SEO testing closely parallels software testing and reverse engineering. While tests can be informed by search engine statements about how their systems are intended to work, the real objective—much like in software testing—is to determine what is actually happening in practice. This process often resembles reverse engineering, requiring an understanding of the underlying technologies and limitations of document retrieval and AI systems to accurately interpret how they function.
Solution Smith approaches SEO and AI-guided search the same way it approaches software testing: if a feature is claimed, it is tested. Observations often begin as early data points and are then validated through experimentation. Ongoing findings are documented in recent SEO insights. This process does not rely on confirmation from Google or other search engines—especially since their algorithms are not publicly disclosed.
Myths and Confirmation Bias
Confirmation bias occurs when someone tests SEO assumptions based on how they believe search engines should behave, rather than objectively evaluating results. This can lead to selectively interpreting data in a way that supports existing beliefs.
Myths, on the other hand, form when assumptions about how search engines work are accepted without testing or validation. These beliefs persist not because they are proven, but because they go unchallenged.
To avoid confirmation bias, conclusions from testing are compared against observations from the broader SEO industry. Agreement or disagreement is treated as a signal for further investigation. Anecdotal observations are treated as early indicators and are not dismissed outright; instead, they are tested and validated to determine whether they hold up as empirical evidence.
Contact Information for This Page
Updated:
by Wayne Smith
Wayne is the founder of Solution Smith, with over 20 years of experience in SEO and a background in software testing and analysis. His experience includes evaluating how complex systems behave in practice, rather than relying on stated intent or assumptions.
This perspective shapes the approach throughout Solution Smith's AI-Aware Full-Stack SEO Guide: search engines and AI systems are treated as black boxes, with conclusions drawn from controlled testing, observed outcomes, and repeatable validation.