Grow / AEO and GEO
Entity consistency, direct answers, first-hand evidence and machine-readable structure, built on sound SEO fundamentals.
Answer engine optimization and generative engine optimization make expertise easier for search and AI systems to understand, retrieve and attribute. The work starts with the same fundamentals as strong SEO: crawlable pages, clear entities, useful first-hand information, sound internal linking and accessible content. TechSteps improves the quality and machine-readability of your source material. No agency can guarantee an AI system will cite a specific page.
What this solves
A genuinely new channel has appeared, and around it a large amount of nonsense. AI systems increasingly answer questions directly, sometimes citing sources, and a market of vendors has emerged selling techniques to get cited. Most of what is sold as an AI optimization hack is either ordinary SEO with a new label or invented.
What is actually true is less dramatic and more useful. These systems retrieve from crawlable web content. They favour material that is specific, attributable and clearly structured. They struggle with pages that hide content behind JavaScript, bury the answer, or say nothing a hundred other pages have not already said.
So the work is real, and it is mostly about being genuinely worth citing and easy to parse. That does overlap heavily with good SEO, and the parts that differ are worth doing deliberately.
When people call us
If more than one of these sounds familiar, the underlying cause is often a single issue rather than several separate ones.
Technical scope
Not every engagement includes all of this. The scope is agreed in writing before we start, and anything excluded is named rather than left ambiguous.
How we approach it
Crawlability, rendering, structure and internal linking. A page an AI system cannot retrieve cannot be cited, and this is where most of the real gap sits.
A single maintained facts page, consistent details everywhere, and structured data that matches. These systems have to establish who you are before they can rely on you.
A direct forty to ninety word answer to the page's primary question. This helps readers who are skimming and systems extracting, which is the same thing for different audiences.
Original evidence is the actual differentiator. A page summarizing publicly available information has no reason to be cited over the source it summarized.
Retrieval crawlers and training crawlers are separate decisions. We document both rather than leaving it to a default nobody chose.
Referral traffic and branded search growth are observable. Citation frequency across systems largely is not. We report the limits rather than inventing a score.
What goes wrong
These are the patterns we see most often when we are called in to fix someone else's work, or our own from earlier in our careers.
It is an optional convention some systems may use. Google stated in June 2026 that it is not a requirement for AI visibility in Search. Publishing one is harmless; being sold one as the solution is not.
Nobody controls which sources a model cites, and the systems change frequently. Any guarantee is either a misunderstanding or a lie.
Volume without original information. These systems are specifically built to select sources worth citing, and a hundred derivative pages give them nothing to choose.
A blanket rule intended for training crawlers also blocks retrieval bots, so the site cannot be cited at all. The two need separate, deliberate decisions.
A number with no stated methodology, reported monthly. It measures nothing and exists to justify a retainer.
Questions we actually get asked
Mostly it is the same work with different emphasis. Crawlable content, clear structure, genuine expertise and consistent entity information serve both. What differs is the weight on direct answers, self-contained sections, explicit sourcing and being distinctly worth citing rather than merely ranking. Treat anyone presenting it as a wholly separate discipline with caution.
It is optional. Some systems may use it as a navigational convenience. Google stated in June 2026 that it is not a requirement for AI visibility in Google Search. We are happy to add one, and we will not describe it as a ranking factor, because it is not.
That is two decisions, not one. Retrieval crawlers fetch pages to answer a user query and can cite you. Training crawlers collect data to train models and will not. Most businesses want to allow retrieval and may or may not want to allow training. Blocking both means you cannot be cited at all, which is usually not what people intend.
Partly through referral traffic from AI products where it appears in analytics, and through branded search growth, which often rises when people encounter you in an answer and then search for you. Beyond that, manual checking of a defined query set. Comprehensive citation tracking is not currently possible and we will not pretend otherwise.
No, and neither can anyone else. We can make your expertise clearer, better sourced, more crawlable and more genuinely worth citing. Which sources a given system selects for a given query is not under any agency's control, and the honest version of this service says so up front.
Describe the system and what is going wrong with it. A short technical conversation is usually enough for us to tell you whether this is the right work and roughly what it involves.