</> htmx ~ Yes, and...

</> htmx ~ Working With AI: A Concrete Example

In this essay, Carson Gross walks through a concrete bug fix in hyperscript to show where AI helped, where it fell short, and why keeping a knowledgeable human in the loop is what kept complexity in check.

The Future of Software Engineering Isn’t What You Think

Over the past two decades, I’ve watched software eat the world, then hardware catch up, then Generative AI reshape both at the same time…

More Than a Tool

What We Learned from a Year of Conversations About AI

Is AI causing a repeat of Frontend’s Lost Decade? | Mastro Blog

AI is doing to programming what framework-brain did to the frontend before. Deskilling, or just working at a higher level of abstraction?

The New Software Lifecycle

I co-wrote a Google whitepaper about how AI is changing the software lifecycle. I'm not going to summarize the whole thing. Instead, here are the handful of ...

Something Big Is Happening

A personal note for non-tech friends and family on what AI is starting to change.

I Started Programming When I Was 7. I'm 50 Now, and the Thing I Loved Has Changed | James Randall

I still love developing but the shifts that AI have brought are tectonic and are forcing me to re-evaluate my own relationship to building things

The Future of AI Should Serve People, Not Platforms - The Liquid Frontier

On AI and building your own GIS software

Of the thousands of essays over the past two years surrounding AI and its implications are some very thought provoking ones with enormous implications for GIS. Some of the essays are around the the…

Resetting on engineering expectations in the age of AI

I’m accepting new sponsorships for The Modern Leader for 2026. If you’re interested (or you think your company may be interested), you can learn more here.

Field Theory: AI as Social Science Question, Object & Tool

Uses of advanced artificial intelligence are changing how societies organize labor, govern, produce knowledge, and make meaning. In light of these developments, this essay argues that AI models, tools, and systems pose three interrelated imperatives for social science: they demand renewed attention to social theories of how technology, human experience, and social order are entangled; they require study as objects of inquiry in their own right; and they offer capabilities that may transform—or upend—the practice of social investigation itself. From Weber’s analysis of rationalization to Du Bois’s study of technology and inequality to contemporary scholarship on algorithmic governance, the essay examines what social science distinctively offers: the capacity to historicize the apparently unprecedented, to trace connections across scales, and to center those most affected by technological change. It identifies how algorithmic systems are remaking the distribution of opportunity and risk as a central task of social inquiry and asks what futures social science might help bring into being.

Everybody needs a personal AI policy. Just ask Hank Green.

How can we reap AI’s benefits without melting our brains in the process?

Programming (with AI agents) as theory building

Back in 1985, computer scientist Peter Naur wrote “Programming as Theory Building”. According to Naur - and I agree with him - the core output of software engineers is not the program itself, but the theory of how the program works. In other words, the knowledge inside the engineer’s mind is the primary artifact of engineering work, and the actual software is merely a by-product of that.

How does AI impact skill formation?

Two days ago, the Anthropic Fellows program released a paper called How AI Impacts Skill Formation. Like other papers on AI before it, this one is being treated as proof that AI makes you slower and dumber. Does it prove that?

Automate the C-Suite - The Ideas Letter

Weatherby argues that Benanav’s and Morozov’s essays on AI and the left miss a deeper reality: Today’s AI is not a neutral tool operating within capitalism but the materialization of…