Comparisons
Editorial planning across Google and AI engines: the Pico Neural method
When ChatGPT and Perplexity quote different parts of a page Google reads in full, the editorial plan has to start from those differences. Here is how Pico Neural maps them.
You have a page Google reads in full. Then you ask ChatGPT and Perplexity about the same information, and the answers quote different portions of the text. That gap is where an editorial plan should start. At Pico Neural, we treat AI visibility as something distinct from what Google reads, and we build the plan by observing which parts of a page the AI engines we track actually report. The job is not to rewrite the page. It is to map which blocks surface and which stay invisible, then decide what to produce or restructure. Our method is operational and checkable. It is not a universal standard.
Why the differences matter for the editorial plan
Pico Neural's public pages name ChatGPT, Perplexity, Gemini, Grok and Google AI. Claude and Grok are measured only after you connect them. Gemini and Google AI Overviews are not the same observation and should be treated as two separate viewpoints. An editorial plan therefore cannot rest on a single source of reading. It has to record separately what each observed engine surfaces.
The Pico Neural method in three steps
- Collect answers engine by engine. For each key page, ask ChatGPT and Perplexity the same questions and note which portions of the text come back. Checkable rule: every answer is tied to an engine and a date, and Gemini is never mixed with Google AI Overviews.
- Compare against what Google reads. Take the page as Google reads it and identify which blocks appear in the AI answers and which do not. Checkable rule: for every block on the page, state whether ChatGPT reports it, Perplexity does, both do, or neither does.
- Decide the editorial work. Based on that comparison, give every invisible block an action: rewrite it, split it into a new page, or remove it. Checkable rule: every action is tied to a specific block and to an engine that does not report it.
What this piece offers is a concrete way to use the differences between Google and AI engines as input for the editorial plan. We propose treating each page as a sum of blocks and recording, for every block, whether it is present or absent in the answers from ChatGPT and Perplexity. The plan does not start from abstract keywords. It starts from an inventory of blocks with their AI visibility status. That inventory becomes the basis for deciding which new content to write and which parts of existing pages to restructure. This is an operational proposal from Pico Neural, not a universal standard: adapt it to your context and check it over time. The method requires keeping the observed engines separate and not confusing Gemini with Google AI Overviews, because they are different observations.
A limit you can check
The method rests on observed answers from ChatGPT and Perplexity and on the public pages that name the engines. It does not cover what cannot be observed, and it does not guarantee that a change to the editorial plan will change the AI answers. For more detail, see the features page.
AI Visibility: Build Your Editorial Plan From the Features Page
AI Visibility and Editorial Planning: Reading the Features Page