AI Design Help is the experiment workspace where an AI model can design, ideate, critique, and revise the specification you are currently working on.
| Term | AI Design Help |
|---|---|
| Category | AI, Content Generation and Experiments |
| Also known as | Design Help |
| Where it appears | Experiments → Design help |
What it means in RankGear
AI Design Help lives inside the Experiments area, under Design help. It hands the current experiment specification to an AI model and asks it to reason about that spec — sketching an approach, proposing changes, or critiquing what is already there. Rather than sending you to a separate chat window, it works against the experiment you have open, so the suggestions it produces refer to your actual variables, hypotheses, and setup. The answer it returns is retained alongside the experiment so you can read it, edit it, or discard it before anything is applied.
How to interpret it
Treat what AI Design Help gives back as a draft to inspect, not a decision to accept. Before you apply or publish anything it produces, check four things: the context it was given (did it actually see the right spec?), the model you chose, the cost boundary you set for the run, and the proposed output itself. The workspace deliberately keeps the AI response separate from the live experiment so this review step is the default — nothing changes until you choose to carry a suggestion across.
Example
You are setting up an experiment to test whether restructuring a page’s H2 headings around a tighter question set moves its coverage score. You open Experiments → Design help and ask the AI to critique your current spec. It flags that your control and variant differ in two ways at once — headings and internal links — which would confound the result, and it drafts a cleaner version that holds links constant. You read its reasoning, keep the confounding note, adjust the spec yourself, and leave its suggested wording untouched where it is stronger than yours.
Important considerations
- AI output can be incomplete or simply wrong. Verify factual claims, credentials, statistics, and citations before you rely on them.
- Pay particular attention to experimental isolation — an AI-drafted spec can still leave two variables changing at once, which invalidates the comparison.
- Nothing is applied automatically. The retained answer is a proposal you review against your context, model choice, and cost boundary before acting.
- Any relationship the AI describes between a change and a ranking outcome is a hypothesis to test, not a proven cause. RankGear’s numbers are comparative indicators, not Google scores, and no edit “makes” a page rank.
Related terms
Part of the RankGear glossary · how RankGear measures · the 870 factors.