me a Message
If you want to talk about AI search, LLM visibility or how agentic commerce might affect your site, send me a message and we can explore where you are now and what is realistic.
Other Ways to Get In Touch
Here is how to reach me:
- Email: [email protected]
- Phone: +44 07469 842532
- LinkedIn: Connect with me
My hourly rate is £70 (GBP) per hour, with flexible arrangements for longer term commitments.
From classic SEO to AI search systems
Traditional SEO assumed a fairly straight line between a query, a ranking page and a click. AI search does not work like that. LLMs fan out a question into multiple sub queries, hit different data sources, merge the results and then decide what to show the user. If your content is missing from those steps, you vanish from the journey even if you technically still rank.
Thinking in embeddings, not just keywords
LLMs do not see your pages as words on a screen. They see vectors inside a huge embedding space. That space has clusters, edges, gaps and overlaps. A big part of my work is looking at how your content clusters, where there are holes and where you are over represented or under represented compared to how people actually ask questions.
Technical foundations for LLMs, GEO and AEO
AI search still relies on technical foundations. Crawlability, internal linking, structured data, clean URL patterns and stable entities all matter. GEO and AEO layer on top of this, making sure that local context and real world attributes can be understood and reused by AI systems.
Agentic commerce and decision making
Agents and AI assistants will increasingly shortlist products, compare offers, apply filters and check trust signals before a user ever reaches your site. That is agentic commerce. You cannot optimise for every possible future, but you can make sure your brand is easy for agents to read, reason about and recommend when they need to decide between you and a competitor.
Using CSSF to avoid AI hype
My Confidence in Search Systems framework is how I keep all this grounded. It separates deterministic and probabilistic systems, and helps map where AI search fits in, which is mostly in probabilistic zones. It focuses effort on the parts of search where confidence can be built and measured rather than chasing tactics that shift too often.
Continuous testing, learning and refinement
This is not a set and forget channel. Models change, providers change and user behaviour changes. I treat AI search as an ongoing loop. Track, test, learn, adjust. Most of what I share on my site and LinkedIn comes from that cycle. I am learning alongside you, I just happen to be a few steps further down the rabbit hole.
Book a Consultation
AI Search Strategy
Joined up strategy for how your brand appears across AI search, LLM answers and traditional SERPs.
LLM & GEO Visibility
Strengthening the signals LLMs use when deciding whether to reference or surface your content.
Agentic Commerce Planning
Preparing your products, content and data so agents can confidently shortlist and recommend you.
AI Search Insights
Thinking, experiments and observations from working at the overlap of SEO, LLMs, GEO, AEO and agentic commerce. Less theory, more real world notes from the workbench.
Freelance AI Search & LLM Visibility Consultant
Where AI search is heading
Search is moving towards systems that provide answers directly, compare products in real time and guide user decisions long before they reach a website. This shift is already clear in how major models retrieve and combine information from different sources. As that becomes the norm, the volume of traditional organic clicks is likely to decline.
This will not happen overnight, but the direction is consistent. Brands that prepare for stronger LLM visibility, cleaner entity signals and better retrieval quality will be in a far stronger position as AI search becomes part of everyday behaviour.
I help companies plan for this change by focusing on the practical side of LLM retrieval. Understanding how models fetch information, how they treat conflicting signals and where your content fits inside that process helps protect visibility and avoids unintentional issues that can hold you back later.
Hiring someone who understands retrieval
LLM retrieval governs which brands appear in generated answers, which products are shortlisted and which sources are trusted. It is not driven by trend chasing. It is driven by clean technical signals, consistent entities and content that sits in the right part of the embedding space.
When you work with someone who understands how models crawl, embed and group information, every decision becomes calmer and more predictable. It reduces the risk of unintentional changes that weaken visibility across both classic and AI driven search journeys.
My work focuses on clarity. How models interpret your content, where your entity signals are strong or weak and how retrieval patterns affect how often you are surfaced. With that insight, you can make decisions based on evidence rather than guesswork.