> what if the most important professional “developer skill” to learn or improve is how to effectively use coding agents?

Well, it's not. There's a small moat around that right now because the UX is still being ironed out, but in a short while able to use coding agents will be the new able to use Excel.

What will remain are the things that already differentiate a good developer from a bad one:

- Able to review the output of coding agents

- Able to guide the architecture of an application

- Able to guide the architecture of a system

- Able to minimize vulnerabilities

- Able to ensure test quality

- Able to interpret business needs

- Able to communicate with stakeholders

> This is going to catch some heat, but what if the most important professional “developer skill” to learn or improve is how to effectively use coding agents?

If it does go as far that way as many seem to expect (or, indeed, want), then most people will be able to do it, there will be a dearth of jobs and many people wanting them so it'll be a race to the bottom for all but the lucky few: development will become a minimum wage job or so close to that it'll make no odds. If I'm earning minimum wage it isn't going to be sat on my own doing someone else's prompting, I'll find a job that involves not sitting along in front of a screen and reclaim programming for hobby time (or just stop doing it at all, I have other hobbies to divide my time between). I dislike (effectively) being a remote worker already, but put up with it for the salary, if the salary goes because “AI” turns it into a race-to-the-bottom job then I'm off.

Conversely: if that doesn't happen then I can continue to do what I want, which is program and not instruct someone else (be it a person I manage or an artificial construct) to program. I'm happy to accept the aid of tools for automation and such, I've written a few of my own, but there is a line past which my interest will just vanish.

The endgame in programming is reducing complexity before the codebase becomes impossible to reason about. This is not a solved problem, and most codebases the LLMs were trained on are either just before that phase transition or well past it.

Complexity is not just a matter of reducing the complexity of the code, it's also a matter of reducing the complexity of the problem. A programmer can do the former alone with the code, but the latter can only be done during a frank discussion with stakeholders.

A vibe coder using an LLM to generate complexity will not be able to tell which complexity to get rid of, and we don't have enough training data of well-curated complexity for LLMs to figure it out yet.

I also remember a similar wave around 10-15 years ago regarding ML tooling and libraries becoming more accessible, more open source releases etc. People whose value add was knowing MATLAB toolboxes and keeping their code private got very afraid when Python numpy, scikit learn and Theano etc came to the forefront. And people started releasing the code with research papers on github. Anyone could just get that working code and start tweaking the equations put different tools and techniques together even if you didn't work in one of those few companies or didn't do an internship at a lab who were in the know.

Or other people who just kept their research dataset private and milked it for years training incrementally better ML models on the same data. Then similar datasets appeared openly and they threw a hissy fit.

Usually there are a million little tricks and oral culture around how to use various datasets, configurations, hyperparameters etc and papers often only gave the high level ideas and math away. But when the code started to become open it freaked out many who felt they won't be able to keep up and just wanted to keep on until retirement by simply guarding their knowledge and skill from getting too known. Many of them were convinced it's going to go away. "Python is just a silly, free language. Serious engineers use Matlab, after all, that's a serious paid product. All the kiddies stacking layers in Theano will just go away, it's just a fad and we will all go back to SVM which has real math backing it up from VC theory." (The Vapnik-Chervonenkis kind, not the venture capital kind.)

I don't want to be too dismissive though. People build up an identity, like the blacksmith of the village back in the day, and just want to keep doing it and build a life on a skill they learn in their youth and then just do it 9 to 5 and focus on family etc. I get it. But wishing it won't make it so.

Talented, skilled people with good intuition and judgements will be needed for a long time but that will still require adapting to changing tools and workflows. But the bulk of the workforce is not that.

Using a coding agent seems quite low skill to me. It’s hard to see it becoming a differentiator. Just look at the number of people who couldn’t code before and are suddenly churning out work to confirm that.

I think your argument is predicated on LLM coding tools providing significant benefit when used effectively. Personally I still think the answer is "not really" if you're doing any kind of interesting work that's not mostly boilerplate code writing all day.

Many of those skills have temporary value before they're incorporated into the models/harnesses

There was a moment we thought JS had won. And then crypto. I personally believed low-level development was done.

Not sure why this would catch heat rationally speaking. It is quite clear in a professional setting effective use of coding agents is the most important skill to develop as an individual developer.

It’s also the most important capability engineering orgs can be working on developing right now.

Software Engineering itself is being disrupted.

I'd offer an edit that the most important skill may be knowing when the agent is wrong.

There's so much hand wringing about people not understanding how LLMs work and not nearly enough hand wringing about people not understanding how computer systems work.

I'd say viewing it as most important is pretty unprofessional. But isn't it the point of this extreme AI push? To replace professional skills with dummy parrots.

