Why write code in 2026

https://softwaredoug.com/blog/2026/07/09/write-code

by softwaredoug • 12 days ago

220 303 12 days ago

guyzana• 12 days ago

I found myself working mostly at the requirements and architecture level, but do not give up proper code-review, creating skills along the way that maintain conventions.

olsondv• 11 days ago

TL;DR: Write it so you’re actively involved and not a passive reviewer. Then a sign up link for his course.

vips7L3• 11 days ago

I still exclusively write my code. The quality is higher. I know exactly how it works. It’s more extensible. You don’t have to generate it.

bigstrat2003• 11 days ago

In fact, it's better not to generate it imo. Like you said the quality is higher, and by the time I get done reviewing the LLM's output I haven't really saved time over just doing it myself. LLMs are only useful for things you can verify extremely quickly (like a short script), or for things where you don't care about the quality.

glouwbug• 11 days ago

Turns out you internalize it when you write it and refactor it with iteration

sph• 11 days ago

In fact, not many people know that these days, but a human doing a thing by bashing their head against it, often tends to improve. My hand-written code is my best yet. My breadth of knowledge, wider than ever.

lordnacho2• 11 days ago

But the attraction of LLM code is not that you get quality.

The selling point is that you know have a quality Vs time tradeoff that is a lot better than you used to have.

I can spend 10 seconds typing out a prompt that will generate ok code.

Before a couple of years ago, it might have taken me an hour to type out and debug that code.

vips7L3• 10 days ago

Sure, if you prefer low quality go ahead. Many people have always preferred low quality. Many people prefer to eat junk. I also genuinely believe that time tradeoff doesn’t matter.

Before a couple of years ago, it might have taken me an hour to type out and debug that code.

Are you not running and testing your code?

light_hue_1• 11 days ago

This is too generic. There's some code I need to write like core abstractions that are going to set the pace for everything. Or tricky steps that can look good without actually working well.

Then there's the mass. I don't need that anymore. The mountains of boilerplate, etc.

I write little islands which need high judgement that are then connected by the obvious goo.

jdthedisciple• 11 days ago

this is the way

sublinear2• 11 days ago

The boilerplate was always boilerplate though. You never needed to write it to already have that code in your project, so I'm confused by what you mean.

Generating boilerplate is strictly inferior than something already written and tested by the authors of the tools. You will eventually have to make slight adjustments to it, and those decisions can be just as impactful as your "high judgment" code. Those decisions are what actually enable your high judgment code to stay clean and straightforward.

Poor decisions in code architecture are some of the biggest blunders of all. Once you have begun to fill in the blanks on some boilerplate code, it ceases to remain boilerplate code. If you let AI make those adjustments, you will eventually blunder the codebase in precisely this way. You'll first recognize it when your high judgment code seems too verbose. You'll then soon realize some things are impossible without adjusting the boilerplate you started off with. Then the AI will fail to grasp what you want and you'll have to manually untangle a lot of the slop that you let grow out of control. Good luck with that.

simonask• 11 days ago

"Why cook food in 2026 [while McDonald's exists]?"

gb2d_hn• 11 days ago

I think fragility is the key reason i intervene in llm code too. Good article.

jdw643• 11 days ago

Recently, even a tourist lost to OAI's model in competitive coding. To be honest, I haven't been able to beat AI at coding since around 5.2. People often say 'AI can't write good code,' but in reality, the quality of AI's output is layered depending on the level of the prompt input. The deeper the prompt, the better the code actually gets.

Usually, when people say AI code is terrible, it's because they either don't understand the theory well but have grown through hands-on experience and can't explain things properly to the AI, or they don't know what they don't know. Or there are the very few who are just far better coders than AI. Some people will say they're among the rare few who can write better code than AI, and for some that may be true. But in my experience, the vast majority are not. Even from my perspective as a beginner, I could see flaws when I looked at their git code. It's a metacognition problem.

Realistically speaking, at the script level, it's quite common to see AI surpass human programmers as you increase the input level. You might disagree, but that's probably because you're a specialist in that field, deeply immersed in a very narrow area—it only holds true in that limited scope. In the general domain, most people would agree that AI writes code well.

