Most developers don't love writing tests, or updating documentation, or working on tricky dependency updates - and I really think we're heading to a world where AI can take the load of that and free me up to work on the most interesting and complex problems.
What is the job for the developer now? Writing tickets and reviewing low quality PRs? Isn't that the most boring and mundane job in the world?
So they won’t like working on their job ?
I use all of these tools, but you also know what "they're doing"...
I know our careers are changing dramatically, or going away (I'm working on a replacement for myself), but I just like listening to all the "what we're doing is really helping you..."
Those orgs that value high-quality documentation won’t have undocumented codebases to begin with.
And let’s face it, like writing code, writing docs does have a lot of repetitive, boring, boilerplate work, which I bet is exactly why it doesn’t get done. If an LLM is filling out your API schema docs, then you get to spend more time on the stuff that’s actually interesting.
Doing either of them _well_ - the way you do when you actually care about them and they actually matter - is still so far beyond LLMs. Good documentation and good tests are such a differentiator.
A good example of the kind of result is something like the Laravel documentation[1] and its associated API reference[2]. I don't believe AI can help with this.
[0]: https://en.wikipedia.org/wiki/Docstring
If/when will this take over your job?
I get paid for the mundane, boring, annoying tasks, and I really like getting paid.
Where does the most come from? There's a certain sense of satisfaction in knowing I've tested a piece of code per my experience in the domain coupled with knowledge of where we'll likely be in six months. The same can be said for documentation - hell, on some of the projects I've worked on we've entire teams dedicated to it, and on a complicated project where you're integrating software from multiple vendors the costs of getting it wrong can be astronomical. I'm sorry you feel this way.
Actually if you want well-written prose you'll read AI slop there too. I saw people comparing their "vibe writing" workflows for their "books" on here the other day. Nothing is to be spared, apparently
I would not be surprised if things end up the other way around – humans doing the boring and annoying tasks that are too hard for AI, and AI doing the fun easy stuff ;-)
I expect though that most people don't read in that much detail, and AI generated stuff will be 80-90% "good enough", at least the same if not better than someone who doesn't actually like writing documentation.
> What is the job for the developer now? Writing tickets and reviewing low quality PRs? Isn't that the most boring and mundane job in the world?
Isn't that already the case for a lot of software development? If it's boring and mundane, an AI can do it too so you can focus on more difficult or higher level issues.
Of course, the danger is that, just like with other automated PRs like dependency updates, people trust the systems and become flippant about it.
I'd argue the vast majority of software development is neither critical nor commonly used. Anecdotal, but I've written documentation and never got any feedback on it (whether it's good or bad), which implies it's not read or the quality doesn't matter.
If we're expected to even partially believe the marketing, LLM coding agents are useful today at junior level developer tasks and improving quickly enough that senior tasks will be doable soon too. How do you convince so many junior and senior level devs to build that?
It’s very, very far from possible today.
The goal here is for it to be able to do everything, taking 100% of the work
2nd best is to do the hard, big value adds so companies can hire cheap labor for the boring shit
3rd best is to only do the mundane and boring stuff
> There's a certain sense of satisfaction in knowing I've tested a piece of code per my experience in the domain coupled with knowledge of where we'll likely be in six months.
one of the other important points about writing unit tests isn't to just to confirm the implementation but to improve upon it through the process of writing tests and discovering additional requirements and edge cases etc (tdd and all that)i suppose its possible at some point an ai could be complex enough to try out additional edge cases or confirm with a design document or something and do those parts as well... but idk its still after-the-fact testing instead of at design-time its less valuable imo...