Is anyone actually at a company that is purposely trying to use a ton of tokens? It gets expensive really fast.
> You must understand what your AI generated code does
Absolutely yes.
> You must be able to do your job if your AI tooling disappears
Absolutely not.
Look, I'm an alright programmer. Not good, far from great. Interpreted languages work for me; add all that strong typing and compilation and it starts to go beyond what I'm interested in. Nonetheless, pre-AI, I have shipped many very functional, production-grade applications for many companies.
Now, I can write stuff in Go, and Rust, and it's fantastic. So much faster. The AI likes the strong typing, the test-ability, predictability, it all makes total sense. I'm using this stuff all the time, but I have not learned any Go; I'm too busy focusing on the parts the AI cannot do for me, like real requirements gathering, architecture, fit and finish, engaging stakeholders, etc. that still require the human touch. Maybe I could have learned some Go using that time, but at the end of the day my employer is paying me for results, not for my edification!
There are now huge parts of my job I cannot do without AI. Sure, it's like 800-1200 bucks a month of extra cost; ok; but with that extra low-5-figs a year of cost I am a much better employee in terms of my capabilities. It's easily delivering ROI for me, and therefore for my employer. Instead of sitting around wishing I had a Go developer to ask for help implementing a simple feature in a Terraform provider, I can just fork it and add what I need, try to submit it upstream for inclusion, etc. and the lack of language specific skills is no longer holding me back.
Take away the tool and I can't do that part of the job anymore, sorry. I can still do a lot, but slower, and honestly it would feel like going from a car back to walking, now; walking's fun, I do it recreationally for the sheer joy, but when there's hundreds of kilometres to cover in a short amount of time, the car is clearly the correct choice. So too is it with AI: we've invented the car for computers and only a fool would pretend he can do everything the same without it now.
Academia is the place with the least coherent policy. In the few institutions I'm aware of the AI rules for, the guide is usually 3 lines long and it is basically we don't promote usage of it, which is a meaningless phrase. Therefore you end up with students who are not supposed to use it unless they are international masters students who require it because of language barriers, and in that scenario, it is basically allow them to use it however they like even if it makes a mockery of the rigour of a degree. Lecturers can use it as and when they wish, then you get researchers who either use it endlessly or not at all. Then upper management who use it instead of using their own brain.
As a fun exercise replace AI with "junior" and "junior" with "mid-level." It holds up pretty well, as a manager you have responsibility for the work your team does and "make everyone put in more hours for no reason" is dumb. Maybe it comes across a bit neglecting of the "juniors" (in particular, it doesn't show any desire for figuring out ways for AI/"the juniors" to grow their responsibilities in a sustainable way).
Imagine reading that version as someone who doesn't know how big companies work. "But then they'll just fire all the mid-level managers, since they don't do any of the actual work!" Haha, boy would you be wrong.
For another type of incoherent policy: don't restrict your employees to 2025 models and then accuse them of being sticks in the mud when they say the models are inadequate.
DORA.dev (DevOps Research And Assessment) also point to having a clearly communicated stance concerning AI to be a foundational capability.
https://dora.dev/capabilities/clear-and-communicated-ai-stan...
When I see "in the year of our Lord" I immediately tune out the writer. Almost as bad as "Unreasonable Effectiveness"
> It’s Still Your Code... AI maximalists will read this section and scoff. They’re already vibe coding everything and have little to no idea what the generated code looks like.
This frames the argument like a dichotomy. And to be honest, using the Social Media "vibe-coding" as a strawman risks anchoring against something that's a mirage.
There are plenty of good engineers getting good results whilst accepting code-ownership as a continuum.
> If Claude goes down tomorrow, can you still do your job?
This is a valid counterpoint, but doing software is already a tricky set of dependencies. The answer here isn't automatically "you need to be able to do everything". It could simply be also use Codex.
I think the overall point is well made, I just don't agree with the absolute framing. There are things you can hand over AI safely. Even if you start small and increment it'll have a decent impact.