Human programmers don't know much outside their own domain. But AI, while it loses in very narrow specialist areas, writes better code than humans across the broader range. It loses in the 1% zone (the expert's domain), but wins in the other 99%. Usually, when that's the case, you have two choices: become the 1%, or learn how to use AI.

Since I'm a non-native English speaker, I'm already at a disadvantage compared to native speakers in programming skills, so I chose the latter. But I still code. Not for any other reason—if I don't maintain at least some typing muscle, I won't be able to review AI code properly.

That's why I think coding is essential. Even if I can't understand the entirety of AI's output, I still need to understand the core business logic. At the very least, the core logic requires human understanding, so coding is necessary.

nmehner3• 11 days ago

"The deeper the prompt, the better the code actually gets."

.... and in the and you end up with a very deep prompt that exactly specifies the behavior. This is what a programming language is.

I'd rather describe a data structure in a language designed for this task, than a prompt the might be interpreted in many different ways.

rossant• 11 days ago

I don't write code anymore, because AI writes better code than me. I could write code, but the next AI would find 10 ways to make it better and more consistent with the rest of the AI-generated codebase. So I just let it write all of it. However, I inspect it all carefully and I constantly asks it to reflect on the code quality, to refactor, to reorganize, to make the code as good as possible. The end result is code that is much better than anything I could have written myself.

And I should mention that I have 30+ years of programming experience.

jdw643• 11 days ago

To be honest, as you know, background knowledge is extremely important in programming. As you move into complex domains, the specifications multiply. So as a domain gets more complex, there comes a point where it exceeds my cognitive capacity. And that's when AI surpasses me and writes code I can't keep up with.

Usually, it produces code that would take three or four humans days to figure out—in just 20 minutes.

Even the professors and PhDs who hire me all use AI. Honestly, they hold PhDs and professorships, which puts them in a league I can't even touch—and even they use it. AI just does it really well.

Honestly, I learned from your book, 'rossant'—I never expected a programmer like you to say something like that. I thought my perspective was because I'm only an intermediate-level programmer. But you're in the 1% expert category I mentioned

nevertoolate• 11 days ago

Can you explain what you are working on?

I’ve stopped using llms to generate architecture, which i design and write myself and let the machine pattern match the gaps. I also use it to review issues which I lot of the times push back against.

I’m working on a stateful application sitting on top of a data warehouse and have to implement a stream of messy half defined feature requests and navigate on top of an ever changing infrastructure layer. LLMs rarely get the infra layer even if it is written as code and have hard time grasping how to deal with tech debt, when and how to re-architecture parts of the stack or even implement stuff based on a detailed openspec design.

zelphirkalt6• 10 days ago

How do you improve, if you don't write code? How do you aim to close that gap, that is the 10 different ways of improving your code? And if you don't aim to improve, how do you deem yourself capable of even reviewing AI code in say 3 to 5 years, when your code writing skill has fully atrophied?

newsoftheday• 10 days ago

If AI is generating better code than you can, that does say a lot. I've tried various AI's available and outside of being a better Google or a fast reference for Stack Overflow; LLM's do not generate better code nor better running code.

zelphirkalt6• 10 days ago

In my experience AI often overlooks generalizations of ideas iteratively arrived at. I need to give it the idea, that something could be generalized and nudge it, to arrive at the solution.

I imagine at competitive coding the goal is quite clear, but in a real world project, the goal is not always so clear, and especially in hobby projects the ideas and goals are not that clear. I get inspiration on how to improve my project or its usability, not the LLM. I instruct it to do something a specific way, because it doesn't do anything on its own, and I need to tell it what to generalize, which it failed to see, because it didn't consider a simplification which is technically less precise, but due to user context and human nature doesn't matter (in this case it was interpreting "now" to mean the current second, which is a small time range, instead of a mere point in time).

