>The current market doesn’t value those skills particularly highly, but instead prioritizes a different set of skills: working in the details, pushing pace, and navigating the technology transition to foundational models / LLMs.
depends on the assumption that technology must "transition" to "foundational models / LLMs". The author doesn't seem to interrogate this assumption. In fact, most of the career malaise I've seen in my work is based on the assumption that, for one reason or another, technologists "must transition" to this new world of LLMs. I wish people would start by interrogating this bizarre backwards assumption (ie., - damn the end product! Damn the users! It must contain AI!) before framing career discussions around it.
However,
>decision-makers can remain irrational longer than you can remain solvent
It’s important to understand how AI will affect your field and recalibrate your position or contribution accordingly
It is a big enough change for this to be a valid question for anyone in the world today
Leaving what you’re doing and going into “AI” will likely set you up for a crypto level disaster
Vibe coding is a thing but vibe business building or job hunting isn’t! So beware of hype and know that in the end money is made by serving people and it will be equally hard with vibe coding too because the bar is higher
AI will create newer opportunities for sure but follow the opportunity, not the AI is what the sentiment here is I guess
>It’s important to understand how AI will affect your field and recalibrate your position or contribution accordingly
In the case of my industry (middling cybersecurity) we're seeing the following "advances"
- When you ask someone a question, they vomit your question into co-pilot, paste the result, and presume that they have helped somehow.
- All meetings now have not-useful meeting notes and no one reads these.
- People are considering implementing security co-pilot, which will introduce useful advances such as spending much more time building promptbooks so co-pilot can understand our logs.
- A lot more people think they're engineers, and vomit out scripts which do things the "authors" do not anticipate.
>- 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?
Our senior leaders have also been completely captured by this crap. Recently our CTO (public company in the US you've heard of) announced in chat that engineers with an aversion to relying on LLMs have an attitude problem that is incompatible with our company direction. I was blown away.
Only in the short term. In the medium to long term, false assumptions will kill a company. As an employee, you would be better off recognizing it before the crunch hits.
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.
Exactly my thoughts reading this article.
Luckily if next few years we will have thousands of projects written using 'ai' there will be need for someone to debug and fix all of that broken software.
Or maybe not, maybe it will be cheaper to just slap another ten k8s pods to mitigate poor performance...
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.
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.
The real revelations will come(it always does, nature and economy works in cycles), when excessive layoff caused damage will come due and now everyone will scramble to rehire people in few years. Unlike the Ford innovation of replacing horse carts, software is more prevalent in our every aspects of life, same as doctors and lawyers and civil service, hence we need to honestly play the game until the wave turns and then cash in by making in 200x killing just like the businesses are cashing in on right now.
> 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.
> 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.
No one knows what the "current market" thing really is, people are making wild guesses looking at the hands of other people who also make wild guesses.
I do think some transitions are inevitable and not because AI must be used, but because once enough companies figure out where it genuinely improves efficiency, the competitive pressure to follow suit becomes real
The same holds true for software developers imo. If you can't figure out how to use LLMs to improve efficiency, your likely a dinosaur of the past soon (unless you work on somethink __very__ specific where LLMs dont help much).
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?
The best use I've gotten out of LLMs is as an autocomplete. I use Cursor at work, and it's pretty good at consistently calculating the next 10-20 characters I want to type out. Anything longer, save for some situations where the changes I'm making are super repetitive, the quality dives off a cliff.
I've yet to coax out good/working code of significant complexity from these models without putting an amount of effort into prompting that would be greater than just working it through myself without any LLM assistance.
The use I do get out of Cursor can save a lot of time for me, so I do think it's a productivity boost as is.
Think about what you're asking when you tell these people to interrogate the assumption that LLM based AIs are going to be the dominant technology going forward. Hundreds of billions, the growth of the technology industry, the entire US stock market, and the global economy has been wagered on this technology. Imagine the turmoil when those in power realize the reality of what they're betting the farm on.
The next time I am angrily typing to claude 3.7 in all caps because he overengineered a bunch of code I didn't even ask him to write in the first place, I'll be sure to let him know his continued failures are risking the entire world economy.
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're just describing programming without realizing that having a stochastic and imprecise programming language is a leaky abstraction.
The problem isn't that a "pro bowler" could come in and do something irrelevant for more money. Professional programmers understand that you shouldn't prematurely optimize things like memory or performance in contexts where that doesn't matter. You're ignoring the most important metric which is correctness. When we write a program, we make it correct then we can optimize it if that's actually important.
What's going to happen when you have your non-expert write a program using these tools and it inevitably gets something wrong? Are you prepared to build business process on top of a program whose author can't tell you how it works which might contain bugs? Do you even realize that this is just a recipe for producing mountains and mountains of technical debt?
You seem to believe this is going to put programmers out of a job but you're just explaining why they'll need even more of us in the future when these piles of garbage inevitably cost the company money.
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?
You don't stop the car but speed up faster toward the wall. That has been the strategy in the last decade or so. In other words, you invent a new AI-BLOCK-WEB-4.X thing and move the bubble one stage further.
I think bubbles form and pop all the time. I would add (in the US) home price bubble, biotech bubble (of mid 2010s), cybersecurity bubble and more.
Pops are less noticeable when a lot of money is sloshing around so deflating one bubble immediately start inflating something else. Worker bees can switch to the next thing in the same "building next great thing, work is plentiful, money no object" environment.
So the bubbliness, IMO, is a function of the macroeconomic state, specifically the amount of money in the economy. Things get sober (and very ugly) when the money printing cycle ends, as it eventually must to avoid sliding into hyperinflation. My 2c.
I think 2008 set the stage that the government will bail out reckless economic activity for the top at the expense of the tax payer. Actions no longer have consequences and you better be big enough to hold the economy hostage to your scheme.
Seeing more and more of this now, where even in "these parts" anything short of "AGI IS HERE" even a few months ago would have you labelled as "Luddite" "skeptic" and "left behind".
When is the general public going to start asking questions? It's really not a game--people's 401ks have been propped up by the "Magnificent Seven" (disproportionately by one company) for some time now.
What happens "if" these proclamations fail to manifest? How is this all supposed to work out?
I'm entirely in agreement with you, I just have a dark sense of humor.
I do actually use claude quite a bit recently and I suspect (completely anecdotal, so take it with a boatload of salt) it speeds up my development time by about 25% on average. But its a very lumpy sort of speed up that is sometimes a slow down depending upon how wacky the LLM's answers are. And I find claude 3.7 to be worse than claude 3.5 in many ways which makes me confused about how hyped up it is and further disillusioned about the "common sense" idea people around these parts have that the technology is just going to keep improving significantly year over year.
I use it entirely through the web interface and using the lowest price basic monthly subscription fee. I am probably a cost center for Anthropic rather than a profit center, but I don't really see that as my problem to worry about. I'll enjoy the thing while it lasts and then not cry too hard when the house of cards collapses.
I don't think companies like Meta, Alphabet or even Amazon are extremely overvalued. Their growth in revenues and earnings is still very solid, so even if A.I is a no show their earnings should continue to do fine (I'd even add Microsoft to the list).
Sure stock price might slow down significanty but it can easily add 10% yearly for the forseeable future. Its much less than what we're used to, but its solid growth that has not much to do with A.I.
And I totally agree people should forget about the s&p 500 returns we've seen in the last 15 years going forward, it would probably be less (though I have no crystal ball, but regression to the mean seems likely).
Actually, all stocks are dead and tech heavy Nasdaq has entered the correction zone this year. It will be a real while before the stocks return to their pre-correction value. The AI hype drivers have lost massive value, hence the desperation will get immense, expect the “AI ready to replace expensive SWE/Lawyer/Entertainers/Creatives” narrative to start any moment now! Of course everything is smoke&mirrors so those will be charged at such premium that the naysayers will not be able to afford it and irrational leaders will buy it and cite immense success to maximise their C level bonuses and will early retire before the tower comes falling down.
Correction is one thing but saying "stocks are dead" is hyperbole.
Just my poor ass startup is paying Google Cloud around 1 million USD a year to have our operations going. We're quite a cheap company but we're totally dependent on them.
And Cloud is a minor part of Google's earnings they have Youtube, Search, Android etc etc. This isn't a bubble, these are real earnings that are probably not going away any time soon. Does it mean Google is bullet proof? No. They may experience a big correction at some point but that has always been the case for all companies.
I can make the same case for Meta, Microsoft, to lesser extent Amazon. I'll leave Tesla aside it's indeed too richly valued.
I have no analogy for this except the railroads of the Gilded Age. Did railroads become a pretty big deal? Yeah. They were also a giant vortex that slurped up endless investment, far more than the real demand could possibly justify. And it ends, well, we know how it ends.
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.
We've become so accustomed to the rip-roaring growth that came from widespread Internet adoption and now that it has piped down, we're desperate to find the next big boom. VR, crypto, blockchain, generative AI. And each time, like degenerate gamblers, we're feeling it, this must be it, the next Big 'Un, the bet that redeems all the bets that went wrong, bigger, riskier, bigger, riskier.
But it just won't be, nothing in our lifetime will ever come close to what the Internet boom was. The window for becoming a Jeff Bezos or Mark Zuckerberg as easily as they did is closed now, and you just need to live with it. The title of this chapter till the end of our days will remain "After the Internet Boom" and it will chronicle this pathetic desperation.
You're right of course, but nobody ever gave me a free VR headset or a few thousand dollars of Monero. OpenAI and Google will both give you, for free, access to an LLM whenever you want. I can do a Google search and help with LLM adoption right now, it will be at the top of the page.
That's an overblown claim. AI companies failing won't mean technology doesn't advance nor that companies betting against/independently from AI would recind.
This guy probly doesn't doesn't do any actual work just reads ppl like Mario Damadai who are out there claiming 90% of coding will be done by llms in next 3-6 months.
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.
> I’m a software engineering leader and writer, currently serving as Carta’s CTO. I’ve worked at Calm, Stripe, Uber, Digg, a few other places, and cofounded a defunct iOS gaming startup
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.
> Steer away from skills like web development that are clearly getting eaten by LLMs
On the contrary, here in my corner of EU nearly 60% of new jobs are frontend or full stack.
Anything else left is mostly SAP consultant or DevOps.
I think, the whole WebDev is dead end is just false lies to dissuade new entrants. Literally most successful business with a digital solution is web stuff with some automation that would otherwise be ms excel sheets shared via email.
Also this whole panic over LLM is overblown, I know of some brilliant experienced people in other professions like Electronics, Mechatronics, Aerospace, Material Science and literally all of them are finding the job market “very difficult at the moment”. It is the bad global mood in general used deceptively by opportunists to spread false fears of their LLM/AI.
At the end of the day, an insurance seller has hundreds of concerning reasons to convince you why everything is dangerous around you and you really need their product. Now apply that to AI sellers.
Web element feel similar to PHP or wordpress development in 2010.
There are millions of small businesses that demand wordpress websites, but the barrier to entry to support and build systems got very low very quickly. Professional developers were competing with high school students and offshore devs for work.
As a backend Developer, I can now build websites easily with Claude and react. I think web development, especially front end, will be like knowing HTML and CSS in 2015. Like everyone should know it, and thus not even worth putting on your resume.
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.
Well, "frontend development" means a million different things, but LLMs are very good at flexbox and grid (and I'm not).
With backend I find they're good at the really high level (give me the options for architecture and their pros and cons) and doing something small and precise (gimme a function `List (Maybe a) -> List a`). The stuff in-between I have to handle myself.
