Recent searches
Search options
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/
Increase the cost of generating code by a factor of X; increase the cost of understanding by a factor of Y. How much bigger must X be than Y for that to pay off?
Check that OP again: if a software engs spend on average 1 hr/day writing code, and assuming (optimistically!) that they only work 8 hr days, then a napkin sketch of your AI-assisted cost of coding is:
1 / X + 7 * Y
That means even if X = ∞ (and it doesnt, but even if!!), then Y cannot exceed ~1.14.
Hey CXO, you want that bet?
4/
@inthehands Oh, why hello, Amdahl!
@OmegaPolice
That’s it: Amdahl’s Law law except optimization actually creates large costs in the other parts of the system!