the derivative and repetitive nature of most coding tasks.
when I ask GPT for some code and it spits out 200 lines of boilerplate in 2 seconds, i feel sick. what am i doing with my life.
similar to how houses are built from prefabricated components. Imagine that the AI is producing these pre-fab parts to order. But the design of the interfaces and assembly is still an art.
if you think of your job as a mason assembling bricks to build components, you are mistaken. you need to think of your job as an artist creating systems that work well built out of pre-fab components.
there is a story of how woz wrote the entire software for the early apple in assembly. nobody does that anymore. because, we have tools that produce assembly like compilers and such. that didnt take away the jobs of software engineers, because, someone had to now produce code at a different layer of abstraction.
imagine you ranting at the compiler 50 years back because it took away your job producing assembly code.
I have never been able to use a large output directly from an LLM. They’re useful for starting from nothing or tickling your brain when you’re blocked on something, but they’re nowhere near making me wonder what I’m doing with my life.
There’s so much more to software than code. I get that the final implementation is code, but the path to that delivery is incredibly complex. Especially with existing code belonging to relatively non technical teams. They need a real human to connect to them, their history, current and future needs, nuances of the teams’s capabilities, etc. AI is nowhere near serving teams like this, and I have a hard time imagining when that would change.
On the other hand today it's already passably good at generating stuff that requires less precision and less accuracy (i.e. humanities type stuff, marketing, managerial/secretarial tasks, etc.).
So while you might be looking at your own CS job eventually being in jeopardy, whole swaths of alternative careers you aren't looking at are probably way, way more in jeopardy.
Really? My experience is that it gets better every release (every few months to a year) and then gradually worse until the next release.
The real value is Doing Useful Stuff with the code, written by you, your LSP, or AI.
The robots only take the jobs we give them. I don't give them code, more using LLMs as a sort of consultant with the pathological urge to lie and please.
I think every tech-related company looked at the high bar at big tech, assumed the algorithm questions was the only signal (it's not), and have been poorly aping that ever since.
I also think a simple 20 minute discussion between a hiring candidate and an engineer simply discussing how to build something will give you better hiring signals than any Leetcode challenge.
If bullshitters are making it into your organization at the higher ranks that's something else... :(
In other words, if you were starting college today, would you still do tech? Is it still better than getting any other job for equivalent pay bands?
Specifically comparing early career job seekers:
* Easier/harder to get $50-100K tech job versus $50-100K job in other fields?
* Easier/harder to get $100-150K tech job versus $100-150K job in other fields?
* Easier/harder to get $150-200K tech job versus $150-200K job in other fields?
Other fields are things like marketing, accounting, law, medical, biotech. A quant/finance job is probably CS or CS adjacent these days so its basically a tech job.
My take is that by the time you get above $130K there probably is not any other field outside of tech where this is possible unless there is some very unique skill.
And instead of annoying but somewhat objective leetcode/live coding whiteboard interviews; hiring is way more subjective, credential based, network based and gate kept.
Of course medicine has other downsides as a career field which makes it maybe not a great choice unless you really love it.
> Algorithms are tiny parts of large systems. The algorithm part can usually be abstracted as an API call that provides some value(s) with inherent uncertainty; an ML endpoint is in essence an API call with few or no side-effects that returns an uncertain value. It turns out, the system design surrounding this almost always matters more than the algorithm and the dumb algorithms tend to do well enough anyway.
I think this is basically dismissing almost all APIs and algorithms in favor of system design. But system design is pretty similar in many apps, while the value of each app is very different. So clearly the API/algorithm is very important, and often the most important part.
I also disagree about AI not taking jobs. GitHub copilot definitely makes programming about 30% faster. To keep up the jobs, we would have to write 30% more code. But it seems innovation is the limiting factor more than typing code, so maybe we'll only write 15% more code, and we can have less devs.
compilers eased the production of assembly code. that didnt reduce the need for folks coding at a different layer of abstraction.
The fed just made it official that the easing cycle is beginning. The 10yr has already front run them by about 1.7%.
So if the article conclusion is correct tech job market could look good going into the new year.
In my experience a lott of LLM usage in B2B is fairly basic (translation, summerization, data extraction, categorization) and fairly well handled by current SOTA foundation models. Could this be improved by custom/finetuned models? Sure, but in nearly all cases I have seen the ROI of improving other parts of the application is way higher than the investment in developing and maintaining custom models.
i update my cv, upload it to the big recruitment websites, recruiters do all of the work, my phone rings 3-5 minutes later and the calls barely stop for a second until i've been in my new role for 2-3 months. interviews are always laid back conversations over the phone or a teams call with no curveballs, just the standard questions like what kind of stuff do you work on in your current job, what tech stack do you use, what do you think about [current popular thing], etc. i'd say i get an offer from about half of the interviews i do.
my only real complaint other than the amount of recruiters who deliberately waste mine and their own time for reasons known only to them (which has always been a thing), is the very obvious coordinated push to get people "back in the office" spilling over and affecting developers, which means there are way less fully remote roles than there were even before covid.
