Essays on how software engineering is changing with AI, written from daily practice.
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The fight over whether AI is good or bad is the wrong fight. AI is a friction-removal engine, and there are two kinds of friction: the kind that is building you, and the kind that is only taxing you. Telling them apart, in the moment, is the whole skill.
Most defenses of AI are about productivity, and they are weak. The strong case is older and bigger: this is the next rung on a seventy-year ladder of removing effort that was never building anyone. Here it is, made at full strength.
AI does not destroy your work in front of you. It moves the cost somewhere you cannot see: to later, to the invisible, to the version of you that stops getting built. The strongest case against leaning on it, made in full.
AI is strong in one place and confidently wrong half a step over, and from the inside the two feel identical. The real skill is not prompting. It is knowing when to delegate, when to steer, when to verify, and when to think alone.
AI took the typing, and the cost of software engineering did not go away. It moved from the hands to the head and got heavier. The new scarce resource is your attention, and the new discipline is managing it.
DevOps was always a feedback loop. The first one ran between people. The one worth building now runs the system back on itself, so every failure and every change makes the next one cheaper and safer. The recursion is the compounding.
Agent mode is not a faster way to type. It moves the unit of thought up from syntax to intent, turns you into a conductor of parallel work, and makes the real bottleneck the clarity you can hold in your head at once.
When a system gets too big to hold, almost everyone reaches for the same move: make it simpler. It is the wrong move. You cannot simplify the ocean. You can only chart it. This is about the difference between simplicity and legibility, why decisions quietly migrate to whoever holds the context, and how to make a complex system visible enough to navigate without pretending it is small.
Not prompts. Real file access, real execution, real consequences. The patterns that hold in agent mode and the failure modes nobody warns you about.
AI hasn't replaced software engineers. It has moved the bottleneck. The cost of writing code dropped to near zero; the cost of deciding what to build, how to architect it, and when to ship became the whole job. A field report from a year of running production work in agent mode.
"Vibe coding" means throwing prompts at a model and hoping it works. That is not what AI-assisted development is. The difference matters, and it is the difference between amateur hour and professional craft.
The code was AI-generated. Beautifully elegant. It had sailed through review, passed all tests. And it had a subtle flaw that only manifested when two processes collided in production. The quality paradox: code can be technically perfect and still fail in ways you never imagined.
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