AI Content & AEO Strategy
I’ve been working in search since 2004, founded Builtvisible (acquired), and spent the last two years rebuilding everything I know about content on top of AI. Content strategy, answer engine optimisation, production pipeline design, and voice analysis, from someone who’s been doing this since before Google had a toolbar.
Book a free call to discussWhy this matters now
The way people find information is changing faster than most content strategies can keep up with. When someone asks Claude or Gemini or Perplexity a question about your industry, does your content show up in the answer? For most companies the answer is no, and they haven’t even thought to ask the question yet because they’re still optimising for Google’s ten blue links while a growing share of their audience has already moved to AI-generated answers as their first port of call.
I’ve been in search since 2004. I founded Builtvisible, grew it into one of the UK’s best-known content and SEO agencies, and it was acquired. I spent over a decade building content strategies for brands across every industry you can name. And for the last two years I’ve been building the AI-powered content pipeline that produces houtini.com, which means I’m not just talking about the shift to AI, I’m watching it happen in my own analytics data every week and adapting in real time.
What I do
AI-enhanced content strategy
Topic research, keyword clustering, competitive analysis, and content calendar, but done with AI tools (DataForSEO for keyword data, Google Search Console analysis pipelines I built myself, Claude for pattern recognition across large datasets) rather than the manual spreadsheet approach that most agencies still use and that takes three times as long. The output is a prioritised list of what to write, in what order, targeting which terms, with realistic traffic and conversion projections based on actual data. Not a 60-page deck with vague recommendations about “thought leadership,” but a working plan you can hand to a writer on Monday morning.
Answer engine optimisation (AEO)
AEO is the discipline of making your content appear in AI-generated answers, the responses from Claude, Gemini, ChatGPT, and Perplexity that are increasingly where people go before (or instead of) Google. It’s not the same as traditional SEO, because the AI isn’t ranking ten blue links, it’s synthesising an answer from multiple sources, and the criteria for what gets included are different from what ranks on page one of Google. The structure of your content matters more, the depth of your expertise signals matter more, and generic copy that reads like every other result on the internet gets filtered out entirely.
I’ve been testing this extensively with my own content (houtini.com articles regularly appear in AI-generated answers across multiple platforms), and the patterns are clear enough now to apply systematically to other sites. This is where my 20 years of search experience is most directly useful, because understanding how search engines evaluate content is the foundation that AEO builds on.
Content production pipeline design
How to use AI to produce quality content at scale without it reading like AI wrote it. This is harder than it sounds, because most AI-generated content is detectable, generic, and sounds like every other AI-generated article on the internet, which means it doesn’t rank, doesn’t get cited by answer engines, and doesn’t build any trust with readers. I built a pipeline that handles research, drafting, voice matching, AI detection scoring, and WordPress publishing via the REST API, and it produces content that consistently scores below 20% on AI detection tools while maintaining a distinctive editorial voice.
I can design a similar pipeline for your team, calibrated to your voice, your tools, and your publishing workflow, whether that’s WordPress, Shopify, or something else entirely.
Voice analysis and brand consistency
I wrote the voice analysis MCP server used in my own content workflow, and it’s published as an open-source npm package (@houtini/voice-analyser on npm). It analyses a corpus of your existing content and extracts your actual writing patterns: sentence rhythm, vocabulary preferences, hedging behaviours, structural habits, how you open articles, how you transition between ideas. The output is a voice guide that AI tools can use to match your style with genuine fidelity, and the difference between telling an AI “write in a professional tone” and giving it a proper voice profile built from your real writing is the difference between generic corporate copy and something that actually sounds like you.
Why me and not an agency
I’ve been on both sides. I ran Builtvisible for over a decade, managing content strategy for clients at scale with a team of 50 people. And now I’m a practitioner again, building the tools myself, writing the content, running the pipelines, checking the analytics. That combination of strategic experience and hands-on technical depth is genuinely rare. Most strategists don’t build their own MCP servers and content pipelines. Most builders don’t have twenty years of search strategy experience and the client-facing judgment that comes with it.
And frankly, most agencies selling “AI content” are using ChatGPT to generate articles and hoping no one notices. I built a detection and rewriting pipeline specifically because I know how bad that approach is and wanted to do it properly, with content that reads like a human wrote it because the AI was guided by a real voice profile and validated against detection tools before publishing.
What you get
I’ve been working in search since 2004. Founded Builtvisible (acquired). Built the content pipeline that produces houtini.com. Wrote the voice analysis MCP server. This isn’t a service I added to the menu because AI content is trendy, it’s what I’ve spent the last two decades doing, with the last two years spent rebuilding the entire approach on top of AI tooling I built myself.
Common questions
What is answer engine optimisation (AEO) in plain English?
When someone asks ChatGPT, Claude, Gemini, or Perplexity a question, those tools pull information from web content to build their answer. AEO is the practice of structuring your content so it gets cited in those AI-generated answers. It’s related to traditional SEO but the rules are different, because AI models weight expertise signals, content structure, and specificity differently from how Google ranks pages. If your content is generic, it gets ignored. If it’s genuinely useful and well-structured, it gets cited.
Won’t AI-generated content hurt our brand?
Bad AI-generated content will, absolutely. And most of it is bad, because most people are just prompting ChatGPT with “write a blog post about X” and publishing whatever comes out. The pipeline I build is different: it uses voice analysis from your existing content to match your actual writing style, runs every piece through AI detection scoring, and the output reads like your team wrote it because the AI was constrained by your real voice patterns rather than its default corporate tone.
How long before we see results from AEO?
Faster than traditional SEO, in my experience. New content optimised for AI citation can start appearing in AI-generated answers within weeks rather than the months it takes to rank on Google. But it depends on your domain authority, your existing content, and how competitive your space is. I’ll give you honest timelines based on your specific situation rather than promising things I can’t deliver.
Want to talk about your content strategy?
Book a free 30-minute call. Tell me what you’re publishing, what’s working, and where you’re stuck. I’ll give you an honest view of whether AI can help and what the first step should be.
Book a call