Commentary

Boris Cherny, who runs Claude Code, told Business Insider in May that the phrase “vibe coding” had started to annoy him, and that he’d gone looking for a better one. He’s not the only one who’s annoyed. The term itself doesn’t actually annoy me, though. I think vibe coding is a really good name: It […]

I hadn’t heard of Dan Guido until a few months ago, when I came across the video of a talk he gave at [un]prompted, an AI security practitioners’ conference. Dan is the CEO and cofounder of Trail of Bits, a software security research and development firm that works with companies in tech, defense, and finance.

The following article was originally published on Drew Breunig’s blog and is being republished here with the author’s permission. Thanks to natural language interfaces, AI applications can be prototyped quickly. You write what you want in English, hand it to a frontier model, and a working prototype appears in an afternoon. This is extraordinarily powerful

The following article originally appeared on LinkedIn and is being republished here with the author’s permission. We’re currently at the peak of the hype cycle. On June 7, Peter Steinberger posted that you shouldn’t be prompting coding agents anymore; you should be designing loops that prompt your agents. That same week, Boris Cherny of Anthropic

For as long as we’ve taught programming, the student’s code has provided a window into the students’ thinking. Errors, the code structure, the awkward working solution—all of it showed how someone reasoned and where they got stuck. It was never a clean window. Students have always copied, crammed, and borrowed, sometimes turning in work they

The following article originally appeared on Charity Majors’s Substack and is being reposted here with the author’s permission. A few days back I wrote a piece called “AI enthusiasts are in a race against time, AI skeptics are in a race against entropy.” I have notes on a whole pile of AI-related topics that I’d

Gene Kim was grilling dinner for his family on the evening of June 12 when his phone told him that Fable 5 was no longer available. He’d heard the day before from Steve Yegge that the model was going away in 10 days, and he’d spent that first day starting on a plan to get

The price of adoption euphoria You played entirely by the book. You procured the most capable enterprise models, mandated adoption across your teams, and put the right metrics in place. The promise was a predictable boost in efficiency. And at first, it delivered. The demos were flawless. The prototypes worked. The agents reasoned with a

“Help! There are too many [LLM bug reports, blog posts about LLM bug reports, books, treatises, codices, scrolls, papyri, cuneiform tablets]! How do I choose which to read?”  —Many people, presumably Stop there! If you are reading this, ask yourself how you got here. Did Substack’s algorithm recommend this article for you? Did a juicy

The first expensive agent run doesn’t look like a governance problem. It looks like a billing problem. A team opens its first agent invoice after the meter turns on, sorts the runs by cost, and finds one that cost 40 times the median. The provider meter shows tokens and a total. The application logs say