GoKawiilA 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 like to cover in depth: AI mandates, communication norms, code review, AI art, and more. Unfortunately, I got too many interesting responses to my last piece, and now I have to address those before I can move on to other topics. 😉
There were two types of interesting responses: the first on the technical merits, the second on ethical grounds. I will respond to each of these separately. Let’s take the technical side first, because it’s easier.
Somehow, a subset of readers came away believing I was telling everyone to ditch code review and push their shittiest code straight into production without reading it, right now, tout suite.
That is not what I am doing. That is not what I think you should do. But I did not pick that example at random, and I will tell you why.
In 2025, the question was whether AI could ever generate “good” code
It’s easy to forget, but for most of 2025, the idea that AI-generated code was slop and might always be slop was not only a reasonable position to hold, it was the default, mainstream position.
That question was answered decisively last November. Ever since Opus 4.5 came out, AI has been able to generate code that is approximately as good as that of the median software engineer, at least for common patterns, and much faster and more cheaply. I came out of a book hole and realized this in January, and over the first few months of 2026, it seemed like everyone around me was having a similar realization.
But many saw it coming much sooner.
The popular narrative holds that Opus 4.5 was what changed. But Opus 4.5 was more like the tipping point. Agentic harnesses (the code that wraps the LLM in a loop with tools) became a real thing in mid 2025, with precursors building back to late 2024. Tool use, function calling, MCPs…all of this wave was building over the course of 2025, and crested into real general purpose usability at the end of the year.
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