So it still takes a ton of hand holding in a more open project. I imagine, one could also code it up in the same amount of time. But it is good for generating tons of test cases. Though one will have to review those, and impose a test style on them, give examples and so on.

jdw643• 10 days ago

I agree. In fact, that's precisely one of the hardest parts of programming. Your thinking aligns with mine. I do a lot of equipment programming for factory delivery. I've even delivered an MES system before, to be precise, it was migrating a legacy MES to a modern version.

Beyond hobby projects, most clients often don't really know what they want. And that's generally what we call domain modeling. This is definitely an area where AI is weak. As you know, it mainly pulls from generic patterns.

When there are specific constraints, AI struggles with core business logic. And as you said, it's also weak at choosing the right direction or the goal to pursue. But as you also know, 80% of programming is built on what others have already created. Originality is only about 20%. And in that 80%, AI is absolutely dominant. I agree with you and I've upvoted your comment.

I really like your perspective

mcrk• 11 days ago

Do ppl think that programmers just write code from sratch each time..?!

Even without AI I barely write code. 95% of time are spend setting up integrations, configs, copying & adjusting code from previous projects.

estetlinus• 11 days ago

+1, I don’t understand who these greenfielders are. Either I wait on the CI to finish, or I’m in a meeting.

danielbln• 10 days ago

And that sort of yak shaving is something LLMs are great at.

softwaredoug16• 10 days ago

I’m old enough to remember coders being made fun of for doing copy-pasting from stackoverflow all day.

jonplackett• 11 days ago

Prediction: in 2027 a coding agent will read this as inspiration for why it should code.

nmehner3• 11 days ago

"It’s about attention and understanding. To keep my attention, I must go beyond ‘read code’ like a passive observer of agents from afar. To really connect with the architecture of the system, it helps to truly experience the code"

I guess the funny answer that is behind this sentence is: You have to train your own mental model. We always argue about code in a very abstract and logical manner. But when coding the subconsciousness makes most of the decision ("this just feels right"). But for this to work you have to train it. And this does only work in a very limited way with code reviews or reading documentation. It requires repetition and deep focus.

When there is an issue in production with this mental model you will be able to point to the cause of an error message instantly. With generated code you'll search for a long time with your slow, conscious part of the brain.

For LLMs to be really helpful, they have to take over complete maintenance of the code. So you can treat them like an external library: Just assume it works. Otherwise this will always be problematic.

kqr• 11 days ago

With generated code you'll search for a long time

The observability people will claim that if the dynamic runtime behaviour of your system makes it hard to find the source of a behaviour, your system must be made more transparent and observable. They would also claim this was always the case -- we should never have relied on people's mental models being amazing because people move around.

(I don't know yet where I stand on this but I'm trying to learn more.)

hack1312• 11 days ago

The observability people are correct. It’s not either-or though.

nmehner3• 11 days ago

If it was only "my" system without any integrations, I might agree.

But currently e.g. I am working on an MES/Scada layer that integrates data from a load of different machines in a factory. These machines are from China, Korea, Germany, Sweden ... Upwards there is an ERP integration (and some other systems).

Sometimes machines are updated and suddenly behave differently. Giving error messages in Chinese.

The ERP has the nasty behavior of returning error messages where it is not clear whether the actual processing actually happened or not. There are some heuristics on parsing the error messages, but these also change with new versions.

Sometimes one machine overloads cloud infrastructure and completely unrelated functionality fails.

Sometimes the on-premise network stops working for whatever reason and data is lost.

Sometimes operators do not understand a perfectly valid error message like: "The batch you loaded into input position XY has expired on XZ and cannot be used for production": "But we have been told to use it..."

So when you get called out at night, because the production line stopped and "MES is displaying an error message", it is mostly about finding out what integration failed and who else to wake up. Getting this right is very much appreciated by your colleagues.

And this is where you need a mental model of how things are connected, what error message happens because of what external causes etc.

Observability can only work perfectly for known problems. In a complex system for unexpected problem you can either provide too much data, so analyzing it and finding the relevant part becomes really hard, or too little data which makes finding the issue impossible.

There are so many companies claiming to provide the perfect observability solution and there are certainly solutions that help. But it is all very far from perfect.

