If you have a .6 chance of success on any particular outcome. Long term win or loss is down to your behaviour. If you double or nothing every time loss is guaranteed. The right strategy will win over the long term.
Same with most people "doing a startup" or "opening a restaurant". There will be arguments all day long about how these affairs are technically possible and quite lucrative if everything goes according to plan. But the reality is that vanishly few people are equipped to identify and stick to the right plan. Reality meeting theory.
I've told my developers they can use agentic coding if they want, but they must never mention it in the course of development. Not because I don't want to know, but because it's not going to change my evaluation of "their" work. If they can use the AI and get to a point that they can submit a PR that they themselves understand, then technically speaking, what do I care? But if it breaks the build or does something stupid and they don't understand it, it's going to be a bad day for them, whether they wrote it themselves or copied it out of StackOverflow or had Gemini do it.
Nobody has taken me up on this offer, because I think they know that they aren't going to have the extreme discipline to do the hard thing of understanding "someone" else's code and sign their name to it.
That seems lazy to me. "I'm not willing to see if I can do a better job by using this tool, because I don't want to bother analyzing it's work".
While I mostly agree with your sentiment, I think there is an important difference. Unless you are attempting advantage play (99.99% of gamblers are not, and casinos ban the few that are), there is literally nothing you can do at a casino to make it a positive EV activity. No amount of skill, drive, effort, or anything other than pure luck can consistently generate profit at a casino.
A startup/business, on the other hand, can be effectived by your actions. Luck obviously plays a large factor, but you have some level of control over the outcome.
This is where my employer has ended up after extremely cautious AI adoption: _must_ be reviewed by a human, and the human whose name is on the gerrit review is responsible for the quality of the work.
For some reason the OpenAI dashboard shows me how much money the company as a whole has spent? It's still a very reasonable-looking amount of money and a tiny fraction of salaries.
They probably aren't making a loss on the $3.10 Manhatten either.
https://www.casino.org/news/vegas-myths-re-busted-the-end-of...
I agree that people will rationalise being in a losing situation as a winning situation. That does not change the fact that winning situations can exist.
Developers have to gamble on whether they will be better with AI or without.
The no excuses criteria means if they choose AI and it performs well, you both win, if it performs poorly they lose.
If they don't choose AI but colleagues do and it performs well, they lose relative to their colleagues.
The sensible solution would be solidarity and all reject the offer. Don't play the house.
Back two years ago, a lot of them were playing with AI code gen. They also have some explicit tasking for using agentic AI tooling to evaluate for use in an analytics product we're building, so it's not like they don't even have access or permission or time to try. We're just not religious converts who think AI would one day replace humanity and we should be working to help it.
Through the lens of "don't ask don't tell", throughout all of this, I've not seen any significant change in work output. The folks that have used AI for the specific research tasks they had did not produce solutions faster than without it. They spent huge amounts of time on things like getting the AI to produce results that have any meaning beyond what was trivially reportable in the data already, reliably reproduce the same results, even reliably operate over the full dataset. It's not been the go-fast button everyone has said it would be. I think folks are optimizing for reducing their cognitive workload: it's easier to understand, modify, and live with code you wrote yourself.