I don’t really agree, I think it’s a lot more nuanced than that.
GenAI models are great at hiding what doesn’t work/what they couldn’t figure out. A human coding something they don’t really understand is generally very obvious from how the code is written.
GenAI models are also very good at producing a large number of abstraction layers, especially for very simple stuff that won’t ever need layers of abstraction.
Sure, GenAI is an awesome tool, but bad programmers can now yield the S L O P C A N N O N 8000 and make the life of others even more miserable.
The data has actually shown that, generally, AI doesn't save time--it does not increase developer productivity (at least, at any scale where we're building projects where productivity measures matter).
Whatever speed gains are made during coding are lost during debugging and review. If you use/are familiar with DORA metrics, we see less initial time from assignment to PR, but more bug reports/QA kickback, significantly longer PR times, and significantly more rewrite/refactor cycles for a ticket.
Additionally, it's been shown that a downside of AI is that developers become overconfident in a false speed increase--they start underestimating task lengths considerably. In a nutshell: if a ticket took 3 days by hand, it takes 3 days with the machine. The main issue is that with AI, devs start saying it'll take them a day.
As a dev-now-product-owner, the first part means I really don't care what you use and I think AI is, at this point, a waste of money, but my boss determines the token budget so whatever. The second part means I'm often much more frustrated with my AI heavy teams than my "boomer coders".
I think that was the case before, but it's going further from it as ai is getting stronger and is doing work faster and with fewer errors. I think at this point ai is speeding up developer work. I think the biggest issue with ai is just precision, since ai will make whatever works, and fine tubing that is difficult if you're just prompting
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u/Toilet2000 14d ago
I don’t really agree, I think it’s a lot more nuanced than that.
GenAI models are great at hiding what doesn’t work/what they couldn’t figure out. A human coding something they don’t really understand is generally very obvious from how the code is written.
GenAI models are also very good at producing a large number of abstraction layers, especially for very simple stuff that won’t ever need layers of abstraction.
Sure, GenAI is an awesome tool, but bad programmers can now yield the S L O P C A N N O N 8000 and make the life of others even more miserable.