Developing, managing, and operating distributed systems infrastructure has way less training data available than webdev. And it doesn’t translate in to pithy interpreted language one-liners.
There's another factor here I forgot to mention - web development, as a specialization, tends to be paid less and has a lower career ceiling in many companies than backend and infra engineering. This is a personal observation on my part but I've seen many other people remark on this. True full stack engineering, I think, is reasonably safe from the robots at the moment.
If someone likes building products, I'd basically recommend that they not go 100% full-bore on frontend engineering, definitely go for "full-stack", and accept that a lot of frontend code is trivia that you can just ask the LLM for these days. I would also recommend that they develop solid product management and UX skills.
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.
> Steer away from skills like web development that are clearly getting eaten by LLMs.
You had it going well there but then had to ruin it with a take like that.
If you’re talking about your trivial, github-filled example scenarios of frontend, sure. But then we could say the same for all other roles, including backend logic that’s regurgitated all the time.
Like with everything else, the non-trivial bits need work and skills.
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.
Good advice in general. I would add - try to pick a skill which gives you a deep understanding in something fundamental which will always be relevant, rather than a particular shiny tech.
I would love the bay area, but unfortunately it is extremely inaccessible for me and others once you have a family. Trying to find a place to live in a good school district seems like it takes minimum $2M for a house. Renting is less long term secure when trying to maintain consistency for kids. That's not even get into earthquakes and wildfires!
If you’re usual child-raising age then you probably have 6-10 years of experience, and there should be lots of jobs that pay $500k in the Bay Area. Buying a $2m house on that salary is pretty doable.
$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!!)
> Look for work in major U.S. tech hubs like the Bay Area. Pay is better and network effects are strong, so your next job will be easier to get.
Jobs and the network effects happen all across the country. As you get older and maybe don't want the grind, or have a family, or just want a better work/life balance, this will become apparent.
Basically, always have at least two people who will support you for your next job.
There are plenty of tech hubs besides the Bay Area, that's for sure. But I can tell you that when I moved from a small company in a small economy to a moderately-well known startup in the Bay, the rate at which recruiters contacted me jumped from maybe a few times a year to multiple times per week. And after a few years, many of my coworkers started their own companies and invited me to join them.
By contrast, I have very talented friends who did not make the jump to work at a tech hub, and they don't have the same kind of network or opportunities.
With that said, I very much agree with you about wanting work life balance, making sure there are people who will support you in your next job, etc. However, I think that this is much easier to optimize for when you do have an established career and an extensive network already.
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.
I'm mostly thinking of frontend dev work, but also some types of light backend work that you might see in a CRUD app. And listen, I've done that work, I've done a lot of it, and I saw that it's mostly a career dead-end, becoming more and more automated/copiloted away. It's not a career moat to be a mid-level React developer. By contrast, some things I think are worth pivoting into include infrastructure, databases, data engineering, stats, etc, and I've spent the last few years pivoting into those areas.
An interesting counter-point is that if you have great product and design skills, this is a great time to learn frontend development, because it's more accessible than ever and can supercharge your existing skills. But the days of being a pure frontend coder are probably fading.
> 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.
Probably not, but if you are the UI developer that gets annoyed by it every time you open the application, it means you are probably in the right place.
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.
Theoretically - yes, practically, on average, any of the things you’ve listed is far, far, far more complex than your average frontend that is basically glue between “real” logic and user.
If you are doing CRUD simple data apps, I don’t get why your backend will be complicated. Sure the industry has complicated stuff (aws & friends) for complexity sake but that doesn’t mean you have to go down that rabbit hole.
Front-End is complex which is why we have 36362 libraries to solve the same problem and still move user interfaces sucks.
I'm not a fan of the "front vs back" dichotomy. Chrome is just another box as far as my responsibilities and goals are concerned, but it always feels like there's a mental handoff switching to this one context.
To be brutally honest, LLMs aren't very good at solving novel problems, they aren't very good at integrating business context, and they make many small mistakes. That's why they are a good fit for frontend development! Frontend features are
1. often quite deterministic (well-defined specs and mockups from product managers) and
2. repetitive (95% of all frontend features have already been built many times in the training set) and
3. small mistakes often don't really matter much, the page will just be slightly degraded. Speed of development usually beats perfection.
So you can often say "hey, Claude, here is the exact feature I want, this has been done many times before, can you update the codebase to mostly do that?" And Claude can do that in a lot of cases now, and will probably continue to get better at it over time.
By contrast, infrastructure work tends to be more complex and higher stakes (a small mistake can cost you a lot of money or downtime). Also you usually aren't optimizing as much for a large number of small features. So there's just not as much value, and much more danger, in turning an LLM agent loose on this stuff.
This is an extremely dumb take, I’ve worked on both areas before and I could say that infra work is mostly repeated and needlessly complex config sprayed into git. LLMs have seen enough of that to make head or tails of it by the way you’re characterizing frontend dev.
The important part is NOT auto-generating repetitive configs; it's about the effort and skill required to verify that output. On the frontend, we have an easy feedback loop to preview the effects before deploying. That also helps us produce lots of training data for frontend LLM output.
On the backend, there is substantial risk with infra changes - you could drop the database, block production traffic, etc. etc. You can't just vibe code the infra configs and hope for the best, you need someone who understands the output well enough that they could have written it themselves. That means that LLMs are at best a modest productivity boost for infra engineers right now. It's also much harder to simulate the output of LLM infra changes compared to running a browser, so it's more expensive to get training data to boost the next version of the model's performance.
> On the frontend, we have an easy feedback loop to preview the effects before deploying
There are many ways to introduce subtle bugs into your system, I don't think the risk is that low in the front end. I'd agree with your take if LLMs were reliable, but they're not - especially on big codebases. A broken form is downtime just like a broken API endpoint, the damage is the same.
I understand where you're coming from, there's the sense that front end work is "less important" than backend work in some places, but honestly every company that cares about its product shouldn't really adopt this philosophy.
Product work is super important - it's something I care about a lot. I think it's just different from infra work, like comparing woodworking tools to a dump truck. You're going to do a lot of fine-grained feature work with your woodworking tools, and if you scuff something up or break a piece, that's not too disastrous and can be fixed. But the dump truck can, like, destroy your warehouse, throw your inventory on to the highway, or explode. Even if there's a similar error rate in the auto-woodworking-tools to the self-driving-dump-truck, the dump truck's mistakes are too risky.
We should probably also distinguish overall quality from error rate. If the woodworking tools are producing crappy stuff, then there's no reason to use them at all. But if they produce mostly nice stuff, fast, but occasionally break a piece, they might be really useful.
You once again seem to be thinking of trivial examples of frontend to say there is an “easy” way to verify the loops. I really wish it were that simple for anything reasonably complex I encountered that were customer-facing — often filled with plugins/apps/micro-frontends/libraries owned by other teams etc or clients. I also think if it were that simple, companies wouldn’t be popping up every now and then trying to solve challenges in this space w.r.t validating flows, interactions/animations are smooth and ensuring some weird stuff isn’t happening across all the browsers the customers of your product are using. But there are a lot of them gunning for a piece of the pie, more since the LLM frenzy. And this is largely just web stuff I’m talking about, I’m sure similar complexity exists for mobile apps if we are to count that also into the equation.
Re: backend risks, I once again think you try to rub this off by equating all of backend development is done the way you’re talking about — to perfection, with backups, tests for those backups and all that. I’m sorry to burst your bubble here but if we’re thinking about the same kind of scrappy development you’re talking for frontend, the backend side is about as bad or worse (given how critical you think all of this is, which I agree with). I doubt the backend engineers are sitting there, carefully reading manuals and crafting code instead of vibecoding.
> You can't just vibe code the infra configs and hope for the best, you need someone who understands the output well enough that they could have written it themselves.
It’s not vibecoding but I’ve seen engineers in this role google, copy-paste and modify configs and scripts that run multi-million dollar workflows which somehow worked at the end of the day. I bet LLMs can do a much better job than that, don’t you?
> It's also much harder to simulate the output of LLM infra changes compared to running a browser, so it's more expensive to get training data to boost the next version of the model's performance.
I disagree. It’s much, much harder to go and debug why your customer on X OS, Y Browser and Z GPU (to simplify) is seeing glitches when others are not. Sometimes that leads you to browser bugs. I am yet to see any AI-loop based tools come close to tackling the kind of real-life, serious prod-driven challenges. If you think running a browser is all it takes, I can say something dumb like “running a container is all it takes” but see how stupid that sounds? :)
And it’s also silly to think UI mistakes don’t have real-world implications. There are countless examples for this already — broken purchase flows resulting in losses, frustrated customers unable to complete their work and leaving apps, incorrect request flows causing small/big DDoS, sometimes even stuff that might lead to lawsuits.
——
I feel you have a bleak view of frontend as a whole or you never worked with teams who do a good job or you have been conned by the chest-thumpers who have been saying for years and YEARS that frontend development is pointless, not real CS and have zero value. Oh, and that JavaScript is not a serious language — classic!
If I saw backend/infra engineering the same way based on the # of devs and teams I had to hand-hold and # of their mistakes I had to help fix while working as a front-end engineer, I’d be shitting on them too. But I know better to see that there’s a right way to do it.
> I feel you have a bleak view of frontend as a whole
First of all, let me say, I love frontend. I spent probably a decade building products and tools almost entirely on the frontend. I enjoy interfaces and workflows and visualizations. I don't want you to feel like I'm attacking frontend or frontend developers.
> often filled with plugins/apps/micro-frontends/libraries
> It’s much, much harder to go and debug why your customer on X OS, Y Browser and Z GPU
Second of all, it sounds like you're doing some pretty complicated stuff! And that you care a lot about how your work affects people. That's awesome. I don't think LLMs are particularly close to automating web development done at this level.
Here's where I'm coming from: A shockingly large amount of interesting frontend work can now be done, reasonably well, by an LLM. Sure, it's no staff frontend engineer, but you now have people who can't code at all who can dream up little apps and have the LLM actually just build it for them, something actually useful. That is absolutely incredible to me.
I also see the momentum here - if there is any area of software engineering that the model companies are trying to automate, it is frontend engineering. Will they get all the way there? Eh... probably not. But it's going to keep getting better. I think this will make the best frontend engineers much faster and more productive, and will probably make the field more competitive as a result. People will need to learn entire new workflows to stay at the top of the field, and there's no guarantee on how good AI will get. Candidly, I just don't see the same momentum for AI in the database/infra space, and speaking personally, I thought it was the right move to shift in that direction.
> I enjoy interfaces and workflows and visualizations. I don't want you to feel like I'm attacking frontend or frontend developers.
I hope you mean that but it's hard to see it that way based on your original comment and responses. The trope of "frontend is not a serious job" has been infuriatingly going on for a long time before LLMs took the center stage and that seeps out of the things you've said so far.
But, I'm glad if you mean what you said above.
> Here's where I'm coming from: A shockingly large amount of interesting frontend work can now be done, reasonably well, by an LLM. Sure, it's no staff frontend engineer, but you now have people who can't code at all who can dream up little apps and have the LLM actually just build it for them, something actually useful. That is absolutely incredible to me.
And this is where I'm coming from, based on your original reductive narrative on LLMs overtaking frontend and that the field is somehow at risk — if you feel the same way, you can apply these _exact_ arguments to a _shockingly_ large portion of backend too. I could say most are just glorified spreadsheets. Moreover, a lot of startups just use one of the "serverless" platforms and won't think twice about database, devops, security, authn/authz until they hit an escape velocity.
But I personally think meaningful engineering solving real-world problems at scale that is meant to be an enjoyable experience for the user should be well thought through, end-to-end, regardless of the smaller scopes within.
