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Comment by tcdent | Hacker News Reader

> It's been a huge learning curve.

I have been doing this professionally for over twenty years, and I still learn something every day. Over the past couple years, with AI augmentation, I learn even more, move faster and go deeper into the systems that I work on.

A CS degree was never going to provide you with all of the tools that you need for a successful career. It provided you with the basics to get your foot in the door.

AI is not replacing you or an education. AI is raising the bar of what you can comprehend and retain. From someone who is technically minded (and self-taught), all I have ever wanted is to keep learning.

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> AI is not replacing you or an education. AI is raising the bar of what you can comprehend and retain. From someone who is technically minded (and self-taught), all I have ever wanted is to keep learning.

AI is, in my opinion, absolutely murdering the junior dev market. It's now much more efficient to pay for a senior or staff engineer and set them up with a subscription to claude or codex. I think things are going to remain fine for senior+ engineers, but I genuinely don't know what advice I'd give to graduating devs at this time.

I agree with the caveat that a lot of "seniors" (in name only) will be discarded as well. Title inflation finally comes back go bite people.

Being a senior engineer doesn't really have anything to do with how long you've been developing. I've met amazing 21 year old developers who can out code people doing this for 20+ years in their sleep. I would say one of the reasons "seniors" are so much better with AI is because they have CS fundamentals. They know what to ask, they know systems design, they know what ACID is, they understand race conditions...

AI + CS allows you to develop with leverage I've never seen before.

> who can out code people doing this for 20+ years

zero context for the work, so .. javascript?

Yeah. This is absolutely not the case when I worked on control systems, cryptography, or anything else that isn’t a CRUD saas.

https://en.wikipedia.org/wiki/There_are_unknown_unknowns

One of the things that comes with experience is more things moving from your personal unknown unknowns bucket to your personal known knowns and known unknowns buckets.

It's notable that you said "out code" not "out engineer".

If you're desperate to discredit the substance of the comment with pedantic word games, sure. What they are describing sounds like engineering to me.

The substance is hard to see through the conflation of CS and software engineering. Do you actually believe that all there is to software engineering is CS fundamentals?

> I've met amazing 21 year old developers who can out code people doing this for 20+ years in their sleep.

yeah that's only true when you compare the top 10% of the 21-years-olds with the bottom 10% of the 51-years-old.

it's technically true but also bs.

(the "10" in "10%" is a made up number, but the point stands)

> It's now much more efficient to pay for a senior or staff engineer and set them up with a subscription to claude or codex.

this has been happening for years though. just think of cloud computing and things like kubernetes: a single person or a small team can handle the amount of computer that twenty years ago required a full team of sysadmins, a facility (either on premise or datacenter space), huge (upfront!) capital expenditure and ongoing costs (connectivity and power).

same goes for web frameworks (think rails and similar)

Ok, but all of these technologies have bounded impact, and they present new abstractions that need to be learned by engineers.

Coding agents are different in that they are unbounded in the tasks they can do (although reliability is an issue), and you can work with them the same way you work with other engineers (e.g. via natural language).

Also, coding agent capabilities are advancing much faster than people can sit down and learn their limitations. All the tricks we learned for Opus 5 became obsolete in a couple months with Opus 5.5.

Yep, and we have hard data on this: https://arstechnica.com/ai/2026/08/ai-is-hitting-entry-level...

> Stanford researchers find the employment trends they identified for entry-level workers last year are persisting and expanding. Specifically, employment levels for workers ages 22 to 25 in the most “AI-exposed” occupations are now 19 percent below those of their peers in fields less exposed to AI disruption.

Many people in the tech world seem to espouse a great love for "always learning", but the way in which it is said always feels funny to me. Learn about what? When people say this, do they mean that they want to always be learning the next programming language, the next web framework, the next thick-client frontend web framework, the next python packaging CLI tool (pypi, virtualenv, uv ...), the next Linux distro? I'm tired of the churn. Most of these tools are not different enough from each other and don't have different enough use cases to be worth learning, but that's what a job in tech often seems to boil down to. You learn to do a basic set of tasks with one toolset, then once you get proficient, you swap all those tools out for another set of different tools that work completely differently but accomplish the same goal in a way that is not appreciably better or worse than the last set of tools. With AI, this will only get worse, as the cost for making new tools goes down. There seems to be a lot of churn just for the sake of churn.

