It's brutal, my son with a CS degree hasn't been able to get to single live interview ina year. A couple of screens has been it. I've reached out to my network, and the reply is always we're not hiring any juniors.
AI is the biggest threat in over a generation to seniors who aren’t investing in keeping up. Managers without an instinct for AI are an endangered species as well.
Basically the only hard part for old people is getting USED to using AI. Some haven't, but it only takes a few weeks to do. After that, experience and taste really comes in handy and that can't be developed overnight.
If your questions are sharp, probing for detail, and intelligent. Have you seen how people question AIs? It's as if they can't even conceive of the AI being able to supply specific detail.
For this kind of task, is linking to pastebin etc acceptable instead?
Either way thank you tstrimple for going in and looking!
But if I had to use AI for coding I don't think that it would take me very much time at all to get into the swing of it. I wrote code by hand for decades, so I know how to judge whether it's producing something that looks reasonable.
Fun note though, my work these days often involves telling AI to solve a problem and me asking it why it wants to do something a certain way.
It often has to patiently explain something like why the bazel rules need to be modified to accomplish my ends goals, and has to reiterate key concepts about a part of the codebase I'm unfamiliar with these days.
Really the only reason I'm there is to make sure it makes the changes as clean and efficient as possible, without unnecessary complexity that's hard to read.
Just keep your guard up for when the answer to "why" may be just a post-hoc "rationalization".
> AI is the biggest threat in over a generation to seniors who aren’t investing in keeping up. Managers without an instinct for AI are an endangered species as well.
New tech has always been the biggest threat to seniors who aren't investing in keeping up.
Because you can’t shortcut experience. And AI multiplies that.
I’ve seen what ai-focused good senior dev can do and it is scary.
Now the senior can use the AI instead of dealing with a junior.
Plus the biggest danger I’ve seen numerous times is the junior engineer can’t easily tell if the AI is wrong.
They either accept it as correct or spend more time trying to fix AI output with an AI in an area they don’t have the skills for.
Seniors will become more valuable as that knowledge is lost and AI isn't capable of full replacenent.
I use AI daily and it takes almost no extra brain power to use.
It's high variance. A young person can move fast because they lack the accrued assumptions of a senior, but that also means they can quickly move in the wrong direction because they lack the wisdom to identify mistakes before they pile up.
"Use AI" isn't really a skill, getting an implementation is now as easy as google for an answer was for our generation. A senior can trivially learn this. But sniffing out the bullshit and knowing when you're going astray still requires a critical eye that not everybody is going to have.
So it seems reasonable to me that moving more slowly and being more cautious, letting the uncs use their knowledge to keep things from going too far afield, is a really smart idea.
Is it Software or another problem domain? What problem are they attacking, what stack/method are they using?
One states that more junior people will excel. Younger people tend to be more hip to new tech trends, more natively immersed in changing times. And the contemporary AI tools eradicate any knowledge & wisdom gap that the seniors may hold over them. Thus, they'll be faster.
The other school states that the most important thing right now is the wisdom of experience. That the AI tools have made everything *but* the wisdom pretty much an afterthought. Thus, there's no point in having someone who doesn't have deep wisdom.
Which is right? Probably a little bit of both, depending on one's exact needs.
We are a network tooling team, and now we think our next hire will be a young network engineer who probably will generate code that we will have to review carefully, but we have to do that anyway, because we can't really afford having our engineers stuck on a basic knowledge of networking issues.
In any case, thanks to AI everything have a SDK so we won't have to make in-house library to automate everything (thousand of hours making libraries for cisco, forti, zscalers and other lost, but to be honest, good riddance), so the demand for engineers in my situation will decrease.
There is a reason why youngest developers are more productive. They accept everything Agent suggests. They don't understand or care. They rely on your review of the Agent output from prompt they copy-pasted from JIRA. So you spent your time reviewing it instead of your own work.
From study titled "The Widening Gap: The Benefits and Harms of Generative AI for Novice Programmers" https://dl.acm.org/doi/epdf/10.1145/3632620.3671116
>> Without building this solution, and instead just taking what ChatGPT generated, they had skipped crucial steps in the programming problem solving process, and were now lost
When you skip the problem-solving process and take the LLM's first output, you're not building the cognitive framework needed to debug or maintain that code.