Not relying on people is managers wet dream. And for a lot of people it might be true that they can be easily replaced. But for complex systems there are always some key people that you cannot replace without causing issues.

jurgenburgen2• 11 days ago

For LLMs to be really helpful, they have to take over complete maintenance of the code. So you can treat them like an external library: Just assume it works.

We already tried this with humans. It works so poorly that it got the derogatory name “ivory tower architect”. It usually results in theoretical designs that are unworkable in the actual system, implementation teams (or LLMs) that work around the architecture and a lot of slowing down of velocity as the architect and implementers argue past each other.

zelphirkalt6• 11 days ago

This happens when the architect is out of touch. If the architect themselves works on the code, writes code, deals with the imposed restrictions, then the chances of that happening is much lower. Assuming, that they are a good architect.

feverzsj• 11 days ago

Unless you want some unmaintainable shitty sloppy app.

dlvhdr• 11 days ago

lol what a slopper

prymitive• 11 days ago

I need to write code because otherwise LLMs will write too much code, it’s only when you fully understand the problem you can generalise it enough to not end up with 10k lines and 5 abstraction layers for “hello world”. LLMs are token predictors, so all solutions are you tokens, the more problems to solve == the more tokens (code) to output.

h2aichat2• 11 days ago

If tokens are the problem, SDD is the solution

TacticalCoder2• 10 days ago

I need to write code because otherwise LLMs will write too much code, ...

I second that and I can give an example that happened to me yesterday with a totally SOTA model (a US, not Chinese model).

I needed to display an information on the client-side. Something trivial. I ask the LLM to do it. The thing went onto a rampage: it somehow found a way to pass the information from the server to the client during the initial handshake (already: why, just why?). Modifying both server-side code and client-side code. And it worked.

To an unsuspecting programmer/tester (or automated test)/user: the info is there, what was asked has been done. So it's perfect, flawless LLM victory right?

Except none of that sloppy-pasta was necessary: the info was already available on the client-side and was a one-line change, purely client-side.

These thing shall definitely, as of 2026, write way too much code.

And btw the companies selling metered tokens have a very serious incentive to produce the most complicated, rube-goldberg, solutions that use as many tokens as possible, while still kinda solving the problem.

That way not only you consume tokens to produce the code, but later on you consume tokens when working on that code (which btw is a guaranteed thing: for the LLM just introduced new bugs in that gargantic amount of crap it output).

Funnily enough the very same people who made fun of copy-pasta happen to be in love with sloppy-pasta. Go figure.

softwaredoug16• 10 days ago

LLMs love to defensively wrap code instead of thinking holistically about the big picture. That creates a lot of bloat.

A human coder might OTOH follow the Boy Scout rule and clean up as they go.

bigmattystyles• 10 days ago

That’s why even though 99% of my work is C#, llms have made it so I can finally call myself a low-level programmer, which I’ve always aspired to. I didn’t even have to do anything.

supriyo-biswas• 10 days ago

So much this, the other day I wanted to set up a project running in K8s similar to our other modules at work, and it he thing ended up writing unit tests for a hello world implementation.

krackers• 10 days ago

it’s only when you fully understand the problem you can generalize

Peter Naur explained this decades ago

Peter Naur argues that programming is fundamentally a human activity of building a mental "theory" - a deep conceptual insight into how a system's parts match the real-world problem it solves. He rejects the prevailing view that programming is merely the mechanical production of source code, specifications, and documentation. Instead, Naur posits that the true product of programming is the shared mental model held in the minds of the developers who built it.

As a human you're the one with the problem you want code to solve, so it's worth having an understanding the problem. Otherwise you risk an X/Y situation, where the LLM ends up solving a problem that may not actually satisfy what you need.

I think what LLMs allow you to do is better abstract away everything that's _not_ essential to the problem you care about, in the same way that libraries or any higher-level programming language does. Ultimately there's still a "core" of the problem that needs to be expressed formally though. When you see people "vibe coding" by prompting the LLM to add constraints at a time until they reach their desired end-goal, this is ultimately "programming" in a sloppy, non-formal way. Better to get the LLM to write everything else _surrounding_ the problem, so you can write and understand the core yourself.

balder19914• 9 days ago

Basically, I’d say the LLM doesn’t have a “theory” of anything that wasn’t in its training. It’ll always treat your project as if it was reading a book for the first time.