> Candidly, I just don't see the same momentum for AI in the database/infra space, and speaking personally, I thought it was the right move to shift in that direction.
Partly, I think you are probably forgetting that a lot of these startups promising all of this also promise the backend stuff, even if you might disagree with the choice of tech stack (usually React/Next w/ Supabase/Planetscale/Firebase) and the deployment environment (usually something like Vercel). And the reason why the frontend part is front and center is because... well... that's what the users ultimately interact with. They don't give two shits about the stack (front & back) as long as the product works and works well. But it'd be naive to think this didn't involve all the automated code being spit out on the backend side as well.
And let's forget AI for a moment, by this line of thinking, a large portion of the backend engineering you talk about have been available in simplified forms via serverless offerings or via low-code offerings. Same for databases, including branching and claims of seamless migrations and backup. So, maybe you should have started panicking way before modern LLMs hit the scene? :)
But you probably won't because like me, you realize it's not that simple and it's not always practical. Same reason why I am not using Framer/v0/<insert fancy new tool here> to build a non-trivial front-end app with growing complexity.
I'm a cautious optimist in this space. I do think the tech we got so far is cool and groundbreaking and I use them extensively for noodling. But at the end of the day right now, they're still tools. We are seeing the AI leaders shifting goalposts every day, complain about lack of data etc. and I honestly believe we are many more breakthroughs away from getting to the dream world you're thinking of, especially when broadly generalizing things.
> Aside: I'm also pretty sure you can find plenty of "AI" companies promising automated DevOps/Backend/Database etc. just within https://www.ycombinator.com/companies (try keyword searches).
> The trope of "frontend is not a serious job" has been infuriatingly going on for a long time before LLMs took the center stage and that seeps out of the things you've said so far.
Eh, sorry I came across that way. To me, seeing a complex system visualized, making it interactive, is just so beautiful. That's a big part of why I got into frontend in the first place. I wouldn't take anyone seriously who doesn't think frontend is a serious job.
I also suspect that you are doing more complex, and finely judged frontend work than I did - I took a peek at your public profile ;). So it's not surprising that we have different impressions. If someone is building a frontend that needs to work seamlessly for billions of people across many devices, that sounds incredibly challenging and frankly I've never even tried to do that so I can't even comment on it.
But, I would say that a lot of the frontend work that I find interesting can now be automated with LLMs. Historically, I've tended to build internal tools that usually had a fixed runtime environment and small number of users. So I'm not as worried about the fine points of the web, but about creating a lot of features and interactivity in a particular, easily tested environment. I would wager that the average frontend developer is doing work somewhere in between the two of us.
> you can apply these _exact_ arguments to a _shockingly_ large portion of backend too
Hmm, I think we just disagree here. I think a lot of my view comes down to how frontend ultimately needs to collapse into something that can be visualized and interacted with, and this helps force the state to evolve in sane ways. On the other hand, I think backends quickly grow from a spreadsheet to insane, highly-dimensional, highly-coupled nightmares that no one can really visualize anymore, first at the logic level and later at the architecture and schema levels.
Ultimately LLMs are helpful when they can sort of grok the overall structure and plan of your code and add stuff helpfully to it. I think that LLMs have more public examples of frontend codebases and that helps them follow the overall structure a bit better. In my experience, LLMs are doing a bit better in trying to add small features to large frontend codebases than to large backend codebases, probably for this reason.
Finally, you can often define what changes are wanted on the frontend fairly precisely. A series of mockups plus descriptions of the interactions carries a lot of detail. On the other hand, backend changes often interact implicitly with unstated business context that you can't get solely from the backend code itself (this become particularly tough when you try text-2-SQL, for example.) So I think many backend and architectural changes have inherently vague specifications that need to lean heavily on context that's not captured in the ticket.
None of this is meant to undermine the seriousness or difficulty of frontend as a profession. But it is still my opinion that, on average, LLMs have a better chance of doing useful things on the frontend than the backend.
I thought about this a bit more, and I think the boundary between front end and backend can be a bit artificial. Theoretically, one could do highly complex state management and data flows on the front end, even run your own database, etc. Not to mention complex dependency trees. All of this can and does happen, but in my mind this starts to leak into what I’d consider backend work anyway, just coincidentally happening in the browser. And I don’t think LLMs are particularly good at automating any of that.
But I think there is a huge chunk of work, which most people think of as front end, which is displaying pre computed data according to a particular pattern, and providing hooks into the backend for additional interactivity. I think that this piece can be largely done by LLMs now.
LLMs are not the threat right now. Mismanagement of the United States and a 2008 style recession (but without the TOGA power of the SaaS/cloud boom. AI is swimming naked financially) are the biggest threat for your career and employment in 2025.
Less data to train on? Github et all are awash in front end code but the stuff most enterprises run on is locked away and not accessible to the AI companies.
Realistically, you need to bootstrap your experience in these areas. Pick an area to focus on and put your own time into learning it. My rule of thumb is that you need about 100 hours of personal study to get to "smart intern" level in a particular tech skill, given that you're already a professional developer. I typically bootstrap a skill by picking a textbook to work through and combining it with personal projects and adjacent reading as it comes up. Usually after ~100 hours or so you will be able to arrange an internal transfer to work on that stuff in your day job.
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.
On avoiding web dev: I get the concern, but I wouldn't write it off completely. LLMs are changing the game, but they're not replacing deep expertise in architecture, scalability, or understanding real-world business constraints
I don't think they meant architecture, scalability, or understanding real-world business constraints
I think they meant literally web developers, or, aka, frontend folks doing html and css.
I've worked on backend systems that run web sites and apis, for over a decade, and I've never once referred to myself as a web dev. That title has always been frontend specific imo
Good advice -> but is an error or blindness
> * Steer away from skills like web development that are clearly getting eaten by LLMs.
funny enough all the hyped YC / Bay area startups don't make as much as your typical CRUD webapp.
Devs we tend to be attracted to tech. but what makes good tech doesn't mean it's a good business. That's why your typical bay area startup depends on vc funding & will likely spend 10 years without being cash flow positive.
Amazingly enough, I and millions of other developers have managed to find jobs outside of the Bay Area.
Personally, I’ve been finding jobs quite easily 10x since 1996 - the last 2 in 2023 and last year.
> Look at the requirements for your dream job and figure out what you need to learn to qualify.
Those jobs in the Bay Area mostly require you to “grind leetCode” and system design. They really don’t require you to know the latest frameworks, databases, Kubernetes, etc
Hey, as I said in another thread, I did not start out working in the Bay, and ended up here somewhat by accident. It shocked me how much easier it was to find good jobs here, and I'll stand by that. With that said, of course I say this with no judgment to anyone not in the Bay or other tech hubs, it's friendly advice from personal experience.
> Those jobs in the Bay Area mostly require you to “grind leetCode” and system design. They really don’t require you to know the latest frameworks, databases, Kubernetes, etc
Hmm, it sounds like you have a negative opinion of Bay Area jobs in general. I'm asking people to first figure out what work sounds interesting to them, and then learn the relevant skills. If you have the skills, the Bay Area probably has the right job, too. Of course these jobs also exist elsewhere, I'm not sure why I'm triggering this reaction...
I agree, that is how many big tech interviews look. I've done 'em too. If one's dream job is a generic, mid-level role at BigTech, then the path is clear - get very good at Leetcode and system design, and flag down a recruiter.
My dream jobs tend to be more eclectic, and not necessarily at giant companies. I'm more interested in getting really skilled at a particular type of technology and being hired to work on that. And this kind of targeted recruitment still exists at big companies, too.
But also Leetcode doesn't scare me too much, so maybe I'm dismissing it too easily. I've done a lot of those problems over the years, and I'm FAR from great at them but it's never been the blocker to a particular role in practice.
Most people’s “dreams” have nothing to do with working. Their dream is to have a combination of shit ton of money appear in their bank accounts every pay period and stock to appear in their brokerage account every vesting period.
True there are some who want to win the lottery and accept less than their market rate in exchange for “equity” in a non public company that will statistically be worthless.
Coding interviews are definitely is still the part of the process you have to pass unless you are a very well known big deal in the industry.
BigTech companies want versatile developers who can move around as necessary.
There are no “inside tracks” for 99% of positions aside from probably acquihires.
You go through the grind regardless. Open source contributions really don’t mean that much.
It seems like you're really focused on the interview process for a small number of very large tech companies. My experience doesn't match yours - I have been recruited to a specific BigTech team based on my background, and the interviews were more focused on specific skills than leetcode. But it seems like most BigTech interviews probably are coding/system design.
With that said, I have tended to interview more at scaleups/late-stage startups in recent years, and it's been very rare to see a truly leetcode-heavy interview process. These are positions that pay comparably to big tech, although the equity is generally more risky. But I've also been able to cash out some startup equity, so maybe my experience is not representative again...
> Most people’s “dreams” have nothing to do with working
This line always seems like a cop-out to me. Almost all of us have to work, and it takes a huge amount of our time. And for many of us in the tech industry, we have been intrinsically interested in this tech since we were kids, and have specific stuff we'd prefer to work on. Can we just accept that certain work is going to be more interesting for certain people, and that they might want to steer their careers in that direction, especially if it pays better?
By pay similar to BigTech do you mean the cash you get paid at a startup/scale up is similar to cash + liquid public RSUs?
Equity in private companies especially in today’s climate is statistically meaningless.
And if you look at the companies that pay the most + have the largest number of opportunities, they are the “small number” of BigTech companies
And back to the Bay Area argument. Most of the major public tech companies have offices all over the US that pay the same with a much lower cost of living.
Stripe has given their employees a chance to sell their equity via a tender offer. SpaceX I’m not sure
There has to be a market of people who actually want to buy the equity and the company has to allow it. In the case of “scale up” early startups - the type the original commenter said he works for - usually either there is no one that wants to buy the equity or it’s a steep discount
Let me try to state your overall point, as I understand it:
"The primary goal of a tech career is generally to get a high-paying, low-risk job. Many of those jobs are in Big Tech. You should optimize for getting one of those jobs (but ideally not in the Bay Area, because it has a high cost of living.) To do that, you should primarily focus on grinding Leetcode and system design, because those are what Big Tech will evaluate you on. There are no loopholes worth speaking of, and you will be competing with many other engineers for the same positions."
Feel free to correct me if I'm not getting it right. I have no particular issue with someone whose career strategy is the one above. It's actually important information for someone to learn, especially if they come from a small town, like I did, where Google et al. never darken your door.
However, that approach is not a common one in my community. Instead, I see people who exited startups as founders or early employees, people who had particular skills directly recruited by BigTech and others, people who worked at private companies with regular internal liquidity events. People who worked on stuff, by and large, that was interesting to them. People who have plenty of job opportunities, and don't feel like they're one of a thousand people competing for each position. By and large, I prefer this approach.
Again, we can look at statistics instead of suffering from survivorship bias. The vast majority of employees in startups will not see outsized gains from exits especially in todays climate where the IPO market is dead and acquisitions are going for much less.
> Most people’s “dreams” have nothing to do with working. Their dream is to have a combination of shit ton of money appear in their bank accounts every pay period and stock to appear in their brokerage account every vesting period.
Yes.
It took me two years to have the illusion shatter and realize that I simply do not want to work. Imagine spending 8 hours a day plus commute sitting on your ass and writing corporate emails, and calling that self-realization. Or imagine grinding hard for a pay 50% higher than the security guard who's just playing video games, so that you feel like you're above the minimum-wage workers, but in reality you can't escape the poverty either.