There's two ways to grow the space of things to learn: breadth and depth.

You're only thinking about new stuff adding "breadth". I think most people would agree with you that new tools rarely have new use cases, so not truly adding "breadth", but that's where we get into "depth".

When looking at long-term learning, there's a lot of "depth" and subtlety in the way the existing tools work. There also comes a point where you have a firm grasp of all implementation details, but are unhappy with the ergonomics of the existing tools to do a particular job. What was an odd use case can become more common with time. This is how new tools and terminologies are born (adding "breadth"), but you have to remember there are always less experienced devs you need to communicate with. Their understanding will be based on these newer tools. Similarly, you spend the rest of your career "catching up" with the writings of the devs more experienced than you.

Why does any of this matter? Why don't we standardize and end this cycle? Well, that would prematurely kill off innovation. AI training may be allowed to become stale, but human knowledge cannot. The goal is always to improve the existing code and the new code.

I'll give you a recent example: I've been offloading sparse experts to the CPU on a dual socket Zen system. These processors have multiple CPU dies, which connect through shared CCDs, which contain the L3 cache and the bus lines into DRAM and PCIe. (Additionally in the dual socket architecture there is a fabric which links the sockets.) And so by characterizing the physical architecture of the CPU and placing jobs accordingly, I can extract the maximum amount of performance from the system I have on hand.

Dell and some of the other hyperscalers have characterized these systems over the years in terms of maximum throughput via both the cache and the DRAM bus (and I have met or exceeded their numbers). But, nobody has actually characterized (and/or documented) the way that L3 cache eviction and retention works. Using a combination of fuzzing, patent research, and performance analysis, I have been able to characterize the operation of the system and tailor my stack accordingly.

Is this churn? Nah, this hardware is many years obsolete for mainstream deployment. Will this benefit me in my profession? Time will tell. Regardless, I had fun because I enjoy learning.

> Many people in the tech world seem to espouse a great love for "always learning", but the way in which it is said always feels funny to me. Learn about what? When people say this, do they mean that they want to always be learning the next programming language, the next web framework, the next thick-client frontend web framework, the next python packaging CLI tool (pypi, virtualenv, uv ...), the next Linux distro

For me it’s been: Learn more about unix through OpenBSD as a daily driver, learn how the usb and pci stack works in the kernel, refresh my knowledge about operating system, learn a simpler processor (avr) and interfacing, learn digital logic and computer organization, reignite my interest in electronics, refresh my knowledge about control systems, learn how to model dynamic systems, quick dive into robotics…

This is just basic curiosity over the last year. When I was younger and had more time, I explored 3D modeling, making games, pen-testing and reverse engineering, learning various software and platforms,…

> A CS degree was never going to provide you with all of the tools that you need for a successful career. It provided you with the basics to get your foot in the door.

Yes and no.

I concur that it was never about the tools, although I've seen plenty of people advocating it had a more "practical" approach, using the same tools as companies use, and in the same way.

On the other hand it's not only about the basics.

In there you can go at depth in aspects that you will have to fight to use, like proper engineering practices, and might only be vital on the later stages of your career. And I feel that those learnings, plus the possibility of acquiring a breadth of knowledge that is hardly possible otherwise, is what gives CS graduates a leg up to other practitioners of the art of software development.

YMMV and a leg up can be easily overtaken, yes.

I wonder how you'd do without your AI augmentation if you find yourself not being able to use it for whatever reason. I wonder what you retained when the AI is not working... or with a very expensive augmentation that wants more cut from your pay...

> I wonder how you'd do without your AI augmentation if you find yourself not being able to use it for whatever reason. I wonder what you retained when the AI is not working... or with a very expensive augmentation that wants more cut from your pay...

Realistically, "AI is not working" is probably not a realistic scenario. He'll just stop working, just like if the network goes down.

The real risk of AI augmentation is to your value as an employee. Maybe the augmentation makes you feel and perform like Iron Man, but if the suit is doing the heavy lifting, and some cheaper guy could wear it and do pretty well, how are you going to keep that fat paycheck? It's not like any of us have tenure.

Someone could use being able to work without AI as a performance metric if they are looking for people to drop though. Because lots of people can AI code, but the best coders are likely highly correlated with being able to code without AI. It will possibly lose that connotation over time, but certainly not within just a few years.

