I wrote HealthyForge to please Google, and Google never noticed. The site gets visitors in GA4 while Search Console shows almost no queries behind them, which is what a site looks like when it was built around what I assumed Google wanted instead of what searchers were actually being shown. If you have a site that follows every on page rule and still gets nothing back, this post is about the part of AI search optimization that checklists skip, and I want to be upfront that I’m testing it right now, not reporting a win.
Three Ways to Write for Search
The first way is copying the top results. You read what ranks, rewrite it in your own words, and publish a slightly different version of something that already exists. It can get you indexed, but it gives a reader and a search engine no reason to choose you over the original.
The second way is what I call being a Google pleaser. You write to signals you assume the algorithm rewards, like keyword density, word count targets, heading formulas, and whatever the last SEO article said was important. The problem is that you are guessing at something you cannot see, and every guess is built on rumor. That is exactly how I built HealthyForge, and it is why I no longer trust the approach.
The third way is being a SERP pleaser. You read what the results page is actually showing for the query, match the shape of the answer people are being served, and then add the one thing the page one results do not have. The difference is that one approach reads evidence and the other reads rumor. Nothing about it is new, but it changes what you do before you write a single sentence.
What SERP Analysis Actually Tells You
SERP analysis sounds like it needs a tool, and it does not. Search your head term, open the top results, and read them the way a reader would, not the way an SEO would. Notice the format that dominates, whether that is a guide, a comparison, a definition, or a walkthrough, and notice what each page answers first, how deep it goes, and what it assumes you already know.
That is search intent made visible. The results page is Google’s own answer to what people want when they type those words, and two queries that share most of their words can want completely different things. A reader searching for a definition and a reader searching for a fix will be shown different formats for a reason. Matching that format is not copying, because the shape is only the container and what goes inside it is yours.
The most useful part is what is missing. Every set of results leaves gaps: a step everyone skips, a claim nobody tested, an assumption that stops being true for some readers. Those gaps are where a post earns its place, and you cannot see them without reading the results properly first.
Why This Matters for Answer Engine Optimization
I already covered how AI search engines work, so I will not repeat the mechanics here. The part that matters for this post is that these systems lean on the results that already surface for a query, and they work from passages, not whole pages. I also wrote about the top 10 truncation problem, where an answer is assembled from a limited slice of results that gets cut off at some point in the pipeline.
Put those two facts together and the logic is simple. If your page does not look like what ranks for the query, it is less likely to be in that slice, and if it is in the slice but says what ten other pages already say, the engine has no reason to quote you. Answer engine optimization is mostly SERP optimization with a second reader attached. My working belief, and I am calling it a belief because I have not proven it, is that structure gets a page considered while original information gets it cited.
How to Rank in AI Overviews and Get Cited by ChatGPT
Nobody can promise you either one, and anyone who does is selling something. What I can tell you is the order of operations that makes sense given how both tend to work. First, you have to be visible for the query in the shape those systems expect, which is the SERP pleaser part. Second, you need a passage worth lifting, and that is where most pages fail.
A passage worth lifting is a specific claim, a result you measured yourself, a decision with the reason behind it, or a failure described in enough detail that someone else could avoid it. A clean definition is not that, because an AI overview can already write a definition without you. If you want to know how to get cited by ChatGPT, the honest answer I have is to be the source of something instead of a restatement of it. The experience layer is not decoration. It is the thing that makes a page citable.
How to Design It
I think about it as two layers. The shape layer covers the answer format, the order in which questions get answered, the depth, the headings that mirror how the results phrase the problem, and a direct answer placed where a reader or a retrieval system would look for it. The experience layer covers what only you have, meaning what you built, broke, measured, or decided.
Before I write anything now, I run four checks against the idea. What shape does the SERP reward for this query? What do all the top results assume or skip? What do I have that fills that gap? Could a single paragraph from this post be quoted on its own and still make sense? If the answer to the third question is nothing, I do not publish, and that rule is the one that keeps this from turning into a content farm with better manners.
How to Implement AI Search Optimization on a Real Post
Start by searching the head term and reading the top results all the way through, not skimming the headings. Write down the dominant format, the first thing each page answers, and what is missing, and do that before you build an outline. Then build the outline in the shape the results use, and make your gap the strongest sections, not an afterthought at the end.
After the draft is written, read it paragraph by paragraph and ask whether each key passage stands alone if someone quotes it out of context. Then handle the technical side separately. My LLM optimization guide covers what crawlers and bots see, including schema, heading hierarchy, and syndication, while this post covers what to put on the page so those bots have something worth citing. You need both, and they solve different problems.
What This Changes in My Own Rules
Every strategy I have learned eventually got unlearned when I applied the next one, and I have stopped pretending otherwise. That is why I treat this as a guardrail and not a template. A template tells you what to write, while a guardrail tells you what to check, and the second one is why my posts stay human first.
It is also the same instinct behind what I said earlier about clarity, context, and having something to say, just with a method attached. And it fits the conclusion from my repeatable SEO system across five blogs, which is that no universal system exists and you should build yours from what you measure.
The Honest Part: This Is Untested
I am starting this now, and I am testing it on two of my own sites that have been getting almost nothing from Google, HealthyForge and RemoteWorkHaven. Each week, one post gets written to the SERP shape, one gets written the way I normally write, and one is a money post. The money post is where the blogging side matters most, and I worked through that angle separately in SEO content for bloggers. After four weeks I will compare how each indexed post performs in impressions, using the timestamps from when I submitted each one for indexing.
I could be wrong, and I would rather say how than hide it. If the SERP shaped posts do not beat the normal ones, the idea fails. It is also possible the real problem on those two sites is trust at the site level and has nothing to do with content shape, since the same keyword approach worked on four of my other sites and did nothing on these two. If that is the result, I will say so. Until the test runs, treat everything above as a hypothesis with a reason behind it, not a proven method.
