WayliAI Readiness
AI Readiness Labs

How did our understanding of AI Readiness change?

Explore the historical record of discoveries, corrections, unexpected behaviour and methodology changes from the closed AIR assessment experiment.

For the practical website journey behind the research, see the historical Wayli case study, or read the AIR methodology historical reference.

Journal 041

Reproducible Is Not the Same as Reliable

AIR produced deterministic, repeatable results, but checking six assessments against the websites exposed something more important: a reproducible interpretation can still be wrong.

Journal 040

We Found a Score AIR Couldn't Award

Making AIR's scoring more transparent exposed an Audience score that could never be reached. Testing the problem led us to simplify the question rather than weaken the evidence standard.

Journal 037

When AI Retrieves the Wrong Page

A technically healthy website can still produce a poor AI answer when the retrieval system selects the wrong evidence.

Journal 029

Building for a New Audience

As AI becomes a new audience for the web, websites are beginning another period of adaptation. This is why we're choosing to build AI Readiness in public.

Journal 031

ChatGPT on Wayli

An independent review of Wayli by ChatGPT, assessing the platform from the perspective of how modern AI systems evaluate and interpret websites.

Journal 032

Claude on Wayli

Claude's independent review of Wayli's crawlability, content, trust evidence and citation viability.

Journal 033

Perplexity on Wayli

Perplexity's independent review of Wayli's positioning, design, content depth, navigation and trust foundations.

Journal 034

Gemini on Wayli

Gemini's independent review of Wayli's human value, AI processability, interoperability and external authority.

Journal 035

GitHub Copilot on Wayli

GitHub Copilot's review of Wayli's user experience, repository architecture, AI context model and engineering priorities.

Journal 036

Browser Copilot on Wayli

Microsoft Copilot's cross-tab review of Wayli, followed by a scored assessment of the evidence visible on the AI Readiness page.

Journal 028

The Day Giving 100% Became Possible

We discovered our own assessment could never award a perfect score. The problem wasn't the methodology. It was our implementation.

Journal 025

We Were Selling the Wrong Thing

The biggest improvement to AI Readiness wasn't a better engine. It was realising what people should not have to pay for.

Journal 024

The Report Improved Because We Listened

The biggest improvement to our latest AI Readiness report wasn't caused by changing the engine. It happened because we acted on what the previous report told us.

Journal 023

The Score Was Never the Goal

We thought we were improving an AI Readiness score. What we were really improving was how clearly we explained ourselves.

Journal 021

The Pattern We Didn't Expect

We thought we'd find one big problem. Instead, we found lots of small ones. That changed how we think about AI Readiness.

Journal 022

One Hundred Isn't Enough

One hundred businesses gave us our first evidence. It also reminded us how much we still have to learn.

Journal 017

We Tested Wayli on Wayli

Before asking anyone else to trust our Understanding Engine, we pointed it at ourselves.

Journal 012

The Day AI Left the Critical Path

The biggest breakthrough wasn't teaching AI to make better decisions. It was deciding that it shouldn't make them at all.