I consider myself incredibly lucky to be working in a company where people who give a fuck are a minority, so there's very little pressure to actually do anything, while the pay is decent. I use some of my extra time to do some physical and mental exercise, so that my body doesn't collapse when I finally get to retire, and the rest is just spent watching porn. Being a motivated high-achiever taught me that the more you have, the more you expect, leaving you perpetually dissatisfied. The only way to be happy in life is to say "I'm staying here, this is comfy".
I'm trying to save and invest as much money as I can, so that before my body deteriorates due to aging, I might enjoy some time not having to worry about forces beyond my control or understanding carelessly ruin my life. I'm not planning to do anything spectacular once I get to retire. I'm just going to watch TikTok and I'm going to be happy.
> They really don’t require you to know the latest frameworks, databases, Kubernetes, etc
The latest "framework, databases" are constantly changing. Being good at leetcode and system design is a better signal (ofcourse, not perfect) than knowing specific tools.
Being good at system design implies you are aware of tradeoffs across various systems, and that coupled with willingness to grind means you can at pick up new tools and probably deliver on projects. I have used 13 languages and an equally absurd amount of tools across 4 orgs in my 5 YOE at FAANG. It's constant learning, or you're out basically. Doesn't make sense to quiz on anything specific. The interview process is quite fair actually.
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.
"Grind" just means "memorize a bunch of stuff for later regurgitation", which is the same thing as is demonstrated by memorizing the API for some arbitrary database or javascript framework.
Willingness to "grind" is a positive signal for people hiring developers in the same way that low critical thinking skills is a positive signal for people hiring law enforcement officers, and results in a team of similar quality.
"decision-makers can remain irrational longer than you can remain solvent" - Very correct. Whether or not AI actually comes for your job, the fact that enough people at the top think so is enough to cause trouble.
A non-technical friend was asking about the prospects of AI 'taking over' jobs. I told him that I'm less worried about 'Skynet' than I am about 'Slopnet', where bad takes on the applications of 'AI' just make life harder for all of us. That'll come more from decision-maker irrationality than from the tech itself.
This is the problem. Right now we're not in the, I need AI to work or get out stage. We're in the AI might completely upend reality stage.
It's just people telling stories to find bigger fools. Like the ads claiming they sell an AI employee that never needs sleep and never talks back.
Those ads are the same thing as those ads shoved in the lawn near the mcdonnalds drive through that look like they were drawn with sharpie, but are really mass printed. "Real estate investor looking for pupil, trade my money" kind of stuff.
They are purposefully looking for suckers that would overlook the sketchyness. They don't want normal people applying, that reduces the pitches effectiveness.
then why don’t they co-locate teams when they get RTO’d? I keep hearing about people who have to go sit in a mandatory hot desk but are still stuck on Zoom all day. Seems like the worst of both worlds
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.
It’s not really an exception though. These are the same people who spent the last 20 years singing the praises of offshoring and follow-the-sun. It’s just trend chasing.
Honestly I think the mistake we made was calling it “work from home” instead of “telecommuting”.
> Honestly I think the mistake we made was calling it “work from home” instead of “telecommuting”.
I am curious. Why do you think calling it telecommuting would have made any significant difference? And what difference would it have made? Where do you imagine we would be today if more people referred to it with that word?
My drive-by opinion: "telecommuting" has an advantage in optics/marketing and flexibility over "work from home" for both business leaders and employees. If I tell a board of directors or shareholders that "80% of our workforce performs some fraction of their weekly tasks ______", I imagine the following:
- "from home" elicits images of relaxation and lost productivity, while "via telecommuting" sounds like a commute still takes place and work is just as productive
- "from home" sounds like retreating to a comfort zone, while "via telecommuting" sounds like embracing a new technology or skill
- "from home" sounds like remote workers ought to be performing their tasks from their domicile only, while "via telecommuting" sounds like remote workers can do their work wherever they are
If businesses had adopted "telecommuting" terminology, I believe business leaders would not feel obligated to push back in order to regain productivity. I think it's easier to attack the trend of WFH given the points above. I actually agree with the proposal that WFH is a weak terminology, but had never sat down and thought about it before.
From the perspective of initial adoption, I think it would have happened just as fast. Workers were thrust into remote work arrangements during COVID, and everyone would have quickly gotten the gist of what "telecommuting" means, so it would have been the new buzzword to attract talent in job listings just as "remote" or "work from home" have been. Just without the downsides in CEO perception.
RTOs generally have nothing to do with any of the things they say. They are just layoffs.
You can't argue with them about the effectiveness of remote work. They aren't trying to optimize work. They are trying to fire people.
Working from home doesn't fire people, being more productive and happy doesn't fire people. Your mental well being doesn't have any bearing on how many people they need to fire.
Exactly. It’s less about whether AI can replace certain jobs and more about the fact that companies are making decisions as if it will. That alone reshapes hiring, budgets, and job security
We are still doing scrum-like stuff after all. And they are dragging people back to the office. Decision makers have billions at their disposal to be inefficient with.
I started my own business last year that has happened to go quite well. As I’ve watched the software industry over the last year, all I can think is… “damn, what lucky timing.”
I keep looking for what you claim to be doing. I feel like reality continues to smack me in the face with “no one cares about quality”. I have tried big enterprises. I have tried 8 startups in 18 years. I watch the leaders / founders make the same mistakes over and over.
Anyway - your profile resonates with me. Would love to grab a virtual coffee if you are up for it.
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.
The blog confused me. The author opens with senior leaders but does not distinguish between ic and managers. That is a very important difference and the way they are written is somewhat interchangeable at the start but I don’t think that’s necessarily correct.
Managers and senior ics are both facing unique challenges now. However, they are very different and don’t have a lot in common.
For me, as a senior ic, it’s having the right skills and staying afloat in this challenging environment. For the middle managers, from what I can see, it’s not being redundant as Mark Cuban recently pointed out.
I get why someone would want to tell people this, but I think it fails to be advice, as it describes the current state of affairs without much actual guidance for how to do better in it
Which, to be fair, no one really seems to be able to answer that meaningfully
The real answer is, leaders chase trends, so to keep them satisfied you need to also chase trends.
Some advises can be:
* learn prompt engineering to impress your boss and next employer
* adapt AI IDE at work, of course don’t go for cline or freemium ones, go for max expensive tier of Cursor/Windsurf/v0 etc
* Take some expensive(more the better) courses and workshops on Agentic topics, build some small projects. Justify your expenditure by citing being more well prepared for AI transition and adapting to new paradigm to strategically beat the competition businesses who will be extinct without employees with such trainings
* build some proof of concept projects to convert the smaller trivial projects to use agentic workflow. Then show these to your boss and put these up on github for future reference
* learn to train smaller models on your own internal documents, build a chat interface on top and give access to your boss(trust me, they will be blown away and will sell this to their superior)
* seed fear in your colleagues’ minds by using AI stuff where possible
Think of this AI as a new trend we must adapt to, just like FE moved from jQuery to React. Life and work goes on, just this wave nudges the complacent bunch to finally get out of their comfort zone and learn something new or get left out.
Problem solving and UX are not code dependent. Non-coders and entry level folks are using these tools and confusing the output with solving a problem, a business or user problem. It has made my work more difficult to get bogged down into debates about slop that middle managers have posted and said they've done what I can do. Most of the real world integration of these things has devalued the skills of actual programmers. It's so much more than syntax and loops. It's kind of like people who think they've figured out magic tricks. Ok, but haven't you wondered why that isn't useful in any other context?
The shift in what's valued (moving from team-building and hiring prowess to sheer execution speed and adaptability) has been stark. It's also unsettling to see so many senior folks feeling -left behind- not because they lack skills, but because the rules of the game have changed so quickly...
> decision-makers can remain irrational longer than you can remain solvent
Feels definitely true. I wish ICs had much more agency. Wish there was something actionable even as a small step (which I don't think is there on the article).
Having been laid off due to unclear reasons, can't help but think the same could happen in my next prospective job (if I get one in this market that is) and there's nothing I could do about it.
> managers were generally evaluated in that period based on their ability to hire, retain and motivate teams. The current market doesn’t value those skills particularly highly, but instead prioritizes a different set of skills: working in the details, pushing pace, and navigating the technology transition to foundational models / LLMs. This means many members of the current crop of senior leaders are either worse at the skills they currently need to succeed, or are less motivated by those activities. Either way, they’re having less fun.
Don't geeks enjoy playing with LLMs much more than hiring or any other admin/people/meeting type interaction? They should find dealing with the new wave of AI success a lot of fun, and a lot MORE fun that governance stuff, IMHO.
The statement
>The current market doesn’t value those skills particularly highly, but instead prioritizes a different set of skills: working in the details, pushing pace, and navigating the technology transition to foundational models / LLMs.
depends on the assumption that technology must "transition" to "foundational models / LLMs". The author doesn't seem to interrogate this assumption. In fact, most of the career malaise I've seen in my work is based on the assumption that, for one reason or another, technologists "must transition" to this new world of LLMs. I wish people would start by interrogating this bizarre backwards assumption (ie., - damn the end product! Damn the users! It must contain AI!) before framing career discussions around it.
However,
>decision-makers can remain irrational longer than you can remain solvent
is unfortunately painfully true.
It’s important to understand how AI will affect your field and recalibrate your position or contribution accordingly
It is a big enough change for this to be a valid question for anyone in the world today
Leaving what you’re doing and going into “AI” will likely set you up for a crypto level disaster
Vibe coding is a thing but vibe business building or job hunting isn’t! So beware of hype and know that in the end money is made by serving people and it will be equally hard with vibe coding too because the bar is higher
AI will create newer opportunities for sure but follow the opportunity, not the AI is what the sentiment here is I guess
>It’s important to understand how AI will affect your field and recalibrate your position or contribution accordingly
In the case of my industry (middling cybersecurity) we're seeing the following "advances"
- When you ask someone a question, they vomit your question into co-pilot, paste the result, and presume that they have helped somehow.
- All meetings now have not-useful meeting notes and no one reads these.
- People are considering implementing security co-pilot, which will introduce useful advances such as spending much more time building promptbooks so co-pilot can understand our logs.
- A lot more people think they're engineers, and vomit out scripts which do things the "authors" do not anticipate.
>- 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?
This is basically what happened when you can 'Google' something. Thus is like that on steroid.
> The author doesn't seem to interrogate this assumption.
Neither do my senior leaders, so it might as well be true.
Our senior leaders have also been completely captured by this crap. Recently our CTO (public company in the US you've heard of) announced in chat that engineers with an aversion to relying on LLMs have an attitude problem that is incompatible with our company direction. I was blown away.
Only in the short term. In the medium to long term, false assumptions will kill a company. As an employee, you would be better off recognizing it before the crunch hits.
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.
Exactly my thoughts reading this article. Luckily if next few years we will have thousands of projects written using 'ai' there will be need for someone to debug and fix all of that broken software.
Or maybe not, maybe it will be cheaper to just slap another ten k8s pods to mitigate poor performance...
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.
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.
The real revelations will come(it always does, nature and economy works in cycles), when excessive layoff caused damage will come due and now everyone will scramble to rehire people in few years. Unlike the Ford innovation of replacing horse carts, software is more prevalent in our every aspects of life, same as doctors and lawyers and civil service, hence we need to honestly play the game until the wave turns and then cash in by making in 200x killing just like the businesses are cashing in on right now.
> 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.
> 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.
He's describing the current market, not speaking about how the market should be.
No one knows what the "current market" thing really is, people are making wild guesses looking at the hands of other people who also make wild guesses.