Basically true for all degrees. I studied non-cs engineering before getting into coding and feel it often. At times have felt “should have stuck more with mech e where jobs are more stable and the tech moves slower” but know it’s kind of a fallacy.

> AI is not replacing you or an education

I do learn every day thanks to AI, I agree with that part. But I'm increasingly convinced that AI is likely to replace either me or some of my teammates in the near future.

In the last year, half of my team has been laid off (or left) already and won't be replaced, and we don't see any drop in productivity and the tools are getting better by the day. We need experts to drive all this, but not as many people as before.

Companies that let SW engineers go because of productivity improvements are being stupid. These people will go and build new products, and will compete with your company.

If your company is a big corporation, I don't think they need to worry about the file and rank SWEs. I know that I'm going to compete with Google, Meta or Microsoft. But stupid or not, that's what they're doing at the moment.

Retain? You're full of it. You can't possibly make that argument. There's absolutely no data to support it.

> A CS degree was never going to provide you with all of the tools that you need for a successful career. It provided you with the basics to get your foot in the door.

Aside from teaching me the _basics_ of programming and discrete mathematics, it did not help my career. I, in-fact (due to poor GPA), did not even have a SWE role out of school and had to find my own way here into a successful career. (I struggled even with LeetCode easys coming out of college) I attribute it to creating opportunities for luck (networking) and an appetite for life-long learning (which came well after college).

What it's done for learning velocity is incredible. But it's limiting our abilities to change jobs, at least 95% of us, and that sucks.

If you're highly in demand or sitting on millions of equity, more power to you, you can work on projects outside at home by the pool thanks to AI.

AI has been a godsend to my learning especially in regards with CS and Mathematics. It does not get tired of explaining me not only the 'what' but also 'why' and 'how'. Plus lots of learning rabbit holes.

I was never a good student (not academically inclined at all) and I have learnt more with AI in past 6 months than the engineering degree taught me.

Other than keeping up to date with how to best use AI/harnesses what else would be most important to stay on top of for retaining a software engineering job these days? Also AI seems generic to me. Could I bother you for a more detailed breakdown on the most important topics/skills you would consider necessary for a software engineer to be knowledgeable of?

>I have been doing this professionally for over twenty years, and I still learn something every day. Over the past couple years, with AI augmentation, I learn even more, move faster and go deeper into the systems that I work on.

Too bad a big percentage wont get to do that professionally anymore due to AI.

>AI is not replacing you or an education. AI is raising the bar of what you can comprehend and retain.

No, it also makes the job market hell and cuts down on positions, on top of an already squeezed pre-AI environment.

And that's if one is still OK with the fact that coding work (something many of us enjoyed in itself) turned into "project manager for AIs".

> AI is not replacing you or an education.

AI is the tractor in The Grapes of Wrath, and you’re the one driving it.

I don't think they're complaining about the learning curve.

Didn't say that to refute it. I chose that to make the point that the degree is not the destination.

Iff your goal is using a degree as a stepping stone, which seems to be getting less popular these days.

For some, the degree is the destination and that's more than fine as well. It's a marker that says "others agree I learned x to a certain level, and I had fun doing it". This tends to overlap well with those who just liked university as an extra method of learning rather than going primarily to form part 1(a) of their career or something.

> all I have ever wanted is to keep learning

Good for you! Many people just want to be able to pay their bills.

Your post is entirely too dismissive of the chaos this new technology is introducing.

Harsh opinion: but if you just want to pay the bills this is not for you. Software engineering is a career, not a job.

Far too many people focus on passing an interview and then let legal protections keep their position, all while draining resources that could have been better allocated to someone who is actually passionate. They saw my generation do reasonably well and came for the paycheck. I got into this because there were very few people who could rise to the occasion of problem solving that the industry needed. I did not walk into the room with all of the skills or an idealized salary, I walked into the room with a mentality.

Perhaps the "chaos" being introduced is simply a long overdue market correction.

I'll let the downvotes tally how pervasive this is.

Perhaps you are young and don't have people that depend on you. Perhaps your career is more of an identity for you than it is for others.

That's fine, but don't attempt to gatekeep your profession. It makes you look like an inconsiderate asshole.

While it's a nice-to-have to marry the idea of income and meaning, it's not universal - nor can it be. It's okay to exchange your labor time for money and healthcare, because money and healthcare come first, before "passion."

Passion in tech is for 25 year-olds, recruiters, co-founders, and imbeciles.

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