Tag: ai-accessibility-testing
Accessibility overlays do not work, and AI auditing is the opposite
An accessibility overlay is one line of JavaScript that promises ADA compliance while you do nothing. The FTC fined accessiBe a million dollars over that promise. Here is why a widget cannot fix a problem that lives in your code, and how real AI auditing does the reverse by finding the broken line so a person can change it.
Can AI actually do accessibility testing? I ran it on my own product
Automated accessibility tools catch maybe a third of WCAG problems. I pointed Claude Code at Tallyfy, my own product, and let it run a real WCAG 2.2 audit with a live screen reader across four codebases. It found bugs that axe-core cannot see, and it showed clearly where the work still needs a person.
How to run a long autonomous Claude Code job without it drifting
The hard part of a big AI job is not the work. It is making the agent run for many sessions without drifting or claiming it is done when it is not. I used an accessibility audit across four codebases as the test. The setup that kept Claude Code on track was a git ledger, atomic parallel claims, and two verification passes.
What a VPAT costs, and why the report is the cheap part
A VPAT is the report that states how accessible your product is, measured against WCAG. People ask what it costs and price the document, but the document is the cheap part. The real cost is re-auditing every release, and that is the number an AI agent actually moves. Here is the ADA, WCAG, Section 508 and EN 301 549 stack underneath it.
What axe-core misses, and how AI caught it with a real screen reader
Axe-core catches about a quarter of WCAG failures and skips anything that needs judgment. Here are the thirteen criteria a scanner cannot decide, how an AI agent drives a real VoiceOver session to cover them, and the save button that passed every automated check and was silent to a blind user.