As an example, if you chat with an LLM it can sort of explain concepts it learned in its training, because it created some internal representation of them. However it’ll never be able to explain things about your project unless you tell it (then it can simply repeat it, which is the same RAG does, the LLM is just spitting it out without any deep understanding of it).

You can try to cram as much context to it as possible and overload it with extra information, or you can understand this difference and separate a task that you know the LLM can handle because you’ll be able to leverage its knowledge and judge the final work yourself.

But this distinction needs to be more clear, I think. The LLM doesn’t have any deep understanding of anything you’re creaming into the context window the same way it does with concepts it learned during training from millions of examples and building some internal model of the concepts and their relationships.

goodness4all• 11 days ago

I always hated writing code but loved debugging. LLM super charges systems thinkers & auditors, it’s just a different process and no different than copy and paste from stack overflow. It all comes down to the architecture design and LLM just exposes how bad people are at designing dynamic architectures.

girvo3• 11 days ago

and no different than copy and paste from stack overflow

This isn't really the point of your comment, and for that I apologise, but: not all of us did that. For many good reasons, too.

pydry2• 10 days ago

Yeah, the more I hear about people writing "boilerplate" or "copy pasting" code faster using LLMs the more I think it's mainly a tool for letting you write brittle, buggy code, faster.

monk_grilla• 10 days ago

not all of us did that. For many good reasons, too.

This isn't really the point of your comment, and for that I apologise, but I still haven't gotten used to speaking about what we "used to do" in the past tense, as if we are in a post-programming world...

We are already starting to speak of the habits we used to have (or not have), how things used to be done back in the day (1-2 years ago).

I don't think you're wrong to do so. I find myself saying it sometimes too. Just an observation about the weird world we find ourselves in.

imtringued• 10 days ago

I'm not sure this is a good combination?

I mean you're basically saying it is a good thing if the LLM messes up so you have a reason to debug the code.

TacticalCoder2• 10 days ago

... and no different than copy and paste from stack overflow.

It's even got a name: sloppy-pasta.

leptons• 10 days ago

architecture design and LLM just exposes how bad people are at designing dynamic architectures

Speak for yourself. A lot of people have great abilities at designing "dynamic architectures" and anything else an LLM is used for. It sounds like you don't realize that an LLM is only capable of what it does because it was trained on human-written code.

sublinear2• 11 days ago

If we’re building a software factory, details matter. The details that establish architectural patterns. Down to algorithms and performance. Agents push us to evaluate, measure, and guard. They’ve made it cool to add CI into side projects early, not as an afterthought. That’s massive improvement to the state of software.

Why are you building a software factory though, and why weren't you immediately adding CI to every project?

It’s our job to build the software factory - not just the software. Software engineers maintain the assembly line allowing anyone to prompt for a change and ship immediately.

Again, why? Where are you working where this is considered a good idea? This would mean that the software engineers are not just being completely kicked out of all business decisions, but asked to build a moat that ensures they stay on the other side of it.

Any business that intentionally devalues the insights gained through implementation will eventually starve itself to death by making too many passive thoughtless moves. No insight will ever be gained just spot checking AI. Is their intention really just to make tiny amounts of profit while riding the thing into the ground? Crabs in a bucket, man.

cresting• 11 days ago

AI is a tool. Learn how to use it!

Interesting article btw

saghm• 11 days ago

AI is a tool. Learn how to use it!

