You asked for it:
This is an incredibly stupid take, and I genuinely can’t believe people are upvoting it.
Have you actually used an AI agent at any point in the last six months?
Your entire argument seems to rest on the bizarre assumption that describing what you want is roughly equivalent in effort to producing it yourself. It isn’t. That’s literally why abstractions and tools exist.
I can describe the architecture I want in a few paragraphs and have an agent generate a Mermaid diagram. I can give it a pile of documents and have it pull together information I didn’t manually write into the prompt. I can describe the structure and content of a presentation and have it generate the actual PowerPoint. I can give it a repetitive refactoring task that I fully understand how to perform myself and have it apply that change across a codebase.
The fact that I need enough expertise to verify the result doesn’t somehow eliminate the time saved producing it.
I know how to write Java without an IDE. That doesn’t mean IntelliJ becomes useless because I need to understand Java to verify whether the code it generates, refactors, or autocompletes is correct.
And the claim that requiring expertise somehow eliminates AI’s usefulness is particularly strange. Most useful tools require expertise. IDEs require expertise. CAD software requires expertise. Excel requires expertise if you’re doing anything remotely complicated with it. Their purpose isn’t necessarily to let an unskilled person impersonate an expert; it’s to make an expert substantially more productive.
Natural language also isn’t the only interface. Modern agents operate on files, repositories, documents, databases, APIs, tool outputs, search results, and existing context. The prompt can literally be “turn this into a presentation” or “diagram this architecture.” You don’t have to painstakingly reconstruct the entire source material in prose first.
There are plenty of legitimate criticisms of generative AI: hallucinations, unreliable output, loss of control in certain workflows, mediocre prose, inappropriate use cases, people blindly trusting the output, etc.
But “if you know enough to check its work, you might as well have done the work yourself” is basically an argument for coding in Notepad because a competent programmer shouldn’t need a stupid machine-assisted IDE.
Knowing how to do something and wanting to spend your time manually doing every part of it are not the same thing.
Neither do I need to know how a transformer works to use an AI agent. What does that have to do with anything?
I need to know Java to recognize whether IntelliJ’s refactoring produced sensible Java, just as I need domain expertise to recognize whether an AI agent produced sensible output. “Requires oversight and expertise” does not mean “requires understanding the internal implementation of the tool.”
No, it really isn’t, and this is probably the strangest part of your argument.
Specificity of requirements and effort of implementation are two completely different things.
“Take these 30 classes, rename this field, update its usages, add null checks at these boundaries, update the affected tests, and run the test suite” is a reasonably specific description of a task. It is quite obviously not equivalent in effort to manually performing every edit.
“Create a sequence diagram showing the interaction between these five services for this request flow” can take seconds to describe and considerably longer to manually construct.
“Take these documents, extract these specific metrics, compare them by quarter, and put the results into a PowerPoint using this existing deck as the visual template” is a perfectly comprehensible specification. Actually reading the documents, extracting the data, calculating the comparisons, creating the charts and assembling the slides is where the work is.
This distinction is the entire reason programming exists. A specification describes what computation you want performed. We don’t conclude that because SQL lets me precisely specify which data I want from a database, I might as well manually inspect every row.
And “it only saves time where you don’t care about shit-quality work” is just begging the question. You’ve defined AI output as shit and then concluded that anyone accepting AI output must therefore not care about quality.
The useful workflow isn’t “ask AI for something and blindly ship whatever comes out.” It’s “specify the task, let the machine perform the expensive mechanical portion, inspect the result, and correct or reject it where necessary.”
Sometimes that is slower than doing it yourself. Sometimes the output is shit. Sometimes AI is simply the wrong tool.
But the idea that describing a task with sufficient precision inevitably approaches the effort required to execute that task is just demonstrably false.
If that were true, half of software engineering wouldn’t exist.