I'm damn sure the answer is "no", but the devs at my workplace are all in on it in a way that's not as absurd on the surface as the "coding is a solved problem" kind of tech bros. There's an emphasis on the "human in the loop" that I think is far from sufficient; we used to have a human in the loop, it's called actually writing your fucking code!
As a sample, this is from a transcript of a recent discussion about AI with some devs on my team:
Me, a senior dev:
To be clear, I'm not saying not to forego the human in the loop. I'm pointing out that there is an inherent contradiction between using agent as our main means of writing code and actually being able to review all of its output -- be it before or after opening the PR. I'm worried that we'll end up in a position that we're expected to do something intractable, if not strictly speaking impossible.
New mid-level dev:
I just think we should still be responsible for reviewing all the output. Like how I see the before vs now is:
- Before: human plan -> human write -> human review
- Now: human plan -> claude write -> human review (+ claude review)
And in effect we're just as responsible for reviewing every line of the Al code as we were for reviewing every line of human code. Once that changes that's when the Al slop starts coming out So we should never end up posting a PR where we're like "hey guys claude wrote this so do the thing you do for claude PRs"
Team tech lead:
@AppetiteOfExcess, this is a problem across all dev teams in every industry. It's a huge issue. I think we need to lean on Al to speed up PRs, but how we do that is not well defined yet. I think it can help us get our head around a PR faster. Maybe we need to made an artifact for some PRs that give a breakdown of what is changing. Then we can grill Al once it understands the changes. That might speed things up a bit. The important thing is to really understand the code and the impact of the change.
@mid-level_dev I agree with you but I think the new process will be more like the following
- Humans (the whole team) plan by making highly defined stories
- Al makes an implementation and test plan
- Human reviews plan
- Al executes the plan with human oversight at certain steps
- Al does a review using /code-review (new context by default)
- PR is posted with change overview
- Human uses Al to understand the changes and review the code
I don't know how to push back on this while being taken at all seriously. It has me considering that maybe I'm in the wrong for rejecting a tool that is considered useful by all but a few stick in the mud devs, and that those devs will never have a shot at a job again unless they pull their heads out of their asses and join our modern "AI"-driven world.
It isn’t possible for a human being to write code responsibly.
Deepseek (the not very smart but very cheap one from China) is running a 2-3x profit on their gpu hours. That means that even with last gen tech running not generally considered very “good” models it’s still profitable to sell inference at 15 cents per million tokens in(.003 cents cache hit!) and 60 cents per million tokens out.
While the deepseek model loops and makes mistakes more than a Claude for example, when used with a harness it is equally effective if a little slower but at over ten times lower cost.
The point of this isn’t to bamboozle you with facts and jargon but to show in a clear way that what has happened in programming with llms will not go away with some bubble pop.
If you want to stay in your industry, get okay with it. I like deepseek and glm.
From the computer security side of things it has been worth it to recognize that we are currently in a triage process industry wide, that the best process will have to be fixing bugs as fast as possible no matter how and we can deal with the problems introduced by those patches later.