If you think that everyone agrees on the "correct" way to use it, you're mistaken. If you think that your way is the best possible way to use it, you're arrogant. And if you think that the way you think is correct is obvious and that everyone should already know that's the right way, you're delusional.

h2aichat2• 11 days ago

It seems to me that AI won the code Battle and that humans are just trying to justify the defeat. I will relax and wait for the Next AI generation to see how it fixed its problems. May be, everything will be ok.

ataru• 11 days ago

I've got a coin that answers questions. You have to give it a heads or tails query, then flip the coin, and it returns an answer. It's incredible. Now, it doesn't get the right answer every single time, but we're all learning how to use the new coin technology, and this is only the first generation of coin. The next model of coin is going to be even better. Soon we're not going to need humans any more, for any question we have, we'll be able to use the coin.

yard2010• 11 days ago

I have a coin that can tell you whether a program would halt or not. But it's not always right. I think it's a coin like you have? Still trying to figure out how to use it to prove that p=np.

JackSlateur• 10 days ago

Even a broken clock is right twice a day :)

invader• 10 days ago

So, the developers have finally found their Silver Bullet?

I've seen so many of these already. It would be hilarious to see Brooks proving right once again.

mikkolaakkonen• 10 days ago

The software factory is exactly what I'm building. The world is changing, we can either be the ones changing it or be forced to change afterwards.

fernandotakai• 10 days ago

i write code because i love it. it's something that makes me genuinely happy, so why would i give that up?

jayknight• 10 days ago

Exactly this. I got into this field because designing programs and writing code is enjoyable. I'm probably behind on using AI and need to get more up to speed, but I never want to stop coding by hand.

DaiPlusPlus5• 10 days ago

I'm probably behind on using AI and need to get more up to speed

Same.

My difficulty is that for the past 8 years I've been working for (tiiiiny) SaaS business where I don't have anyone I can simply ask in-person "hey, can you show me how to 'do' all this newfangled AI agentic team coding?"; so my only direct-exposure is with the painful Copilot sidebar chat, which I now find myself allergic to.

So let's see elsewhere: while searching online for some (reputable) "agentic coding courses" my results are for the same kind of people who used to run those dodgy coding-camps from 10 years ago. I'm having difficulty finding resources for practicing SWEs like myself wanting a continuing-professional-development course experience, not a get-rich-by-buying-my-course video library from a contemptable AI booster

Even more surprisingly, my local major university (UW.edu) doesn't seem to offer any certificate courses for getting into agentic development either[1] despite offering courses on C++, Six Sigma, and actual ML/AI courses. It's maddening. I can't be the only one with this problem...

[1] https://www.pce.uw.edu/search?type=certificate&programType=c...

ivanjermakov• 10 days ago

There is magic in telling computer do something and seeing it zap through it billions of times faster than by any other means.

bluefirebrand2• 10 days ago

That doesn't feel like magic to me, it feels like cheating. It feels miserable and demoralizing.

And then it feels like a chore slogging through whatever it produced to verify it is correct.

okanat2• 10 days ago

If you're also happy getting paid for it, then the company will just stop paying you. If you rely on such income to have a visa, you'll 100% sure to accept that you're forced into this and you will give up coding, or else.

bananaboy• 10 days ago

100% agree. I don't understand why there is pushback against this.

kzzzznot• 10 days ago

Because professional development is not just for fun

slopinthebag• 10 days ago

Seems like there’s broadly two ways to use LLMs for coding - either as a way to generate the same code you would have written but faster, or as an opaque program-generator where you have no idea what the code is doing. One of these methods results in roughly the same amount of understanding and the other one radically less.

avaer4• 10 days ago

For example, have you ever seen an agent follow the boy scout rule? Where they leave code better than they found it? And would you WANT them to try to do this?

Yes, it's in the rules; run profiles, check code coverage, do a critical review, post the report and follow up tasks. 90% of people I've worked with did not follow these boy scout rules nearly as well as today's frontier LLMs.

Is the author implying this is bad?

softwaredoug16• 10 days ago

That quote is the lead in to an example I talk about after this quote illustrates what I often see.

Agents bias to making the current change as safely as possible. I had a situation in a previous codebase where one morning, pre-caffeinated, my meat brain mentioned using browser local storage. So some random state was managed in local storage. Everything else through a backend database. When I looked at the code, the amount of wrapping and indirection to preserve this idiotic human mistake probably tripled the LoC. Agents can amplify our one-off bad decisions by being so conservative.