Fortunately I have some unique skills that allowed me to land a gig.
The interesting thing is people recommend "networking" and people think it's like... meeting people at industry events or reaching out to linkedin connections but that's not really how I see networking working in real life. The networking that actually gets people jobs is networks from people you've already worked with before, or your professor is on the board of the company or like.. your parents know the exec team really well etc. So new grads truly are disadvantaged.
I say the are three levels of "networking", and peeling back the layers helps to understand why the term can become so nebulous
1. "Associative" networking where you reach out to people at your old school and work but people you otherwise never met nor worked alongside. They vouch based on what they see and know about your associations. They might refer, but often can't do much about the process but poke at the machine.
2. "familial" networking where you reach out to friends/colleagues you have worked with and can personally vouch on your behalf. They might be able to help churn a bit, but are ultimately still beholden to the process.
3. "Influential" Networking where you do either #1 or #2 but your network evolves into leadership, management, and founders. People who have the ability to actually hire you. Often cutting through the HR cruft itself.
3) is what you want, but fundamentally isn't different from 1) and 2), except in who you know. You invest in 1) and 2) in hopes that they become 3) farther down the line, but for a new grad that investment will take a very long time to occur. Reaching directly out to 3) is hard for many reasons (some professors being an exception. Hence why certain schools can be so impactful), so it's often not an option at the new grad level, since you lack any real leverage to bring to the table. If you have the ability to contact them at all.
E.g. under traditional hiring you only do a background check at the end - this means there are implicit decisions being made that nobody calls out explicitly during the process.
The reality is any person in an org actually has to act in the interest of the shareholders - people who are lower down the totem pole do what their manager says - but the manager of a manager of a manager is held accountable by the shareholders via the board. Shareholders want who is the best person not who is someone's preferred hire (which can be for reasons that have nothing to do with productivity). If there was a way to enforce this - you can bet they would.
Essentially what I'm saying is, because the existing systems suck we fall back on mechanisms like this.
There was barely any new construction going on for a couple of years and once it started anew, there was a gap as while people were retiring, new hires weren't replacing them.
I guess we're just going to shrink as a field until the market won't be able to handle it.
Many people here lived through ridiculous times. It was possible to make 1M in a year without incredible skills/hard work. Big tech was and still is full of these people.
I'm not saying that was a bad thing at all, but it always felt unsustainable. CS salaries will decline and fewer people will want to be software developers, balancing the market. Then it may go back to where it came from with the geeks sticking around. No more coding bros. Maybe that's okay.
When I got my degree, I never expected more than a slightly above average salary. I do this because I love it and can't imagine doing anything else. I was lucky and I'm thankful for the luck I had.
When I was in high school, I lied to girls about what I was planning to major in just so I wouldn't sound like some antisocial nerd.
Nobody back then thought coding was cool. It was just the thing the weird kids did in the computer lab.
He's looking into pivots now and taking flight lessons.
I know a 2 of senior devs that got laid off from different times and one is approaching nearly a year of unemployment with no offers and another approaching half a year with few offers but elected to continue looking due the offered salary not matching their expectations.
Thousands of applications. Dozens of recruiter calls. Maybe 20 or so processes past that first call. 3-4 that seemed to be going somewhere but went nowhere. One was a ghost after 5 rounds of interviews.
The market isn't just rough, it's downright disrespectful at times.
I am a new father to a 3 month old son. I will be nudging him to be an electrician if he has no obvious career interests. Union, good pay, endless work and lots of opportunities to do your own thing. It’s scary to even consider what the job market will look like in 22 years.
Things are changing, so I can't make any guarantees. But don't get too discouraged. Pay attention to what is in demand like Python, PySpark, and PyTorch. Make sure that the next time it rains soup your son has a bucket.
Fully remote, Full stack .NET in addition to AI/Python/data-science work
I'd side-eye that list as senior .NET dev full stack.
You're asking one person to do frontend/js/css, backend/databases/Redis/MQ, and Python with all that math behind data-science, but i doubt he can understand and review all of this
Let him contribute to something, yes for free, so that potential future coworkers can see 1) who he is, 2) what he can do, 3) how he approaches people.