I help B2B technology companies show up in the answers their buyers trust, from Google's results to ChatGPT, Perplexity, and Claude. A decade turning search and content into pipeline, now building the GEO/AEO practice at Lil Big Things.
Search didn't get smaller. It moved. Most teams are still optimizing for a page that fewer buyers read.
A growing share of high-intent research now happens inside AI engines, where one synthesized answer replaces ten blue links. For B2B tech with a technical buyer, this hit early. Developers folded AI into their daily workflow first.
By the time a product reaches a shortlist, the AI has already shaped it. If competitors, listicles, and Reddit threads get cited in your category and you don't, you lose deals you never see.
My work is making sure you're in that answer. Not through guesswork or "SEO but for AI," but through a measurable system: know where you stand today, fix what stops engines from citing you, and build content they actually pull from.
Generative and answer-engine optimization. Measure your AI share of voice, fix the technical gaps that keep engines from citing you, and earn citations in ChatGPT, Perplexity, Claude, and Google AI Overviews.
Technical foundations, content built for extraction, and the on-page work that still drives organic pipeline. The classic discipline, run with the same rigor as the new one.
Website GTM, conversion paths, and the demand engine around them. A decade across product marketing, growth, and delivery, so the strategy and the build stay connected.
Build the prompt set your buyers actually ask, then run it across every major engine to baseline your AI share of voice. You can't improve what you've never measured, and most teams have never looked.
Crawlability, structured data, robots.txt access for AI bots, llms.txt, and docs treated as a first-class citation asset. The unglamorous work that decides whether engines can read you at all.
Answer-first pages mapped to real buyer questions, structured so engines lift and cite them, plus the off-site presence (Reddit, GitHub, comparison roundups) that disproportionately feeds technical answers.
Re-run the prompt set, watch citation frequency climb, and track the AI-sourced traffic that converts. Being cited isn't the goal. Pipeline is.
Most teams don't fail because they lack talent. They fail because they ship too much, too early, without systems.
Over the last decade I've held leading roles across product, growth, and delivery at B2B software companies, including venture-backed startups later acquired by public companies.
Today I'm focused on building and publishing execution frameworks that combine product thinking, CX principles, and systemized delivery across website GTM, MVP deployment, and internal CX systems.
The work I care about isn't more output. It's the system underneath it: the one that lets a small, distributed team produce work that looks like it came from a much larger one, and ship it before talking about it.
An AI-age production laboratory that stress-tests AI tools under real production constraints, and ships CX-centered websites and MVPs for B2B technology teams.
Helping B2B tech get cited where buyers now research, inside ChatGPT, Perplexity, and Claude, through measurable answer-engine optimization rather than guesswork.
A productized Figma-to-Webflow sub-brand. The wedge that turns design files into shipped, production-grade sites at speed.
Publishing the systems behind the work, across website GTM, MVP deployment, and internal CX. Building before teaching, operating before advising.
A long habit of writing for technical audiences, translating infrastructure, product, and engineering decisions into plain language. The same instinct now drives how I think about what AI engines choose to cite.