Career Advice in 2025

>- When you ask someone a question, they vomit your question into co-pilot, paste the result, and presume that they have helped somehow.

We have been dealing with this at my job also. It's really concerning how this is becoming normalized and how often we've had to deal with it. Somehow there are people that have "Engineer" in their title that think this is acceptable workplace behavior and work product for a professional making $XXX,XXX/year.

We had a person join our team recently who doesn't know our stack at all (which is fine, we were happy to teach them). When another engineer reviewed their pull request and asked a question, they pasted the question into Copilot and responded to the pull request with the answer (which was wrong!), even going so far as to say "Copilot thinks it's this: ...". I almost lost it. Your job is to learn, understand, and apply that knowledge, not paste incorrect model responses back and forth between web forms!

It's baffling and enraging. Are people _trying_ to demonstrate to management and their teammates that they're actually worthless? Are our expectations as a profession really this low, that we don't expect people to understand the code that they push?

Nah, we have enough captured business that I doubt it’d make a difference. It’s also not actively terrible for the customer, it just doesn’t bring anything to the table for the use cases we’ve used it for.

Then again, maybe it’s good to give people some experience with it even if there’s no real reason to use it right at this moment.

I think SWE's have a serious blind spot here. I use the (rough) analogy of bowling to help illustrate this.

People need to knock over pins in the bowling lane. SWE's are the pro bowlers who can (usually) throw pretty cleans shots to knock over pins. Now bumpers have been invented (LLMs) and regular folks who only have the faintest idea of how to roll a ball are knocking over pins. To the pro's these bumpers are all manner of bad and useless. To the laymen, they are an absolute revolution.

I can tell you, with a straight face, the my (non-tech) company has already forgone hiring a pro bowler in at least four instances now because of these bumpers. Just last week we skipped on a $1k/mo CAD SaaS because Claude was able to build the needed narrow-scope tooling in 10 minutes.

I'm sure a pro could come in and make that python program 3x as fast and use 60% less memory. But the fact of the matter is that we paid Anthropic $20, and spent 10 minutes to get a working niche manufacturing file interpreter/editor/converter.

LLM's are finally bridging the language barrier between computers and humans. Right now the tech exists to make this even more widespread, it's just a matter of time before someone creates a tech-illiterate IDE that users can paste AI generated code into and functioning programs come out the other side. No need to ever even see a terminal or command line. I wouldn't be surprised if this isn't already in the works.

"Hey Google, create an app that allows me to take a picture of a house plant, and then allows me to verbally make entries into a diary about that plant" Sure thing! Give me 3 minutes and the app will be on your homescreen and shareable .apk in your documents folder! I'll also cancel the $9.99/mo app that does the same thing for you. (ok probably not this part but you get the idea.)

You can be as snarky as you want but the reality is we're years deep into a market cycle that has seen a tremendous amount of capex with very little visible return.

How much more productive do you think claude makes you as compared to Google or Stack Overflow? 15%? 50%? 200? Do you think that's enough to satisfy the market or are we all trading on unrealistic expectations? Do you think shareholders are going to like it that they're losing billions a quarter so Anthropic can run a service that helps you write web dev projects marginally faster? Do you even understand the amount of value that's tied up in these questions having a good answer right now?

Fiber optic and data center build out in the nineties is similar. Overinvestment led to a bust for a period, but the infrastructure was useful and provided the foundation for the next wave of Internet growth. LLMs could be similar.

I agree with the sentiment, but LLMs have already had a lot more adoption than VR and Crypto.

> I believe, we are beyond the point of “bad software written, bad software deployed, business as usual” point long ago when AWS/GCP/Azure became an important requirement in job description.

> A bad piece of software can be decently hidden by burning more money in cloud bills, which gives the inflated sense to the leadership that their products are doing global scale ground breaking.

Doesn't this apply to almost all software out there nowadays?

Bloated enterprise frameworks (lots of reflection and dynamic class loading on the back end, wasteful memory usage; large bundles and very complicated SPA on the front end), sub optimal DB querying, bad architectures, inefficient desktop and mobile apps built on web technologies because of faster iteration speed, things like messing up OS package management where it's not easy to halt updates and they don't integrate well with the rest of the system (e.g. snap packages), messy situation with operating systems where you get things like ads in the start menu or multiple conflicting UI styles within it (Windows), game engines that are hard to use well to the point where people scoff just hearing UE5 and so on.

