AI demands more engineering discipline. Not less

Charity Majors

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AI demands more engineering discipline. Not less<br>If you lived through the shift from handcrafted server pets to immutable infrastructure, you should sense something oddly familiar about what's happening now.

Charity Majors<br>Jun 15, 2026

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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.”<br>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. 😉<br>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.<br>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.1<br>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.2<br>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.<br>But many saw it coming much sooner.<br>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.<br>That’s what the enthusiasts were trying to tell us last year. Not only “this is coming”, but “this is coming faster than you think.”<br>As it turns out, they were right.<br>It was reasonable to be skeptical the first time

As you may know, I come from the reliability side of the house. The compliment I will pay to myself and my people is that we do not struggle to adapt to new realities. As soon as a problem is real and in front of us, we adjust smoothly, even eagerly, thanks to an unwholesome zest for lapping up disgusting technical messes (and the campfire tales we get to tell later).

The un-compliment I will pay myself and my people is that we sometimes struggle to accept that progress is real, that the continued existence of bugs and edge cases does not diminish the fact that huge swaths of problem space do get more-or-less solved over time, to the point they can be taken for granted by most people.3<br>The speed at which code went from total crap to “ah damn, that’s not bad” is what I have in the back of my mind, as enthusiasts are telling us that harness engineering and AI validation is real, it’s already here, and it’s getting better astonishingly fast.<br>Holding out for “I’ll believe it when I see it” was forgivable the first time, but much less so the second time. This is what it feels like to be on the inside of an exponential change curve, turns out.4<br>What happened in 2025, exactly?

I want to pause here and be very clear about what I think is happening. Then I’m going to tell you what specifically I am excited about, and why.<br>You are under no obligation to join me there. But there are way too many sweeping statements out there right now about “it was never X” — “it was always Y” — “the future belongs to xyzzy” 🤮 — and I want to be crystal clear how conditional and specific and contextual my claims are.<br>What happened in 2025 was this: the economics of code production were turned upside down. Instead of being very hard, time-consuming, and expensive to generate code, it became effectively free and instant. Lines of code went from being treasured, reused, cared for and carefully curated, to being disposable and regenerable, practically overnight.<br>For most of computing history, the primary way people have learned to understand software is by writing the code. Once you've achieved some mastery, reading and discussing code gets you most of the way there. (I might argue that software engineers have always relied far too heavily on the code instead of sensemaking the system through observability.)

“The real product of a software...