GoKawiilIn talking to engineering management across tech industry heavy-weights, it's apparent that software engineering is starting to split people into two nebulous groups:
The first group will use A.I. to remove drudgery, move faster, and spend more time on the parts of the job that actually matter i.e. framing problems, making tradeoffs, spotting risks, creating clarity, and producing original insight.
will use A.I. to remove drudgery, move faster, and spend more time on the parts of the job that actually matter i.e. framing problems, making tradeoffs, spotting risks, creating clarity, and producing original insight. The second group will use A.I. to avoid thinking. They will paste prompts into a box, collect polished output, and present it as though it reflects their own reasoning. For a while, that can look like productivity. It can even look like talent. But it is a dead end.
The software engineers who will be most valuable in the future are not the ones who do everything themselves. They are the ones who refuse to spend time on work that A.I. can do for them, while still understanding everything that is done on their behalf. They use the time savings to operate at a higher level. They elevate their thought process through rigor rather than outsourcing it.
That distinction matters more than people think.
In this post:
The New Failure Mode: Outsourced Thinking
A.I. can already generate code, summarize meetings, explain concepts, produce design drafts, and write status updates in seconds. That is useful but also dangerous.
The danger is not that A.I. will make people lazy in some vague moral sense. It is that it makes it easy to simulate competence without building competence.
There is now a very real temptation to hand a model a problem, receive a plausible answer, and then repeat that answer as if it reflects your own understanding. That is close to plagiarism, but in some ways worse. At least when a student copies from another person, there is still a real human source behind the answer. Here, people can present machine-produced reasoning they do not understand, cannot defend, and could not reproduce on their own.
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