Essentially just Wirth's law, taken to the maximum of companies and individuals optimizing for shipping quickly and things that catch attention, instead of having good engineering underneath it all: https://en.wikipedia.org/wiki/Wirth%27s_law

Not the end of the world, but definitely a lot of churn and I don't see things improving anytime soon. If anything, I fear that our craft will be cheapened a lot due to prevalence of LLMs and possible over-saturation of the field. I do use them as any other tool when it makes sense to do so... but so does everyone else.

> With AI, I would not be surprised if the quality actually improves and the cost comes down(or stays same). Of course, more bad software will be written by now many aspiring entrepreneurs to realize their dream idea of spotify clone, then sacrificing their life saving on complex cloud bills and ever so profitable rise of revenue of all cloud services citing this as benefit of AI while doing some more layoffs to jack up the stock prices.

At this point we all speculating really. But from logical point of view, LLMs are trained on code written by humans. When more and more code will be written by LLMs instead, models will be trained on content written by other models. It will be very hard to distinguish which code on Github was wrote by human or some model (unless the quality will differ substantially). If this will be the case I would say that quality of code written by them will drop. Or the quality of models will drop. Or code written by model will be still using the pre-LLM patterns, because model-written code will not be part of training data. It may be that LLM written code will be working but hardly comprehensible for human. For now models does not have negative feedback loop that humans have ('oh code does not compile' or 'code does compile but throws an exception' or 'code compile and works but perform poorly').

Anyway, I am sure that there will be impact to the whole industry, but I doubt models will be primary source of source code. Helpful tool for sure but not a drop-in replacement for developers.

Is it statistically possible that one guess will approximate reality?

I can barely think of any real application where they would help. I have a weekend project that's already too much context -- I asked Claude to change some Tailwind styles for me and it just shat up the whole file. and that was a toy!

even if allowed, how is Claude going to help my at work where a single file in a large project, one of many, is tens of thousands of lines long?

guess I'm a dinosaur

I just read this for the first time and was totally underwhelmed. What is the takeaway? "Derisk, Enable, Finish"? This is not insightful or even interesting.

Is he going to update it with how AI will assist in migrations? Or get an LLM to ghostwrite it?

This was excellent and rings very true, thank you

Is this supposed to be an endorsement or an indictment?

oh look another out of touch 'leader' . So sick of these ppl.

His career advice should be how to get your work done while appeasing "leaders" like him at work.

my company now has mandate that 'all coding work must be done by AI' and only manually if its not possible. They bought licenses to all AI coding tools.

Which would've been great if these things actually work. I've never felt more like a stupid cog in my whole career than now.

Genuine question: why do you think LLMs will be able to handle frontend development in a way they won’t be able to handle backend development? I assume you’re talking about real companies, not toy projects or websites for restaurants or whatever.

Anecdotally, I work on backend/cloud and my senior frontend engineers do earn not as much as I do, but close… and their environments are always less stressful (major outages are not caused by frontends usually and when so, reverting to the last stable commit is enough since frontends are stateless; their toolset is narrower than mine, so yeah they need to jump between frontend frameworks but that’s fine… me in the meantime need to jump between backend frameworks, dbs, k8s, distributed system knowledge, unix tooling, OS/TCP/IP, etc)

> a lot of frontend code is trivia that you can just ask the LLM for these days

If you're building CRUD yes. If you're doing anything remotely complex or novel, LLMs fall apart, much like they do for complex backend tasks. There's a lot of cool, highly customized stuff you can build with JS, and LLMs don't do a very good job at general problem solving.

They're still helpful for writing small, specific functions, or providing high level guidance

Certainly. Front-end and UX skills go together. Front-end dev as a beginner → UX → PM later, would provide the same salary as back-end dev -> DevOps / K8s.

I'd personally try to stay away from anything built this way, if I can get a whiff of it (and it's not super hard to find the slop right now). But, even if learn to agree on this for the share of throwaway apps or internal tools that might not need sophistication or care, my point was that the same take applies to the backend side as well and I'd argue that's a more at-risk domain since data is usually in a serializable format to be fed into LLMs and doesn't have the challenges of visual input.

I didn't mean to nullify your experience.

You've undeniably right about how there have been spheres of influence where people and capital come together. Every area of the United States has some kind of forced name of "Silicon *" for a reason.