You can of course solve this many ways. And many of boils down to just how a particular humans brain works. Some will solve this by not reading code. Some will read / write code.

Whatever works for you is great. But many there is upside to the precision of not having code intermediated through the LLM for many.

avaer4• 10 days ago

Right, but this just seems like underspecification. In my experience as both a team leader and an "agentic engineer" (ugh), I try to blame myself for the lack of clarity of my asks, rather than the person/agent for making the "wrong" choice.

I'm sure plenty of meat humans out there would make the same mistake (sorry, you said to use local storage boss!). You might give them a scolding. And maybe document that policy. Maybe in a markdown file for the next person. IME the latest models are significantly better than the median engineer at following this feedback.

I don't think it's fruitful to blame the LLM any more than it is to blame someone working under you.

In fact I would say this is an excellent example of how engineering does NOT fundamentally change in the era of AI.

conqrr• 10 days ago

All this debate around use LLM or not is tiring and just black and white thinking.

Can I use agents to code a SWE project? yes, with nuances.

Can I write code for a SWE project? yes, with nuances.

Its more options now, I'll write code about projects I deeply care and will use llm at work where its shared slop and forced usage.

majorbugger2• 10 days ago

Why is this even a legit question? I need to keep writing code to stay relevant, not to forget my craft, be able to review code... So many reasons. AI doesn't change a thing.

avaer4• 10 days ago

Before my time ppl mostly did things in asm, I bet the vast majority of people reading this have never touched assembly and will never have any reason to. This is quickly becoming true of most "code". AI has changed that.

One way to "stay relevant" would be to admit that.

softwaredoug16• 10 days ago

Yet as a C developer for 15 years I frequently looked at asm and on occasion even wrote a little.

And that is a far stronger abstraction than LLMs :)

majorbugger2• 10 days ago

I have also never used punch cards, what does it prove?

deadbabe5• 10 days ago

assembly is compiled deterministically so you don't really need to look at it, LLMs though can write a variety of things at random based on the prompt. It is not the same.

cozzyd• 10 days ago

How can you evaluate what your compiler is doing without looking at the assembly? The many users of godbolt suggest it's pretty common.

pjmlp• 10 days ago

I write code all the time I can, outside the KPI metrics that everyone is being pushed to, I only care about AI for smarter code completion.

minimaxir2• 10 days ago

Note as some may be confused by the "1 hour ago" with comments older than that: this submission was rescued by dang when a previous discussion existed: https://news.ycombinator.com/item?id=48883341

fwiw I think the rationale behind it is counterproductive because the only difference between a OP submitting their article link and someone else submitting their article link is internet points.

softwaredoug16• 10 days ago

I was fairly confused myself as the author :)

This was actually my original submission last week. There was a front page submission last night from someone else (hence the comments). Then my old post got re-upped just now (1 hr ago)

mrweasel• 10 days ago

Apparently it's not obvious to everyone, but if you can't write code, you can't review it. I do know people, and companies, that says: "So what, we ask Claude to write the code, Codex will then do the review". The thing that then strikes me as odd is that they still ask for the code in Python, Java, or some other high level language.... Why? Just ask Claude to dump out assembly, or a compiled binary, but no, they don't trust the LLM that much. They still want to be able to read the code. So they need developers that can read, debug and reason about the code, yet they don't want to give them the training that's required to do this?

ryandvm2• 10 days ago

They don't have Claude write assembly because there is no training corpus on people making CRUD apps in assembly.

I'm as hateful of LLMs hollowing out the job market as the next guy, but the reality is the frontier LLMs are really good at writing anything that's been done and documented on the Internet a million times and unfortunately most of what software devs have been doing the last couple decades is shitting out cookie cutter CRUD apps.

I have my doubts about whether the state of the industry is going to advance as long as we're having LLMs do all the creation, but that's another diatribe.

deadbabe5• 10 days ago

What's there to advance to?

Without a revolutionary new platform to build apps on that no one has ever developed for before, there is basically no reason to believe there is any software left that has some business or economic value that hasn't already been written.

lp4v4n• 10 days ago

They don't have Claude write assembly because there is no training corpus on people making CRUD apps in assembly.

