Agreed with everything @kevinriggle wrote here. Another angle on this to try with people who simply do not understand what software engineering •is•: “What’s the impact on the other 7/8?”
AI can generate code fast. Often it’s correct. Often it’s not, but close. Often it’s totally wrong. Often it’s •close• to correct and even appears to work, but has subtle errors that must be corrected and may be hard to detect.
All the above is also true (though perhaps in different proportions) of humans writing code! But here’s the big difference:
When humans write the code, those humans are •thinking• about the problem the whole time: understanding where those flaws might be hiding, playing out the implications of business assumptions, studying the problem up close.
When AI write the code, none of that happens. It’s a tradeoff: faster code generation at the cost of reduced understanding.
2/
The effect of AI is to reduce the cost of •generating code• by a factor of X at the cost of increasing the cost of •thinking about the problem• by a factor of Y.
And yes, Y>1. A thing non-developers do not understand about code is that coding a solution is a deep way of understanding a problem — and conversely, using code that’s dropped in your lap greatly increases the amount of problem that must be understood.
3/
@inthehands @RuthMalan every dev wants a greenfield project. LLMs shade even greenfield projects brown.
But then it's not the devs that are asking for this* so much as a managerial class looking for the sort of silver bullet that brings down both pay and the amount of time dealing with a type of worker they find difficult.
*not the ones who are any good, anyway
@rgarner @RuthMalan
Yup. All that.
And Brooks’s maxim that there is no silver bullet still stands undefeated.