Is it statistically possible that one guess will approximate reality?
How statistically probable is it you’ll come across that correct guess?
If it’s a binary choice, then odds are 50/50
I do think some transitions are inevitable and not because AI must be used, but because once enough companies figure out where it genuinely improves efficiency, the competitive pressure to follow suit becomes real
The same holds true for software developers imo. If you can't figure out how to use LLMs to improve efficiency, your likely a dinosaur of the past soon (unless you work on somethink __very__ specific where LLMs dont help much).
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
The best use I've gotten out of LLMs is as an autocomplete. I use Cursor at work, and it's pretty good at consistently calculating the next 10-20 characters I want to type out. Anything longer, save for some situations where the changes I'm making are super repetitive, the quality dives off a cliff.
I've yet to coax out good/working code of significant complexity from these models without putting an amount of effort into prompting that would be greater than just working it through myself without any LLM assistance.
The use I do get out of Cursor can save a lot of time for me, so I do think it's a productivity boost as is.
It likely wont be from where you expect though.
It isnt always a bad idea to wait until trendlines are clear.
LLMs will not go away but it's still not at all clear what skills investment should be made to respond to that.
Ive learned a ton about obsolete tech in the past and ive even learned a ton about LLMs in the last year that ended up becoming obsolete.
Think about what you're asking when you tell these people to interrogate the assumption that LLM based AIs are going to be the dominant technology going forward. Hundreds of billions, the growth of the technology industry, the entire US stock market, and the global economy has been wagered on this technology. Imagine the turmoil when those in power realize the reality of what they're betting the farm on.
The next time I am angrily typing to claude 3.7 in all caps because he overengineered a bunch of code I didn't even ask him to write in the first place, I'll be sure to let him know his continued failures are risking the entire world economy.
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're just describing programming without realizing that having a stochastic and imprecise programming language is a leaky abstraction.
The problem isn't that a "pro bowler" could come in and do something irrelevant for more money. Professional programmers understand that you shouldn't prematurely optimize things like memory or performance in contexts where that doesn't matter. You're ignoring the most important metric which is correctness. When we write a program, we make it correct then we can optimize it if that's actually important.
What's going to happen when you have your non-expert write a program using these tools and it inevitably gets something wrong? Are you prepared to build business process on top of a program whose author can't tell you how it works which might contain bugs? Do you even realize that this is just a recipe for producing mountains and mountains of technical debt?
You seem to believe this is going to put programmers out of a job but you're just explaining why they'll need even more of us in the future when these piles of garbage inevitably cost the company money.
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?
You don't stop the car but speed up faster toward the wall. That has been the strategy in the last decade or so. In other words, you invent a new AI-BLOCK-WEB-4.X thing and move the bubble one stage further.
Just like we study the “Crash of 1929”, our kids will study the “bubbles economy”:
- Internet bubble 2001, - Blockchain bubble 2021, - AI bubble 2025,
(Omitting 2008 and Covid because they’re not startup-related).
Am I wrong or are they bubbling faster?
I think bubbles form and pop all the time. I would add (in the US) home price bubble, biotech bubble (of mid 2010s), cybersecurity bubble and more.
Pops are less noticeable when a lot of money is sloshing around so deflating one bubble immediately start inflating something else. Worker bees can switch to the next thing in the same "building next great thing, work is plentiful, money no object" environment.
So the bubbliness, IMO, is a function of the macroeconomic state, specifically the amount of money in the economy. Things get sober (and very ugly) when the money printing cycle ends, as it eventually must to avoid sliding into hyperinflation. My 2c.
I think 2008 set the stage that the government will bail out reckless economic activity for the top at the expense of the tax payer. Actions no longer have consequences and you better be big enough to hold the economy hostage to your scheme.
Goodness this is such a perfect response.
Seeing more and more of this now, where even in "these parts" anything short of "AGI IS HERE" even a few months ago would have you labelled as "Luddite" "skeptic" and "left behind".
When is the general public going to start asking questions? It's really not a game--people's 401ks have been propped up by the "Magnificent Seven" (disproportionately by one company) for some time now.
What happens "if" these proclamations fail to manifest? How is this all supposed to work out?
I'm entirely in agreement with you, I just have a dark sense of humor.
I do actually use claude quite a bit recently and I suspect (completely anecdotal, so take it with a boatload of salt) it speeds up my development time by about 25% on average. But its a very lumpy sort of speed up that is sometimes a slow down depending upon how wacky the LLM's answers are. And I find claude 3.7 to be worse than claude 3.5 in many ways which makes me confused about how hyped up it is and further disillusioned about the "common sense" idea people around these parts have that the technology is just going to keep improving significantly year over year.
I use it entirely through the web interface and using the lowest price basic monthly subscription fee. I am probably a cost center for Anthropic rather than a profit center, but I don't really see that as my problem to worry about. I'll enjoy the thing while it lasts and then not cry too hard when the house of cards collapses.
comments like this are giving me life lol
I feel like I'm living in an insane asylum but your experience largely matches mine, except I've been reluctant to open my wallet
I don't think companies like Meta, Alphabet or even Amazon are extremely overvalued. Their growth in revenues and earnings is still very solid, so even if A.I is a no show their earnings should continue to do fine (I'd even add Microsoft to the list). Sure stock price might slow down significanty but it can easily add 10% yearly for the forseeable future. Its much less than what we're used to, but its solid growth that has not much to do with A.I.
And I totally agree people should forget about the s&p 500 returns we've seen in the last 15 years going forward, it would probably be less (though I have no crystal ball, but regression to the mean seems likely).
Actually, all stocks are dead and tech heavy Nasdaq has entered the correction zone this year. It will be a real while before the stocks return to their pre-correction value. The AI hype drivers have lost massive value, hence the desperation will get immense, expect the “AI ready to replace expensive SWE/Lawyer/Entertainers/Creatives” narrative to start any moment now! Of course everything is smoke&mirrors so those will be charged at such premium that the naysayers will not be able to afford it and irrational leaders will buy it and cite immense success to maximise their C level bonuses and will early retire before the tower comes falling down.
Correction is one thing but saying "stocks are dead" is hyperbole. Just my poor ass startup is paying Google Cloud around 1 million USD a year to have our operations going. We're quite a cheap company but we're totally dependent on them. And Cloud is a minor part of Google's earnings they have Youtube, Search, Android etc etc. This isn't a bubble, these are real earnings that are probably not going away any time soon. Does it mean Google is bullet proof? No. They may experience a big correction at some point but that has always been the case for all companies.
I can make the same case for Meta, Microsoft, to lesser extent Amazon. I'll leave Tesla aside it's indeed too richly valued.
I meant red(dead). Also losing a lot of valuation after jacking up to that point is not fun.
Also a business paying $1M/year in cloud bill is neither poor nor tiny. We have very different definition of tiny and poor.
Meta is very well suited in this AI race and will prevail well. Others will cut some loss and throw some ashes sometime soon.
It will be incredible when the bubble pops. Especially if it coincides with the upcoming downturn in the economy.
Yeah... unfortunately that might be where we are.
I have no analogy for this except the railroads of the Gilded Age. Did railroads become a pretty big deal? Yeah. They were also a giant vortex that slurped up endless investment, far more than the real demand could possibly justify. And it ends, well, we know how it ends.
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.
At the very least, lots of software will end up running on GPUs.
We've become so accustomed to the rip-roaring growth that came from widespread Internet adoption and now that it has piped down, we're desperate to find the next big boom. VR, crypto, blockchain, generative AI. And each time, like degenerate gamblers, we're feeling it, this must be it, the next Big 'Un, the bet that redeems all the bets that went wrong, bigger, riskier, bigger, riskier.
But it just won't be, nothing in our lifetime will ever come close to what the Internet boom was. The window for becoming a Jeff Bezos or Mark Zuckerberg as easily as they did is closed now, and you just need to live with it. The title of this chapter till the end of our days will remain "After the Internet Boom" and it will chronicle this pathetic desperation.
I agree with the sentiment, but LLMs have already had a lot more adoption than VR and Crypto.
You're right of course, but nobody ever gave me a free VR headset or a few thousand dollars of Monero. OpenAI and Google will both give you, for free, access to an LLM whenever you want. I can do a Google search and help with LLM adoption right now, it will be at the top of the page.
> Hundreds of billions
Yes
> the growth of the technology industry
That's an overblown claim. AI companies failing won't mean technology doesn't advance nor that companies betting against/independently from AI would recind.
> the entire US stock market
Probably yes
> the global economy
Probably no
Don't be silly, if the entire US stock market really was wagered on this technology then you'd better start learning Mandarin.
It wouldn't be the first bubble. That doesn't make the above point about questioning it incorrect.
This guy probly doesn't doesn't do any actual work just reads ppl like Mario Damadai who are out there claiming 90% of coding will be done by llms in next 3-6 months.
"thought leaders" are a plague on working ppl.
Will wrote one of my all-time favorite essays about software engineering: https://lethain.com/migrations/
He's worth paying attention to IMO.
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.
yep i had the same reaction doing a quick read. Whats the insight here?
This was excellent and rings very true, thank you
Is he going to update it with how AI will assist in migrations? Or get an LLM to ghostwrite it?
An excerpt of the author’s bio:
> I’m a software engineering leader and writer, currently serving as Carta’s CTO. I’ve worked at Calm, Stripe, Uber, Digg, a few other places, and cofounded a defunct iOS gaming startup
Is this supposed to be an endorsement or an indictment?
Why would it be 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.
How are they checking if you are using AI enough?
[dead]
Some more free advice, in no particular order:
* Try to get at least one job offer every year, even if you don't accept it.
* Look at the requirements for your dream job and figure out what you need to learn to qualify.
* Pick one skill and get very good at it. Spend an hour a day on it for a year.
* Steer away from skills like web development that are clearly getting eaten by LLMs.
* Look for work in major U.S. tech hubs like the Bay Area. Pay is better and network effects are strong, so your next job will be easier to get.
> Steer away from skills like web development that are clearly getting eaten by LLMs
On the contrary, here in my corner of EU nearly 60% of new jobs are frontend or full stack.
Anything else left is mostly SAP consultant or DevOps.
I think, the whole WebDev is dead end is just false lies to dissuade new entrants. Literally most successful business with a digital solution is web stuff with some automation that would otherwise be ms excel sheets shared via email.
Also this whole panic over LLM is overblown, I know of some brilliant experienced people in other professions like Electronics, Mechatronics, Aerospace, Material Science and literally all of them are finding the job market “very difficult at the moment”. It is the bad global mood in general used deceptively by opportunists to spread false fears of their LLM/AI.
At the end of the day, an insurance seller has hundreds of concerning reasons to convince you why everything is dangerous around you and you really need their product. Now apply that to AI sellers.
Web element feel similar to PHP or wordpress development in 2010.
There are millions of small businesses that demand wordpress websites, but the barrier to entry to support and build systems got very low very quickly. Professional developers were competing with high school students and offshore devs for work.
As a backend Developer, I can now build websites easily with Claude and react. I think web development, especially front end, will be like knowing HTML and CSS in 2015. Like everyone should know it, and thus not even worth putting on your resume.
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.
Well, "frontend development" means a million different things, but LLMs are very good at flexbox and grid (and I'm not).
With backend I find they're good at the really high level (give me the options for architecture and their pros and cons) and doing something small and precise (gimme a function `List (Maybe a) -> List a`). The stuff in-between I have to handle myself.
> Well, "frontend development" means a million different things, but LLMs are very good at flexbox and grid (and I'm not).
