Thanks for sharing your process! It's helpful and refreshing to hear from someone about how they engage with AI when writing, and where / when the detection tools may fail.

(We obviously live in a more nuanced world than most social media interactions might make you think :P)

> On a lighter note, decades ago, in middle school, we had an exercise to summarize a book we read.

My first experience with plagiarism was in first grade, when we were told to write a book report about a subject during our library time. I diligently took my book on the musk ox and copied three pages word-for-word into my notebook as my report. I can't remember when or how we learned this wasn't "right", but I still think back on that and laugh.

Sorry but it's very obvious you used an LLM for more than just suggestions. Ironic given the point of the article.

Taking you at your word, your A.I. revision process nonetheless seems to have yielded content which may as well have been generated at the start for how difficult it is to get through it.

    The valuable engineer is the one who sees the hidden constraint before it causes an outage. The one who notices that the team is solving the wrong problem. The one who reduces a vague debate into crisp tradeoffs. The one who identifies the missing abstraction. The one who can debug reality, not just read code. The one who can create clarity where everyone else sees noise.

This is a list of six things, disguised as an actual paragraph. Of sentence fragments disguised as actual sentences. Etc. Either you wrote this yourself and the AI didn't tell you "this is repetitive and list-y", or...

    "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."

    "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."

    "In that world, the engineer is not replaced by A.I. The engineer becomes more leveraged because they are operating above the level of raw output."

    "The ability to explain why something works, not just that it appears to work."

    "That process is not optional. It is how engineers acquire and elevate their competency."

    "The support system may make you look functional, but it does not make you capable."

    "The challenge is not merely adopting A.I. tools. It is protecting the conditions under which real thinking, learning, and craftsmanship continue to thrive."

    "They will need interview loops that test reasoning, not just polished answers."

    "The organizations that handle this well will not be the ones that simply push A.I. adoption hardest. They will be the ones that learn to separate leverage from dependency, acceleration from imitation, and genuine capability from convincing output."

^ Which of these are your thoughts? They all look like slop to me.

Don't do it man. just stop. you loose something of yourself when you turn to AI