I don’t think it could be the most important skill to have. The most common, and the most standardized one for sure, but if coding agents are doing fundamental R&D or running ops then nobody needs skills anyway.

> As it turns out, neural nets “won”

> The people who scoffed at neural nets and never got up to speed not so much.

I get the feeling you don’t know what you’re talking about. LLMs are impressive but what have they “won” exactly? They require millions of dollars of infrastructure to run coming around a decade after their debut, and we’re really having trouble using them for anything all that serious. Now I’m sure in a few decades’ time this comment will read like a silly cynic but I bet that will only be after those old school machine learning losers come back around and start making improvements again.

I've worked for 35ish companies (contract and fulltime), largely on the west coast of the US. I have experienced the lip service, from the vast majority. I have experienced maybe 2 or 3 earnest attempts at growing engineer skills through subsidized admission/travel to talks, tools, or invited instructors.

Every company I worked for didn’t give a shit about my skills. They just wanted to solve the problem in front of them and if they couldn’t then they would hire someone in with the right skills. Improving my skills was seen as a risk as I might leave.

That’s been my experience, too. But now I get a sort of, “I dunno. Maybe don’t use AI on Fridays?”

There doesn’t seem to be a plan for maintaining that culture.

Given the rest of the paragraph, I believe the parent is trying to say that merely improving developer skills is not valuable to the company, not that improving developer skills cannot provide value in terms of improved work product, morale, retention, etc.

You must be lucky then.

The opposite is true in my case - though 1 organization that had a small budget for things like AWS certs. I remember almost everyone who would get those certificates would never really learn anything from it either. They would just take the exams.

We're witnessing a divergence between Coders and Clauders, with the latter dominating the market at a lower cost of labor + subscription fee to the almighty AI providers. Coders may be called in, hopefully with better renumeration, to review and debug the massive amount of code being generated. Either that or they will also be replaced by specially trained/prompted language models doing the review.

In the future Claude will keep a tight ship on dissenters. If your monthly quota doesn't exceed the 10k worth of tokens your employer will be notified and you will be flagged as a "dissenter". Your lease will be cancelled, because who would trust someone ignorant enough to not use LLMs in their daily life, and you'll be vetoed from the field for life, for clanker companies will proclaim that anyone who doesn't use LLM-assisted coding should be culled and so they'll run a tight ship.

And executives will get millions in bonuses for figuring it out, and the remaining programmers, probably one or two, will raise their necks over who's the best prompter and how everyone else was dumber than them for not figuring it out.

> the generated code just annoys me and the agents are too chatty

I’ve eyerolled way less with Codex CLI and the GPT models than with Claude.

There is a deadly game of chicken going on. Junior recruiting already stopped for the most part. Only way this doesn’t end in a catastrophe is if AI becomes genuinely as good as the most skilled developers before we run out of them. Which I doubt very much but don’t find completely impossible.

How many kernel devs does the world need? A dozen or two?

It will be the same with software. AI will be writing and consuming most software. We will be utilizing experiences built on top of that, probably generated in real time for hyper personalization. Every app on your phone will be replaced by one app. (Except maybe games, at least for a short while longer).

Everyone's treating writing code as this reverent thing. No one wrote code 100 years ago. Very few today write assembly. It will become lost because the economic neccesity is gone.

It's the end of an era, but also the beginning of a new one. Building agentic systems is really hard, a hard enough problem that we need a ton of people building those systems. AI hardware devices have barely been registered, we need engineers who can build and integrate all sorts of systems.

Engineering as a discipline will be the last job to be automated, since who do you think is going to build all the worlds automation?

Trust me. All those people do it for the love of doing it, so I don't think they will outsource the jobs to some automation....

I have been coding long before internet and before there were huge demand for software devs..and I would be coding even after there is no demand for the same.

I feel I've upskilled in so many directions (not just "ability to prompt LLMs") since going all in on LLM coding. So many tools, techniques, systems, and new areas of research I'd never have had the time to fully learn in the past.

I have a hard time believing any tenured developer is not actually learning things when using LLMs to build. They make interesting choices that are repeatable (new CLIs I didn't even know existed, writing scripts to churn through tricky data, using specific languages for specific tasks like Go for concurrently working through large numerous tasks, etc.)

Anyone not learning things via LLM coding right now either doesn't care at all about the underlying code/systems, or they had no foundational knowledge or interest in programming to begin with (which is also a valid way to use these tools, but they don't work very well without guidance for too long [yet]).

>But the number will dwindle and we'll ironically be unable to build what our ancestors did, utterly dependent on the AI artifacts to do it for us.