This is my #1 complaint about how people talk about LLM productivity
If you aren't good at something you are not qualified to say that LLMs are good at it
Developing, managing, and operating distributed systems infrastructure has way less training data available than webdev. And it doesn’t translate in to pithy interpreted language one-liners.
There's another factor here I forgot to mention - web development, as a specialization, tends to be paid less and has a lower career ceiling in many companies than backend and infra engineering. This is a personal observation on my part but I've seen many other people remark on this. True full stack engineering, I think, is reasonably safe from the robots at the moment.
If someone likes building products, I'd basically recommend that they not go 100% full-bore on frontend engineering, definitely go for "full-stack", and accept that a lot of frontend code is trivia that you can just ask the LLM for these days. I would also recommend that they develop solid product management and UX skills.
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.
> Steer away from skills like web development that are clearly getting eaten by LLMs.
You had it going well there but then had to ruin it with a take like that.
If you’re talking about your trivial, github-filled example scenarios of frontend, sure. But then we could say the same for all other roles, including backend logic that’s regurgitated all the time.
Like with everything else, the non-trivial bits need work and skills.
Except that they’re right, a your “non-trivial bits” will like 5% and rest will be dealing with idiots copy pasting AI slop.
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.
Good advice in general. I would add - try to pick a skill which gives you a deep understanding in something fundamental which will always be relevant, rather than a particular shiny tech.
I would love the bay area, but unfortunately it is extremely inaccessible for me and others once you have a family. Trying to find a place to live in a good school district seems like it takes minimum $2M for a house. Renting is less long term secure when trying to maintain consistency for kids. That's not even get into earthquakes and wildfires!
If you’re usual child-raising age then you probably have 6-10 years of experience, and there should be lots of jobs that pay $500k in the Bay Area. Buying a $2m house on that salary is pretty doable.
$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!!)
> Look for work in major U.S. tech hubs like the Bay Area. Pay is better and network effects are strong, so your next job will be easier to get.
Jobs and the network effects happen all across the country. As you get older and maybe don't want the grind, or have a family, or just want a better work/life balance, this will become apparent.
Basically, always have at least two people who will support you for your next job.
There are plenty of tech hubs besides the Bay Area, that's for sure. But I can tell you that when I moved from a small company in a small economy to a moderately-well known startup in the Bay, the rate at which recruiters contacted me jumped from maybe a few times a year to multiple times per week. And after a few years, many of my coworkers started their own companies and invited me to join them.
By contrast, I have very talented friends who did not make the jump to work at a tech hub, and they don't have the same kind of network or opportunities.
With that said, I very much agree with you about wanting work life balance, making sure there are people who will support you in your next job, etc. However, I think that this is much easier to optimize for when you do have an established career and an extensive network already.
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.
I would love for this to be the case!
>Steer away from skills like web development that are clearly getting eaten by LLMs.
What do you mean by web development?
Would backend qualify? Would microservices qualify?
A complex application is much more than coding.
I'm mostly thinking of frontend dev work, but also some types of light backend work that you might see in a CRUD app. And listen, I've done that work, I've done a lot of it, and I saw that it's mostly a career dead-end, becoming more and more automated/copiloted away. It's not a career moat to be a mid-level React developer. By contrast, some things I think are worth pivoting into include infrastructure, databases, data engineering, stats, etc, and I've spent the last few years pivoting into those areas.
An interesting counter-point is that if you have great product and design skills, this is a great time to learn frontend development, because it's more accessible than ever and can supercharge your existing skills. But the days of being a pure frontend coder are probably fading.
> 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.
Probably not, but if you are the UI developer that gets annoyed by it every time you open the application, it means you are probably in the right place.
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.
Theoretically - yes, practically, on average, any of the things you’ve listed is far, far, far more complex than your average frontend that is basically glue between “real” logic and user.
If you are doing CRUD simple data apps, I don’t get why your backend will be complicated. Sure the industry has complicated stuff (aws & friends) for complexity sake but that doesn’t mean you have to go down that rabbit hole.
Front-End is complex which is why we have 36362 libraries to solve the same problem and still move user interfaces sucks.
I'm not a fan of the "front vs back" dichotomy. Chrome is just another box as far as my responsibilities and goals are concerned, but it always feels like there's a mental handoff switching to this one context.
>infrastructure, databases, data engineering, stats
Why would those areas be less exposed to the "LLM threat"?
To be brutally honest, LLMs aren't very good at solving novel problems, they aren't very good at integrating business context, and they make many small mistakes. That's why they are a good fit for frontend development! Frontend features are
1. often quite deterministic (well-defined specs and mockups from product managers) and
2. repetitive (95% of all frontend features have already been built many times in the training set) and
3. small mistakes often don't really matter much, the page will just be slightly degraded. Speed of development usually beats perfection.
So you can often say "hey, Claude, here is the exact feature I want, this has been done many times before, can you update the codebase to mostly do that?" And Claude can do that in a lot of cases now, and will probably continue to get better at it over time.
By contrast, infrastructure work tends to be more complex and higher stakes (a small mistake can cost you a lot of money or downtime). Also you usually aren't optimizing as much for a large number of small features. So there's just not as much value, and much more danger, in turning an LLM agent loose on this stuff.
This is an extremely dumb take, I’ve worked on both areas before and I could say that infra work is mostly repeated and needlessly complex config sprayed into git. LLMs have seen enough of that to make head or tails of it by the way you’re characterizing frontend dev.
> This is an extremely dumb take
...ouch! ;)
The important part is NOT auto-generating repetitive configs; it's about the effort and skill required to verify that output. On the frontend, we have an easy feedback loop to preview the effects before deploying. That also helps us produce lots of training data for frontend LLM output.
On the backend, there is substantial risk with infra changes - you could drop the database, block production traffic, etc. etc. You can't just vibe code the infra configs and hope for the best, you need someone who understands the output well enough that they could have written it themselves. That means that LLMs are at best a modest productivity boost for infra engineers right now. It's also much harder to simulate the output of LLM infra changes compared to running a browser, so it's more expensive to get training data to boost the next version of the model's performance.
> On the frontend, we have an easy feedback loop to preview the effects before deploying
There are many ways to introduce subtle bugs into your system, I don't think the risk is that low in the front end. I'd agree with your take if LLMs were reliable, but they're not - especially on big codebases. A broken form is downtime just like a broken API endpoint, the damage is the same.
I understand where you're coming from, there's the sense that front end work is "less important" than backend work in some places, but honestly every company that cares about its product shouldn't really adopt this philosophy.
Product work is super important - it's something I care about a lot. I think it's just different from infra work, like comparing woodworking tools to a dump truck. You're going to do a lot of fine-grained feature work with your woodworking tools, and if you scuff something up or break a piece, that's not too disastrous and can be fixed. But the dump truck can, like, destroy your warehouse, throw your inventory on to the highway, or explode. Even if there's a similar error rate in the auto-woodworking-tools to the self-driving-dump-truck, the dump truck's mistakes are too risky.
We should probably also distinguish overall quality from error rate. If the woodworking tools are producing crappy stuff, then there's no reason to use them at all. But if they produce mostly nice stuff, fast, but occasionally break a piece, they might be really useful.
You once again seem to be thinking of trivial examples of frontend to say there is an “easy” way to verify the loops. I really wish it were that simple for anything reasonably complex I encountered that were customer-facing — often filled with plugins/apps/micro-frontends/libraries owned by other teams etc or clients. I also think if it were that simple, companies wouldn’t be popping up every now and then trying to solve challenges in this space w.r.t validating flows, interactions/animations are smooth and ensuring some weird stuff isn’t happening across all the browsers the customers of your product are using. But there are a lot of them gunning for a piece of the pie, more since the LLM frenzy. And this is largely just web stuff I’m talking about, I’m sure similar complexity exists for mobile apps if we are to count that also into the equation.
Re: backend risks, I once again think you try to rub this off by equating all of backend development is done the way you’re talking about — to perfection, with backups, tests for those backups and all that. I’m sorry to burst your bubble here but if we’re thinking about the same kind of scrappy development you’re talking for frontend, the backend side is about as bad or worse (given how critical you think all of this is, which I agree with). I doubt the backend engineers are sitting there, carefully reading manuals and crafting code instead of vibecoding.
> You can't just vibe code the infra configs and hope for the best, you need someone who understands the output well enough that they could have written it themselves.
It’s not vibecoding but I’ve seen engineers in this role google, copy-paste and modify configs and scripts that run multi-million dollar workflows which somehow worked at the end of the day. I bet LLMs can do a much better job than that, don’t you?
> It's also much harder to simulate the output of LLM infra changes compared to running a browser, so it's more expensive to get training data to boost the next version of the model's performance.
I disagree. It’s much, much harder to go and debug why your customer on X OS, Y Browser and Z GPU (to simplify) is seeing glitches when others are not. Sometimes that leads you to browser bugs. I am yet to see any AI-loop based tools come close to tackling the kind of real-life, serious prod-driven challenges. If you think running a browser is all it takes, I can say something dumb like “running a container is all it takes” but see how stupid that sounds? :)
And it’s also silly to think UI mistakes don’t have real-world implications. There are countless examples for this already — broken purchase flows resulting in losses, frustrated customers unable to complete their work and leaving apps, incorrect request flows causing small/big DDoS, sometimes even stuff that might lead to lawsuits.
——
I feel you have a bleak view of frontend as a whole or you never worked with teams who do a good job or you have been conned by the chest-thumpers who have been saying for years and YEARS that frontend development is pointless, not real CS and have zero value. Oh, and that JavaScript is not a serious language — classic!
If I saw backend/infra engineering the same way based on the # of devs and teams I had to hand-hold and # of their mistakes I had to help fix while working as a front-end engineer, I’d be shitting on them too. But I know better to see that there’s a right way to do it.
> I feel you have a bleak view of frontend as a whole
First of all, let me say, I love frontend. I spent probably a decade building products and tools almost entirely on the frontend. I enjoy interfaces and workflows and visualizations. I don't want you to feel like I'm attacking frontend or frontend developers.
> often filled with plugins/apps/micro-frontends/libraries > It’s much, much harder to go and debug why your customer on X OS, Y Browser and Z GPU
Second of all, it sounds like you're doing some pretty complicated stuff! And that you care a lot about how your work affects people. That's awesome. I don't think LLMs are particularly close to automating web development done at this level.
Here's where I'm coming from: A shockingly large amount of interesting frontend work can now be done, reasonably well, by an LLM. Sure, it's no staff frontend engineer, but you now have people who can't code at all who can dream up little apps and have the LLM actually just build it for them, something actually useful. That is absolutely incredible to me.
I also see the momentum here - if there is any area of software engineering that the model companies are trying to automate, it is frontend engineering. Will they get all the way there? Eh... probably not. But it's going to keep getting better. I think this will make the best frontend engineers much faster and more productive, and will probably make the field more competitive as a result. People will need to learn entire new workflows to stay at the top of the field, and there's no guarantee on how good AI will get. Candidly, I just don't see the same momentum for AI in the database/infra space, and speaking personally, I thought it was the right move to shift in that direction.
> I enjoy interfaces and workflows and visualizations. I don't want you to feel like I'm attacking frontend or frontend developers.
I hope you mean that but it's hard to see it that way based on your original comment and responses. The trope of "frontend is not a serious job" has been infuriatingly going on for a long time before LLMs took the center stage and that seeps out of the things you've said so far.
But, I'm glad if you mean what you said above.
> Here's where I'm coming from: A shockingly large amount of interesting frontend work can now be done, reasonably well, by an LLM. Sure, it's no staff frontend engineer, but you now have people who can't code at all who can dream up little apps and have the LLM actually just build it for them, something actually useful. That is absolutely incredible to me.
