That’s the part too many people seem eager to hand-wave away. These systems are not arriving with some magically enlightened understanding of disability, inclusion, or accessible implementation. They’re being trained on the web as it is, which means they are taking all of its worst practices as truth.

If we want AI-assisted coding to improve outcomes rather than exponentially accelerate harm, accessibility must be foundational.

It dovetails nicely with my post on identifying accessibility data gaps in codegen models and my follow-up on optimizing codebases for AI coding agents. The former argued that these systems are already biased toward reproducing the web’s accessibility failures; the latter argued that if we want agents to be useful, we need to give them clearer structure, better documentation, and better examples.

What I especially appreciate here is how grounded the whole effort seems to be. One takeaway is that you can’t just wave your hands and tell an LLM to “do accessibility”; you need concrete guidance, clear expectations, and solid examples. Another is that accessibility work is too contextual to treat as a simple linting problem. And, perhaps most importantly, this is a good reminder that if we want AI systems to help improve accessibility, we have to be intentional about the data, patterns, and codebases we are feeding them. Otherwise they’ll just automate the same mistakes faster.

That framing cuts through a lot of the marketing nonsense. The promise is always that AI will help people do their jobs better. The deployment story, far too often, is that a human gets stuck reviewing machine output at impossible speed while absorbing the blame when things go wrong. That’s not augmentation; it’s a liability dump.

In this piece, Eric digs into accessible name length, accidental activation, stacking context weirdness, and progressive enhancement too. That kind of thoroughness matters because patterns like this can go sideways in a hurry when folks cargo-cult only the CSS and skip the reasoning.

What’s exciting to me here is not “AI turned a PDF into an app” so much as what made that possible: components, tokens, utilities, and enough design-system clarity to give the model something useful to work with. That’s a big part of the story so many people miss. If your system is inconsistent, vague, or poorly documented, AI is just going to amplify that mess.

What I especially like here is the framing: not simply “supported” or “unsupported,” but whether a feature is actually advisable in Shadow DOM, how it crosses boundaries, and where browsers still disagree. That’s the kind of nuance you need when you’re building real components instead of admiring specs from afar.

This is not a minor bug trend. It is a systematic civil-rights failure that has now found its way into software as a whole, through lightning-fast adoption of AI systems that are trained on over 20 years of institutional barriers.

The numbers here are bad enough on their own, but what makes this especially troubling is where these systems are being deployed: education, healthcare, finance, employment, and other places people can’t simply opt out of. That’s why I appreciate how direct this project is about accountability. If we automate interface generation without putting accessibility at the center, we’re automating exclusion.

Paul’s teardown is a good illustration of how far modern front-end practice can drift from the simple, robust platform primitives we already have.

If you can use a native HTML element or attribute with the semantics and behavior you require already built in, instead of re-purposing an element and adding an ARIA role, state or property to make it accessible, then do so.

Reading this reminded me of a pair of pieces I’ve linked to before: Making radio buttons and checkboxes easier to use and There can be only one: Options for building “choose one” fields.

We have spent an astonishing amount of time and energy overcomplicating a control HTML already gives us, often in the name of developer experience or styleability. More often than not, all we’re really doing is trading resilience for ceremony.

I also appreciate the callback in the title. We’ve been here before. The particulars may be new, but the core challenge is familiar: how do we build resilient, inclusive systems when the output is fluid, personalized, or otherwise beyond a designer’s exact control? Accessibility is not a bolt-on answer to that question; it’s where the answer has to begin.

This is exactly the sort of thing I want to see the platform absorb. We’ve spent years rebuilding common interaction patterns with roving tabindex, focus management, and piles of event handling code. If the browser can take more of that on, we get lighter pages, more consistent experiences, and fewer opportunities for developers to get keyboard support wrong.

There are a lot of grim numbers in here, but the one that really sticks with me is how many of the same, eminently-fixable issues continue to dominate year after year. We’re still talking about contrast, missing labels, empty buttons, and missing alt text. In other words, this is not a story about edge cases. It’s a story about fundamentals.

