Hello. I am Paul Kinlan.

Link: AI Focus

I've launched a new blog. It's called AI Focus, and it's dedicated to exploring the intersection of artificial intelligence and web development. My goals of the blog is to cover a range of topics that I think are going to affect the web and web development in the coming years.

Why? I think that the nature of the web has changed and it will change even more in the coming years. I love the web and web development, but I don't think we can idly sit by and assume that "the web will always win". I don't "always bet on the web", I bet on the people who build for the medium that is the web, that is the users, the authors, the developers, the designers, the creators and web browser engineers. I think we are going to have to adapt to the changes that "AI", or at least the technology that is Large Language Models, bring to the web, and I want to be at the forefront of that change.

I'm experimenting with a more essay focus to the writing which pose more questions than answers at the moment. I've been silently writing articles on it for the past couple of weeks, covering topics like:

• The future of embedding?
• The future of linking?
• Will there be a super-app?

My buddy Andre Bandarra has also written some great pieces about Mashups and assistance in web development

Let me know what you think, and also what topics you'd like to see covered in the future. I'm always looking for new ideas and perspectives, and I want to expand my understanding and opinion.

Link: Diving into the Data on Feature Availability and Adoption [BlinkOn 20] - YouTube

This is a great talk from Annie Sullivan at BlinkOn 20 about the availability and adoption of web features. Annie discusses the importance of understanding how features are used in the wild, and how this can inform the development of new features.

I took a few notes on the talk, which I thought were interesting and linked to them below:

• Core Web Vitals: Discusses work on improving web page quality metrics (LCP, INP, CLS) using HTTP Archive data to identify and fix issues [00:00:21], [00:00:50] and how this was the groundwork for the talk.
• Baseline Data: A baseline dashboard by the WebDX community group provides metadata on web features, including their availability status and [00:03:32] and how Annie would use this aligned with usage data to understand the adoption of web features (rest of the talk)
• Key Findings:
  • Wider availability leads to higher adoption [00:05:56] <-- We all had a feeling this was the case, but it's nice to see it backed up with data.
  • Feature adoption isn't significantly skewed by website popularity [00:06:15].
  • 1. we can do splits on data easily, 2) HTML and JavaScript features show clearer adoption patterns than CSS [00:07:19].
  • HTTP Archive data aligns well with real Chrome usage data [00:09:27].
• Analysis Tools: Uses HTTP Archive and BigQuery to analyze feature usage [00:10:14].
• Adoption Factors:
  • Site-building platforms (e.g., WordPress) [00:12:54].
  • Third-party embeds (e.g., YouTube) [00:08:52].
  • Progressive enhancement with fallbacks [00:17:43].

Our team has long been pushing to understand API usage and how collaborating with site-building platforms can help us understand the impact of our work (selfishly for me), but I do think broadly that this type of insight helps us get more investment in to the web platform and helps us prioritize the right things.