And this is where I'm coming from, based on your original reductive narrative on LLMs overtaking frontend and that the field is somehow at risk — if you feel the same way, you can apply these _exact_ arguments to a _shockingly_ large portion of backend too. I could say most are just glorified spreadsheets. Moreover, a lot of startups just use one of the "serverless" platforms and won't think twice about database, devops, security, authn/authz until they hit an escape velocity.
But I personally think meaningful engineering solving real-world problems at scale that is meant to be an enjoyable experience for the user should be well thought through, end-to-end, regardless of the smaller scopes within.
> Candidly, I just don't see the same momentum for AI in the database/infra space, and speaking personally, I thought it was the right move to shift in that direction.
Partly, I think you are probably forgetting that a lot of these startups promising all of this also promise the backend stuff, even if you might disagree with the choice of tech stack (usually React/Next w/ Supabase/Planetscale/Firebase) and the deployment environment (usually something like Vercel). And the reason why the frontend part is front and center is because... well... that's what the users ultimately interact with. They don't give two shits about the stack (front & back) as long as the product works and works well. But it'd be naive to think this didn't involve all the automated code being spit out on the backend side as well.
And let's forget AI for a moment, by this line of thinking, a large portion of the backend engineering you talk about have been available in simplified forms via serverless offerings or via low-code offerings. Same for databases, including branching and claims of seamless migrations and backup. So, maybe you should have started panicking way before modern LLMs hit the scene? :)
But you probably won't because like me, you realize it's not that simple and it's not always practical. Same reason why I am not using Framer/v0/<insert fancy new tool here> to build a non-trivial front-end app with growing complexity.
I'm a cautious optimist in this space. I do think the tech we got so far is cool and groundbreaking and I use them extensively for noodling. But at the end of the day right now, they're still tools. We are seeing the AI leaders shifting goalposts every day, complain about lack of data etc. and I honestly believe we are many more breakthroughs away from getting to the dream world you're thinking of, especially when broadly generalizing things.
> Aside: I'm also pretty sure you can find plenty of "AI" companies promising automated DevOps/Backend/Database etc. just within https://www.ycombinator.com/companies (try keyword searches).
> The trope of "frontend is not a serious job" has been infuriatingly going on for a long time before LLMs took the center stage and that seeps out of the things you've said so far.
Eh, sorry I came across that way. To me, seeing a complex system visualized, making it interactive, is just so beautiful. That's a big part of why I got into frontend in the first place. I wouldn't take anyone seriously who doesn't think frontend is a serious job.
I also suspect that you are doing more complex, and finely judged frontend work than I did - I took a peek at your public profile ;). So it's not surprising that we have different impressions. If someone is building a frontend that needs to work seamlessly for billions of people across many devices, that sounds incredibly challenging and frankly I've never even tried to do that so I can't even comment on it.
But, I would say that a lot of the frontend work that I find interesting can now be automated with LLMs. Historically, I've tended to build internal tools that usually had a fixed runtime environment and small number of users. So I'm not as worried about the fine points of the web, but about creating a lot of features and interactivity in a particular, easily tested environment. I would wager that the average frontend developer is doing work somewhere in between the two of us.
> you can apply these _exact_ arguments to a _shockingly_ large portion of backend too
Hmm, I think we just disagree here. I think a lot of my view comes down to how frontend ultimately needs to collapse into something that can be visualized and interacted with, and this helps force the state to evolve in sane ways. On the other hand, I think backends quickly grow from a spreadsheet to insane, highly-dimensional, highly-coupled nightmares that no one can really visualize anymore, first at the logic level and later at the architecture and schema levels.
Ultimately LLMs are helpful when they can sort of grok the overall structure and plan of your code and add stuff helpfully to it. I think that LLMs have more public examples of frontend codebases and that helps them follow the overall structure a bit better. In my experience, LLMs are doing a bit better in trying to add small features to large frontend codebases than to large backend codebases, probably for this reason.
Finally, you can often define what changes are wanted on the frontend fairly precisely. A series of mockups plus descriptions of the interactions carries a lot of detail. On the other hand, backend changes often interact implicitly with unstated business context that you can't get solely from the backend code itself (this become particularly tough when you try text-2-SQL, for example.) So I think many backend and architectural changes have inherently vague specifications that need to lean heavily on context that's not captured in the ticket.
None of this is meant to undermine the seriousness or difficulty of frontend as a profession. But it is still my opinion that, on average, LLMs have a better chance of doing useful things on the frontend than the backend.
I thought about this a bit more, and I think the boundary between front end and backend can be a bit artificial. Theoretically, one could do highly complex state management and data flows on the front end, even run your own database, etc. Not to mention complex dependency trees. All of this can and does happen, but in my mind this starts to leak into what I’d consider backend work anyway, just coincidentally happening in the browser. And I don’t think LLMs are particularly good at automating any of that.
But I think there is a huge chunk of work, which most people think of as front end, which is displaying pre computed data according to a particular pattern, and providing hooks into the backend for additional interactivity. I think that this piece can be largely done by LLMs now.
Because LLMs are dog shit. There I said it.
LLMs are not the threat right now. Mismanagement of the United States and a 2008 style recession (but without the TOGA power of the SaaS/cloud boom. AI is swimming naked financially) are the biggest threat for your career and employment in 2025.
Amount of quality fronted code in public repositories, blogs etc. is much higher. Then even if it is not in the repo it is available via browser.
Backend code is much less available as a training set.
Less data to train on? Github et all are awash in front end code but the stuff most enterprises run on is locked away and not accessible to the AI companies.
> 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!
I highly recommend csprimer for this.
https://csprimer.com/
Or if you want to just use books go with:
https://teachyourselfcs.com/
Realistically, you need to bootstrap your experience in these areas. Pick an area to focus on and put your own time into learning it. My rule of thumb is that you need about 100 hours of personal study to get to "smart intern" level in a particular tech skill, given that you're already a professional developer. I typically bootstrap a skill by picking a textbook to work through and combining it with personal projects and adjacent reading as it comes up. Usually after ~100 hours or so you will be able to arrange an internal transfer to work on that stuff in your day job.
A good signal is you get pissed off with LLMs because they hinder your job. Even if you tried in earnest to use them.
that sounds more like someone needs anger management classes than a problem with technology or LLMs
Feeling anger is not indicative of needing anger management
this and why not use LLMs and become an even more productive web developer
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.
On avoiding web dev: I get the concern, but I wouldn't write it off completely. LLMs are changing the game, but they're not replacing deep expertise in architecture, scalability, or understanding real-world business constraints
I don't think they meant architecture, scalability, or understanding real-world business constraints
I think they meant literally web developers, or, aka, frontend folks doing html and css.
I've worked on backend systems that run web sites and apis, for over a decade, and I've never once referred to myself as a web dev. That title has always been frontend specific imo
Good advice -> but is an error or blindness > * Steer away from skills like web development that are clearly getting eaten by LLMs.
funny enough all the hyped YC / Bay area startups don't make as much as your typical CRUD webapp. Devs we tend to be attracted to tech. but what makes good tech doesn't mean it's a good business. That's why your typical bay area startup depends on vc funding & will likely spend 10 years without being cash flow positive.
Why would web dev be eaten away by LLM's and other fields not?
Why would making a $5 shirt be eaten away by power looms and haute couture not?
Amazingly enough, I and millions of other developers have managed to find jobs outside of the Bay Area.
Personally, I’ve been finding jobs quite easily 10x since 1996 - the last 2 in 2023 and last year.
> Look at the requirements for your dream job and figure out what you need to learn to qualify.
Those jobs in the Bay Area mostly require you to “grind leetCode” and system design. They really don’t require you to know the latest frameworks, databases, Kubernetes, etc
Hey, as I said in another thread, I did not start out working in the Bay, and ended up here somewhat by accident. It shocked me how much easier it was to find good jobs here, and I'll stand by that. With that said, of course I say this with no judgment to anyone not in the Bay or other tech hubs, it's friendly advice from personal experience.
> Those jobs in the Bay Area mostly require you to “grind leetCode” and system design. They really don’t require you to know the latest frameworks, databases, Kubernetes, etc
Hmm, it sounds like you have a negative opinion of Bay Area jobs in general. I'm asking people to first figure out what work sounds interesting to them, and then learn the relevant skills. If you have the skills, the Bay Area probably has the right job, too. Of course these jobs also exist elsewhere, I'm not sure why I'm triggering this reaction...
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.
I agree, that is how many big tech interviews look. I've done 'em too. If one's dream job is a generic, mid-level role at BigTech, then the path is clear - get very good at Leetcode and system design, and flag down a recruiter.
My dream jobs tend to be more eclectic, and not necessarily at giant companies. I'm more interested in getting really skilled at a particular type of technology and being hired to work on that. And this kind of targeted recruitment still exists at big companies, too.
But also Leetcode doesn't scare me too much, so maybe I'm dismissing it too easily. I've done a lot of those problems over the years, and I'm FAR from great at them but it's never been the blocker to a particular role in practice.
Most people’s “dreams” have nothing to do with working. Their dream is to have a combination of shit ton of money appear in their bank accounts every pay period and stock to appear in their brokerage account every vesting period.
True there are some who want to win the lottery and accept less than their market rate in exchange for “equity” in a non public company that will statistically be worthless.
Coding interviews are definitely is still the part of the process you have to pass unless you are a very well known big deal in the industry.
BigTech companies want versatile developers who can move around as necessary.
There are no “inside tracks” for 99% of positions aside from probably acquihires.
You go through the grind regardless. Open source contributions really don’t mean that much.
Infamously
https://x.com/mxcl/status/608682016205344768?lang=en
It seems like you're really focused on the interview process for a small number of very large tech companies. My experience doesn't match yours - I have been recruited to a specific BigTech team based on my background, and the interviews were more focused on specific skills than leetcode. But it seems like most BigTech interviews probably are coding/system design.
With that said, I have tended to interview more at scaleups/late-stage startups in recent years, and it's been very rare to see a truly leetcode-heavy interview process. These are positions that pay comparably to big tech, although the equity is generally more risky. But I've also been able to cash out some startup equity, so maybe my experience is not representative again...
> Most people’s “dreams” have nothing to do with working
This line always seems like a cop-out to me. Almost all of us have to work, and it takes a huge amount of our time. And for many of us in the tech industry, we have been intrinsically interested in this tech since we were kids, and have specific stuff we'd prefer to work on. Can we just accept that certain work is going to be more interesting for certain people, and that they might want to steer their careers in that direction, especially if it pays better?
By pay similar to BigTech do you mean the cash you get paid at a startup/scale up is similar to cash + liquid public RSUs?
Equity in private companies especially in today’s climate is statistically meaningless.
And if you look at the companies that pay the most + have the largest number of opportunities, they are the “small number” of BigTech companies
And back to the Bay Area argument. Most of the major public tech companies have offices all over the US that pay the same with a much lower cost of living.
Stripe has given their employees a chance to sell their equity via a tender offer. SpaceX I’m not sure
There has to be a market of people who actually want to buy the equity and the company has to allow it. In the case of “scale up” early startups - the type the original commenter said he works for - usually either there is no one that wants to buy the equity or it’s a steep discount
Let me try to state your overall point, as I understand it:
"The primary goal of a tech career is generally to get a high-paying, low-risk job. Many of those jobs are in Big Tech. You should optimize for getting one of those jobs (but ideally not in the Bay Area, because it has a high cost of living.) To do that, you should primarily focus on grinding Leetcode and system design, because those are what Big Tech will evaluate you on. There are no loopholes worth speaking of, and you will be competing with many other engineers for the same positions."
