GEO starter guide is the practical starting point for making a site more usable by generative engines. It focuses on the highest-leverage basics rather than advanced model-specific tactics in GEO fundamentals.
The goal is simple: make the site easy to crawl, easy to understand, and easy to trust.
Start here
- Make the site crawlable and indexable.
- Publish clear, answerable pages.
- Use stable URLs and consistent entity signals.
- Add references where facts need support.
- Monitor whether the site is being used in AI answers.
What this looks like
If Ajey is helping AwesomeShoes Co., the first pass is not a clever prompt trick. It is fixing the pages that explain products, fit, returns, and brand details so they are easy for humans and systems to read.
That usually means:
- one topic per page when possible,
- visible facts that match the markup,
- clean internal links,
- and updates when the underlying facts change.
What to skip early on
- Fancy tactics before basic clarity.
- Content that cannot be trusted.
- Technical work that does not improve access or understanding.
AEO rule of thumb
The best first step is not a special GEO trick. It is a clean source that can be understood by both humans and machines through better grounding.
Starter workflow
- Audit crawl/index health for priority pages.
- Rewrite top pages for direct answer clarity.
- Align entity naming across site and profiles.
- Add evidence where trust-sensitive claims appear.
- Track early citation and mention outcomes by query set.
This creates momentum with high-leverage fundamentals.
Common pitfalls
- Jumping to advanced tactics before fixing basics.
- Publishing broad pages with unclear page purpose.
- Ignoring outdated facts on high-traffic content.
- Measuring only traffic and not answer-surface visibility.
Quality checks
- Are priority pages easily extractable and verifiable?
- Are entity signals stable across key touchpoints?
- Are high-risk claims supported with evidence?
- Do first-round fixes improve real answer outcomes?
GEO onboarding works best when foundational quality is treated as infrastructure with ongoing monitoring.