That's only a brief moment in time. We learned it once, we can learn it again if we have to. People will tinker with those things as hobbies and they'll broadcast that out too. Worst case we hobble along until we get better at it. And if we have to hobble along and it's important, someone's going to be paying well for learning all of that stuff from zero, so the motivation will be there.

Why do people worry about a potential, temporary loss of skill?

If a catastrophic failure occurs we will have to return to first principles and re-derive the solutions. Not so bad, probably enlivening even to get to spin up the mind again after a break.

I mean there should be. But there's not. Despite the millions of CS grads produced many people could not reasonably be expected to produce many 'standard' parts of a software stack

I love the perpetual motion machine / thermodynamics analogy.

It kind of feels like companies are being fooled into outsourcing/offshoring their jr. developer level work. Then the companies depend on it because operational inertia is powerful, and will pay as the price keeps going up to cover the perpetual motion lie. Then they look back and realize they're just paying Microsoft for 20 jr. developers but are getting zero benefit from in-house skill development.

This is silly. I can build products in a weekend that would take me a year by myself. I am still necessary 1% of the time for debug, design, and direction and those of not at all a shallow skill. I have some graduate algebra texts on the way my math friend is guiding me through because I have found a publishable result and need to shore up my background before writing the paper...

It's not perpetual motion, it's very real capability, you just have to be able to learn how to use it.

A long-standing truth in martial arts circles has been that you can't advance beyond a certain belt before you teach classes.

It's purely because of the fact that if you can't teach something, you really don't understand it.

And the act of having to simplify and break down a skill to explain it to others improves your knowledge of it.

I haven't heard this benefit for mentors clearly articulated before (probably just missed it), but definitely felt it - I guess it's a deeper version of how writing/other communication forces clarity/organization of thoughts because mentorship conversations are so focused on extracting the why as well as the what.

For the first time in quite a while, I've started reading a challenging, non-computer book ("The New Testament in its World").

I'm trying to decide if my attention span has atrophied, or if I'm just more aware now of my ADD.

Either way, I'm hopeful that my attention span for this kind of reading will grow with practice.

I tried reading Proust's In Search Of Lost Time some time ago, in which the first 10-20 pages are about a guy lying in his bed at night and observing his own thoughts (roughly). And I quickly realised how I was reading the words and even sentences, but couldn't grasp the meaning of them - I couldn't produce a "mental model" or image of what it was about. It was a very humbling experience.

I used to be an avid reader as a child, even as a teenager. That was a long time ago. I'm looking forward to that time when I will have the mental capacity to read long prose again.

I'm pretty sure the -as-a-service stage is only temporary.

The local models are only going to get better, and the improvement curve has to top out eventually. Maybe the cloud models will still give you a few extra percentage points of performance, especially if they're based on data sets that aren't available to the public, but it won't make much difference on most tasks and the local models will have a lot of advantages too.

I agree on the over-reliance part, but I don’t think it’s AI itself .It’s how people choose to use it.

Most people are outsourcing thinking instead of using it to go deeper. The tools aren’t the problem, the default behavior is.

> which seems to have zero introspection as to why we're just going to accept the feudal overlords of technology.

You’ve let them in and given them power in many aspects of your life without even a whimper of resistance. Of course you’ll accept them as your lords.

hoped for something useful in your link, found drivel.

You’re making a lot of assumptions. They could just stop visiting HN. They don’t even need a “plan” or an alternative, they can just stop.

I thought the same as the person you replied to. For me, the solution is to stop coming here as often and instead read traditional literature.

Soon to remove my access entirely to this website.

That attitude is particularly galling. Along with the "lock in now or become part of the permanent underclass".

Dog in the Manger.

I get a feeling from overall anti-AI sentiment online that a lot of people feel they're entitled to 100% of value created by anything even tangentially related to their person, whether that's some intentional contribution or a random brain fart that happened in the vicinity of someone else doing something useful - and then become resentful they're not "getting their share".

There's hardly any other way to read all the proclamations of quitting to do anything because "cognitive dark forest" (itself a butchering of the original idea of "dark forest" across so many orthogonal dimensions in parallel, that it starts to look like a latent space of a transformer model).

There’s definitely a fear of repercussions (I’ve been commenting on this site for over a decade now! Who knows what’s in my history...) but importantly I actually take some pride in many of the comments I write. What drew me to this site originally was how high quality everyone’s perspectives and articulation was, and I suppose I view the writing voice I’ve nurtured here as unique and special to me. It’s not about compensation, I’d just hate to see some future chatbot sound 1/1,000,000th like me I guess? Hard feeling to describe, but I’d rather just not be globbed in and instead express myself in ways that aren’t profitable or feasible to copy.