I just don't think this will be true in the future. Move where you want to, maybe have to work harder to break through, but that was also true in the Valley.

$500k would likely be a staff level salary offer. I think a senior role around $350-400k is probably more likely as a new hire coming in which is definitely great money, but still hard to take a $20k+ monthly mortgage with! Especially since a lot of that salary is variable equity income which can go down (ask me how I know!!)

I’ve worked for BigTech. If you look at how to pass any of the interview processes, it’s basically all about generic coding interviews.

That’s it, those are the only “skills” you have to have to get into the BigTech - pass coding and system design interviews.

And there are thousands of developers looking for jobs - even those who are coming out of well known tech companies.

System design yes, leetcode no.

Leetcode is only a useful problem to ask if the candidate has not encountered that problem before and has not practiced leetcode. Otherwise it is exactly as good a signal as knowing some arbitrary framework or database.

> By contrast, some things I think are worth pivoting into include infrastructure, databases, data engineering, stats, etc

I can't imagine why if LLMs can magically solve web development (which can be complex as hell depending on the app) they wouldn't be able to solve infrastructure, database or data engineering. I somewhat agree that our career moats were hurt (though not as much as you seem to believe in my opnion) but that's happening across the board.

I'm my view, the core of front-end work was always the UI "User Interaction".

Yes some can be solved by designers, but I believe there will still be a big market for designer-programmers.

The programmers that understand design, interaction, pixels and colors will still be of great value.

But if you don't really care about how stuff looks or can't tell a difference between an animation at 25fps vs 50 fps, it is a good sign it is time to try something else.

AI will simply refine your skillset. A backend programmer will have more time to think about architecture, a data engineer/scientist will have more time to think about maths. Or in essence "what am I trying to achieve". And it is up to you to step up to it.

I rather think of this generation with hordes of "coders, writing code" as an anomaly.

Front-End interfaces can be as complex (or more complex) than Back-End/infra/analytics/etc... At the end of the day, it is all about data and the front-end needs to maintain state. If your interface is complex, your state will also be complex.

>infrastructure, databases, data engineering, stats

Why would those areas be less exposed to the "LLM threat"?

> infrastructure, databases, data engineering

I work as a backend dev, without an opportunity to work on these at my current company. How do I learn and showcase these skills effectively. Thanks!

that sounds more like someone needs anger management classes than a problem with technology or LLMs

I see the evolution, atleast until things get drastic, to be where the interviewer will allow LLM use and observe how fast you can deliver the objective while dealing with hallucinations etc.

It’s ordinary corporate dysfunction. The mandates come top-down. People in management don’t think too hard about exceptions. The people making decisions are far-removed from the consequences of their decisions.

In no particular order:

Quality seems completely lost as a goal in any shop. See Demming and Peopleware.

In very general terms: "founder mode" is more often than not toxic because it is taken out of context and used to scapegoat being an asshole. Much like the Steve Jobs worshipping of yesteryear.

Lack of financial oversight by board/investors including founders putting up company money for personal investments including moving money into personal accounts to try and inflate their credit ratings.

Non-VC startup: lack of preparing for a future where income is reduced for a period of time and keeping some amount of business savings around

VC startup: lack of appropriate fund handling given the assumption that the money machine will always be there

Hurting all option holders by removing the ability to exercise early or ruining their exit with poor financial stewardship including down rounds or bridge rounds

Always time to fix it later vs taking the time to plan and execute correctly in the first place. This is a relative scale of time to market and risk to opportunity cost but with the exception of large events like tradeshows or such a few more weeks to get it right is better than hobbling along with literally millions of dollars of technical debt if success is found.

And re:tradeshows - demoware is the name of the game and sales needs to be onboard with eng that demoware is demoware and what to sell ahead of the product

Lack of clear execution plan as product market fit is found and everyone has been acting in "throw shit on the wall to see what sticks" mode

General lack of discipline to keep things orderly as work is done which is a failure to understand systems and second / third order effects. Speed is a lagging indicator not a leading one. Everyone wants more, faster but then fails to slow down to put process in place to facilitate moving faster.

Not growing teams appropriately. Lots of lack of empathy, poor hiring practices, abysmal firing practices. Lots of tolerance of "smart assholes" in small teams when leadership only cares about P/L and so the toxicity grows.