Feel free to correct me if I'm not getting it right. I have no particular issue with someone whose career strategy is the one above. It's actually important information for someone to learn, especially if they come from a small town, like I did, where Google et al. never darken your door.
However, that approach is not a common one in my community. Instead, I see people who exited startups as founders or early employees, people who had particular skills directly recruited by BigTech and others, people who worked at private companies with regular internal liquidity events. People who worked on stuff, by and large, that was interesting to them. People who have plenty of job opportunities, and don't feel like they're one of a thousand people competing for each position. By and large, I prefer this approach.
Again, we can look at statistics instead of suffering from survivorship bias. The vast majority of employees in startups will not see outsized gains from exits especially in todays climate where the IPO market is dead and acquisitions are going for much less.
> Most people’s “dreams” have nothing to do with working. Their dream is to have a combination of shit ton of money appear in their bank accounts every pay period and stock to appear in their brokerage account every vesting period.
Yes.
It took me two years to have the illusion shatter and realize that I simply do not want to work. Imagine spending 8 hours a day plus commute sitting on your ass and writing corporate emails, and calling that self-realization. Or imagine grinding hard for a pay 50% higher than the security guard who's just playing video games, so that you feel like you're above the minimum-wage workers, but in reality you can't escape the poverty either.
I consider myself incredibly lucky to be working in a company where people who give a fuck are a minority, so there's very little pressure to actually do anything, while the pay is decent. I use some of my extra time to do some physical and mental exercise, so that my body doesn't collapse when I finally get to retire, and the rest is just spent watching porn. Being a motivated high-achiever taught me that the more you have, the more you expect, leaving you perpetually dissatisfied. The only way to be happy in life is to say "I'm staying here, this is comfy".
I'm trying to save and invest as much money as I can, so that before my body deteriorates due to aging, I might enjoy some time not having to worry about forces beyond my control or understanding carelessly ruin my life. I'm not planning to do anything spectacular once I get to retire. I'm just going to watch TikTok and I'm going to be happy.
> They really don’t require you to know the latest frameworks, databases, Kubernetes, etc
The latest "framework, databases" are constantly changing. Being good at leetcode and system design is a better signal (ofcourse, not perfect) than knowing specific tools.
Being good at system design implies you are aware of tradeoffs across various systems, and that coupled with willingness to grind means you can at pick up new tools and probably deliver on projects. I have used 13 languages and an equally absurd amount of tools across 4 orgs in my 5 YOE at FAANG. It's constant learning, or you're out basically. Doesn't make sense to quiz on anything specific. The interview process is quite fair actually.
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.
Leetcode shows candidates willingness to grind.
"Grind" just means "memorize a bunch of stuff for later regurgitation", which is the same thing as is demonstrated by memorizing the API for some arbitrary database or javascript framework.
Willingness to "grind" is a positive signal for people hiring developers in the same way that low critical thinking skills is a positive signal for people hiring law enforcement officers, and results in a team of similar quality.
Ask yourself: "What do I need to learn now for the next five years of my career?" Learn that.
Five years from now, ask yourself the same question.
"decision-makers can remain irrational longer than you can remain solvent" - Very correct. Whether or not AI actually comes for your job, the fact that enough people at the top think so is enough to cause trouble.
A non-technical friend was asking about the prospects of AI 'taking over' jobs. I told him that I'm less worried about 'Skynet' than I am about 'Slopnet', where bad takes on the applications of 'AI' just make life harder for all of us. That'll come more from decision-maker irrationality than from the tech itself.
This is the problem. Right now we're not in the, I need AI to work or get out stage. We're in the AI might completely upend reality stage.
It's just people telling stories to find bigger fools. Like the ads claiming they sell an AI employee that never needs sleep and never talks back.
Those ads are the same thing as those ads shoved in the lawn near the mcdonnalds drive through that look like they were drawn with sharpie, but are really mass printed. "Real estate investor looking for pupil, trade my money" kind of stuff.
They are purposefully looking for suckers that would overlook the sketchyness. They don't want normal people applying, that reduces the pitches effectiveness.
Only desperate people who will fall for anything.
Same is true for remote work. All the engineers know the return to work policies are dumb but all the decision makers have decided we’re all wrong.
then why don’t they co-locate teams when they get RTO’d? I keep hearing about people who have to go sit in a mandatory hot desk but are still stuck on Zoom all day. Seems like the worst of both worlds
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.
It’s not really an exception though. These are the same people who spent the last 20 years singing the praises of offshoring and follow-the-sun. It’s just trend chasing.
Honestly I think the mistake we made was calling it “work from home” instead of “telecommuting”.
> Honestly I think the mistake we made was calling it “work from home” instead of “telecommuting”.
I am curious. Why do you think calling it telecommuting would have made any significant difference? And what difference would it have made? Where do you imagine we would be today if more people referred to it with that word?
My drive-by opinion: "telecommuting" has an advantage in optics/marketing and flexibility over "work from home" for both business leaders and employees. If I tell a board of directors or shareholders that "80% of our workforce performs some fraction of their weekly tasks ______", I imagine the following:
- "from home" elicits images of relaxation and lost productivity, while "via telecommuting" sounds like a commute still takes place and work is just as productive
- "from home" sounds like retreating to a comfort zone, while "via telecommuting" sounds like embracing a new technology or skill
- "from home" sounds like remote workers ought to be performing their tasks from their domicile only, while "via telecommuting" sounds like remote workers can do their work wherever they are
If businesses had adopted "telecommuting" terminology, I believe business leaders would not feel obligated to push back in order to regain productivity. I think it's easier to attack the trend of WFH given the points above. I actually agree with the proposal that WFH is a weak terminology, but had never sat down and thought about it before.
From the perspective of initial adoption, I think it would have happened just as fast. Workers were thrust into remote work arrangements during COVID, and everyone would have quickly gotten the gist of what "telecommuting" means, so it would have been the new buzzword to attract talent in job listings just as "remote" or "work from home" have been. Just without the downsides in CEO perception.
The only problem is that telecommuting is not a new buzzword, it was all the hype in 90s/00s, which is probably reason enough to pick a new word.
Yes and business leaders ate it up. They only pushed back when it was rebranded as “work from home”.
RTOs generally have nothing to do with any of the things they say. They are just layoffs.
You can't argue with them about the effectiveness of remote work. They aren't trying to optimize work. They are trying to fire people.
Working from home doesn't fire people, being more productive and happy doesn't fire people. Your mental well being doesn't have any bearing on how many people they need to fire.
Based on their own gut.
Exactly. It’s less about whether AI can replace certain jobs and more about the fact that companies are making decisions as if it will. That alone reshapes hiring, budgets, and job security
We are still doing scrum-like stuff after all. And they are dragging people back to the office. Decision makers have billions at their disposal to be inefficient with.
I started my own business last year that has happened to go quite well. As I’ve watched the software industry over the last year, all I can think is… “damn, what lucky timing.”
I keep looking for what you claim to be doing. I feel like reality continues to smack me in the face with “no one cares about quality”. I have tried big enterprises. I have tried 8 startups in 18 years. I watch the leaders / founders make the same mistakes over and over.
Anyway - your profile resonates with me. Would love to grab a virtual coffee if you are up for it.
Could you share the mistakes they are making repeatedly?
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.
I've been doubling down on mine as well rather than pursue a more traditional career path and I feel the same way.
Hi, can you please elaborate a bit?
The blog confused me. The author opens with senior leaders but does not distinguish between ic and managers. That is a very important difference and the way they are written is somewhat interchangeable at the start but I don’t think that’s necessarily correct.
Managers and senior ics are both facing unique challenges now. However, they are very different and don’t have a lot in common.
For me, as a senior ic, it’s having the right skills and staying afloat in this challenging environment. For the middle managers, from what I can see, it’s not being redundant as Mark Cuban recently pointed out.
I get why someone would want to tell people this, but I think it fails to be advice, as it describes the current state of affairs without much actual guidance for how to do better in it
Which, to be fair, no one really seems to be able to answer that meaningfully
The real answer is, leaders chase trends, so to keep them satisfied you need to also chase trends.
Some advises can be:
* learn prompt engineering to impress your boss and next employer
* adapt AI IDE at work, of course don’t go for cline or freemium ones, go for max expensive tier of Cursor/Windsurf/v0 etc
* Take some expensive(more the better) courses and workshops on Agentic topics, build some small projects. Justify your expenditure by citing being more well prepared for AI transition and adapting to new paradigm to strategically beat the competition businesses who will be extinct without employees with such trainings
* build some proof of concept projects to convert the smaller trivial projects to use agentic workflow. Then show these to your boss and put these up on github for future reference
* learn to train smaller models on your own internal documents, build a chat interface on top and give access to your boss(trust me, they will be blown away and will sell this to their superior)
* seed fear in your colleagues’ minds by using AI stuff where possible
Think of this AI as a new trend we must adapt to, just like FE moved from jQuery to React. Life and work goes on, just this wave nudges the complacent bunch to finally get out of their comfort zone and learn something new or get left out.
>seed fear in your colleagues’ minds by using AI stuff where possible
You mean make them terrified of debugging your code after you have moved on?
> seed fear in your colleagues’ minds
Jikes
Watch your boss file you for training a model on internal documents without permission
Problem solving and UX are not code dependent. Non-coders and entry level folks are using these tools and confusing the output with solving a problem, a business or user problem. It has made my work more difficult to get bogged down into debates about slop that middle managers have posted and said they've done what I can do. Most of the real world integration of these things has devalued the skills of actual programmers. It's so much more than syntax and loops. It's kind of like people who think they've figured out magic tricks. Ok, but haven't you wondered why that isn't useful in any other context?
The shift in what's valued (moving from team-building and hiring prowess to sheer execution speed and adaptability) has been stark. It's also unsettling to see so many senior folks feeling -left behind- not because they lack skills, but because the rules of the game have changed so quickly...
> Steer away from skills like web development that are clearly getting eaten by LLMs.
There's a slim chance that frontend work runs into Jevons paradox.
Rather than churning out simpler interfaces faster, the complexity will grow.
More 3D sites, MR, etc
> Many people who first entered senior roles in 2010-2020 are finding current roles a lot less fun.
This resonates with me.
I find that the current crop of new tech (AI) produces a lot of cognitive dissonance for me in my day-to-day work.
Most initiatives/projects/whatever around AI seems to be of the "digging your own grave" variety - making tools to replace software engineers.
Definitely not fun.
> decision-makers can remain irrational longer than you can remain solvent
Feels definitely true. I wish ICs had much more agency. Wish there was something actionable even as a small step (which I don't think is there on the article).
Having been laid off due to unclear reasons, can't help but think the same could happen in my next prospective job (if I get one in this market that is) and there's nothing I could do about it.
> managers were generally evaluated in that period based on their ability to hire, retain and motivate teams. The current market doesn’t value those skills particularly highly, but instead prioritizes a different set of skills: working in the details, pushing pace, and navigating the technology transition to foundational models / LLMs. This means many members of the current crop of senior leaders are either worse at the skills they currently need to succeed, or are less motivated by those activities. Either way, they’re having less fun.
Don't geeks enjoy playing with LLMs much more than hiring or any other admin/people/meeting type interaction? They should find dealing with the new wave of AI success a lot of fun, and a lot MORE fun that governance stuff, IMHO.
> Many companies that were stable, durable market leaders are now in tenuous positions because foundational models threaten to erode their advantage.
uh.. which companies are these ?
Chegg?