This sounds like a nice principled stance, but you won't get any traffic with this approach. That's demotivating - to me blogging is a tight balance of exploration, learning, improving and feedback. I'm not able to write without considering how this impacts the reader - removing all readers breaks the process for me.

Yeah, everyone went on "blocking all crawlers" end result being half of internet inaccessible over vpns. Good job, people.

AI makes the entirety of the software engineering profession available to you. All you have to do is ask the right way, and you can build in days what once took months or years.

Decompiling and re-engineering proprietary code has never been easier. You almost don't even need the source code anymore. The object code can be examined by your LLM, and binary patches applied.

Closed source is no longer the moat it was, and so keeping the source code to yourself is only going to hurt you as people pass you over for companies who realize this, and strive to make it easier for your LLM to figure their systems out.

You don't have to. Just like you don't have to support Amazon for web services and file stores.

Or Oracle for databases.

Or Microsoft for operating systems.

Or DEC for computers.

There are perfectly good open source LLMs and agents out there, which are getting better by the day (especially after the recent leak!)

I want to support local models and compute over SaaS models.

I want to support RISC V over Intel.

I want other things too, and on balance, Intel+Anthropic is most compliant with my various preferences, even if they're not perfect.

Was there one for memory managed languages like C# vs self managed like C/C++?

see: purity spiral politics

It’s worse than that, in the linked “I’ve done my research” they make the tired claim that ai hallucinates api calls. Which while true has not been a practical problem since tool calling was added.

I think the position that ai is morally troubling enough that the downsides out way the positives is perfectly defensible. But the entire argument becomes a joke when you can’t accurately catalog the positives.

Amara’s law: “We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run.”

>If it had a generous built in HTTP cache, and instruction to maximise use of the cache, then it could avoid a lot of re-fetching of content, which would help reduce the harms.

While this is a great idea, the harms are somewhat overblown. The big scare number for water consumption includes water used in power generation which itself includes evaporation from hydroelectric power.

I'm giving them a lot more but I assumed people know uncle bob. Like the Open Source Architecture Books, Googles SRE Books, 1:1 mentoring every week.

But yeah there is one person made of teflon. Nothing sticks. And i could tell you that teflon person in every company i worked so far.

I had Claude write me some lyrics about Clankers after that one guy had an AI write a hit piece about him over denying his PR.

Yeah I also keep thinking this. I don't see LLMs reliably producing code that is up to my standards. Granted I have high standards because I do take pride in producing high quality code (in all manner of metrics). A lot of the time the code works, unfortunately only for the most naive, mechanical definition of "works".

This just isn’t true at all, with guidance and guard rails they produce much better code than the average developer does. They are only going to get better.

This is a US-centric take, in Europe, particularly in cities, we walk everywhere.

There is perhaps some relevance to the analogy however, because the US is designed in such a way that makes walking difficult to impossible. I am already seeing this pattern in vibe-coded areas where engineers will just use AI because it's too difficult to parse and edit by hand.

> people did stop walking everywhere.

I didn't. Yesterday I walked 11 km for errands. Today I took a detour when walking to work, a more scenic route with less traffic.

For me walking is not much slower than using public transport (you need to get to it, then from it to the point of your destination), and not much slower than a car (stuck in traffic, finding parking, not to mention the road rage). I'd be faster on a bicycle but I'm not in a hurry and enjoy my walks.

In the US, perhaps, which has had perhaps the bulk of its growth post-automobiles.

across the street, no?

It's also a crime to jog on the railroad tracks.

Major, big big major, not just me either. How is it alarming beyond words? If I said "Im an emt and I just ask the AI everything" now that would be alarming beyond words.

I disagree that this adds anything new to the conversation, but fair enough.

I agree that humans should continue to value various forms of literacy even in the face of AIs that can do everything better than us. I too will continue to dig deeper into tech literacy. There was a Terence Tao paper recently that mentioned we are in a shift similar to the end of heliocentrism. It made clear that Earth is not the center of the universe, but Earth is still deeply valuable and important for humans. Much the same way that AI may supersede our understanding and intellect and make the are limitations more apparent, but our human intellect is still important to humans. Plus, what are you going to do when the price of LLM tokens are through the roof or you get messages like "burn an extra 1,000,000 tokens for a better implementation!".

I get it. I’ve been doing this for 11 years. I use agents everyday at work now and deal with all the benefits and problems of that. The craft is certainly changing and it will take years for everything to shake out and settle. I understand the desire to publicly wax poetic, but nobody actually knows shit about where we will land, so it gets a bit tiresome to see over and over.

> sythansized audio playback

Thats generated audio. It may not be LLM generated but it's not read by a human.

To draw an arbitrary line between _this kind_ of generated content but not _that kind_ is seemingly a matter of perspective and preferences.