I particularly appreciated how plainly this post describes a mismatch a lot of teams create for themselves: wrapping largely-static content in an app shell, then shipping a pile of JavaScript just to re-assert what the server already knew. MDN’s new approach feels refreshing, despite being grounded in age-old best practices: Keep the content first-class, treat interactivity as optional (and isolated), and only ship what the page actually needs.

There’s a lot to like here, but more than anything I love seeing MDN embrace an architecture that’s truly aligned with the platform it documents.

I appreciate how clearly Anil connects dots that too many people are still treating as separate problems. This isn’t just about AI summaries siphoning traffic from publishers or slop code drowning maintainers or bad actors ignoring long-standing norms like robots.txt. It’s all of those things at once. The through-line is extraction: taking value from open systems without giving anything back, then undermining the very ecosystems that made that extraction possible in the first place.

The good of the web only exists because of the openness of the web. They can’t just keep on taking and taking without expecting people to finally draw a line and saying “enough”.

If you care about the web as a public good, this post is worth your time.

It’s one of those tools that immediately makes me want to crack open a demo and start playing. What’s especially nice is that it doesn’t ask you to invent some parallel configuration universe if you don’t want to; it can just inspect the variables you already have and give you a UI for experimenting with them. That makes it feel less like a framework and more like a really practical enhancement to the way many of us already work.

In other words, AI use is reinforcing what good documentation has always required: clear structure, explicit language, sensible headings, and fewer assumptions about what the reader already knows. That’s good for machines, sure, but it’s even better for people navigating with assistive tech, reading in a second language, or simply trying to get an answer quickly.

AI has not invented new rules for writing, it has made the cost of ignoring the old ones obvious.

This is the part too many teams miss: accessibility doesn’t end at the component boundary. A well-built component library can give you a stronger foundation, but it can’t guarantee the right labels, the right heading structure, the right focus management, or the right overall experience once those pieces are assembled into an interface. That work still requires judgment, care, and testing with actual people.

I also appreciate Mark’s call for more ambition here. Too often, we talk about the web as if it’s destined to be an OS for web apps rather than a public-interest platform in its own right. That’s not inevitable. But getting somewhere better requires recognizing that refusal, delay, and strategic disinterest can be every bit as consequential as formal opposition.

What I especially appreciate here is the restraint. Yes, there’s some clever CSS and a little JavaScript to help with positioning, but the whole thing is built on top of the platform, not in spite of it. That’s the interesting takeaway for me: we can build interfaces that feel bespoke without throwing away the reliability and accessibility native controls already give us.

I know someone that uses her screen reader on her mobile phone, but when she’s on her desktop computer, she uses a mangifier.

Different contexts, different tools, same person.

I know someone that uses voice controls on his computer. He uses direct commands like “Click Contact Us” when he’s near the start of his day, and commands like “Click link, twelve” when he’s near the end of his day with lower energy and less clear speech and a dry mouth.

Different energy/capacity, same tools, same person.

I know someone that uses a switch on his computer. He also uses the onscreen keyboard on his computer. The one that he chooses reflects the task he’s trying to accomplish and how he can minimize switching between the tools.

Different task, same context, same tools, same person.

Disability is not black and white… it’s every shade of every colour.

I immediately invited them to pitch us for the AI for Accessibility Grant Program that I ran for Microsoft. With so much focus on assistive technology to enable folks to work and accomplish common life tasks, I loved that the OneCourt team was interested in enabling people with disabilities to enjoy leisure activities like sporting events. Moreover, I saw the potential to enable Blind and low-vision parents to experience their kids’ sporting events, which could be life-changing for them.

Needless to say, they wowed both me and the rest of the seleciton committee. We funded them to expand their prototypes and pursue partnerships with different professional sports leagues, teams, and venues. They were ambitious and it’s paying off.

Fast forward a few years and they’re enabling a handful of Blind & low vision sports fans to exerience the Super Bowl in a whole new way, using their technology. It’s amazing and I could not be more proud of them.

Congrats y’all!