I'm disputing this. You can have a training corpus in assembly as big as any other language: just feed the compiled result(in assembly) of the CRUD apps to the LLMs.

cactusplant73742• 10 days ago

It's still possible to make CRUD apps in assembly with an AI agent but it would be a research project.

dehrmann2• 10 days ago

They don't have Claude write assembly because there is no training corpus on people making CRUD apps in assembly.

I suspect that despite its translation abilities, this is true, but I'd like to see it do things in languages that are more or less appropriate for tasks to see how much the training corpus matters vs. its ability to translate. Assembly is a bit of an extreme example because you're either writing it as close to C as possible (C is essentially portable assembly) or you're writing complex, unreviewable code that happens to work. And who know if it's been trained on register allocation, or resorts to doing everything on the stack because it works.

ekidd3• 10 days ago

Claude is perfectly capable of writing assembly. Here's a working (basic) Prolog interpreter that Claude Fable 5 wrote in WebAssembly in 61 minutes for $16.75 in token costs: https://github.com/emk/fable-wasm-prolog/blob/main/prolog.wa...

WebAssembly is slightly easier than real assembly, but here Fable used WASM GC extensions, which are poorly documented and not yet super common.

Fable didn't even need to debug it; I believe essentially all the assembly worked correctly on the first try.

I have feelings about this, but I'm not pretending it isn't real.

Salgat3• 10 days ago

LLMs are perfectly capable of translating between programming languages at this point. The main bottleneck for them is logic, not language.

coderatlarge2• 9 days ago

couldn’t the frontier labs simply compile their existing source code training data and have an assembly corpus to train on?

wqaatwt• 9 days ago

LLMs are designed to imitate humans not compilers. Hardly anyone is capable of writing modern optimized Assembly code by hand outside of a few snippets here and there (not in a reasonable amount of time at least)

dana321• 10 days ago

I have a few personal projects, i let codex do all the code - i do the thinking and testing.

One time, something didn't work as expected - its the first time it happened with this project. I read through the section of code and it was perfectly readable and well-written.

Turned out a plugin wasn't effecting the audio, so i just got it to pad some blank audio onto the beginning before processing it, then remove it at the end of the process. That fixed the issue, there was nothing wrong with the code but my ability to think laterally is what made it work.

We're getting to the stage where you can just ask them to write code and they will do what you want, and it writes good code. Its up to you to test everything beyond the internal tests it writes.

softwaredoug16• 10 days ago

I’m finding it all boils down to cognitive differences.

Some people find code easier to read than the English description. It’s more precise and many experienced devs can scan it and know what’s happening

Many other people can’t read code. Or they find English easier to read than code.

Thats not a knock on anyone. Maybe the latter will rule the world because the former focuses too much on irrelevant details. Or maybe me there are just different types of problems that need differing levels of attention to detail.

rawling• 10 days ago

Sure, read the English description.

How can you be sure that's what the code the LLM wrote actually does?

dgroshev• 10 days ago

Some heart surgeons might only be able to explain to the nurses their ideas on how to carry out the surgery, but are they still heart surgeons?

pythonplayer123• 10 days ago

I wonder how LLMs could be compared to compilers. I personally think the nondeterministic behavior of LLMs are the biggest distinguisher.

t435627• 9 days ago

The code tells you HOW, the English should be telling you WHY. Both are usually needed IMO. Even a tiny bit of "why" can be extremely helpful to understanding in my experience. I don't want generated AI garbage that merely describes the code - I want the reason the whole thing exists and what was wanted by the person who wrote it.

BerislavLopac• 10 days ago

but no, they don't trust the LLM that much

Yet...

mochapwns• 10 days ago

Pretty sure Casey Muratori and Demetri Spanos cover why in one of their videos online.

Less about “trusting” the llm and more about how complex it is to work with binaries due to machine code being different per machine and hard to interpret the context of the code as well as offsets.

In that sense because high level languages come with the ability to add context to what code does. It’s like the understanding a human has when given decompiled C code ghidra gives you vs C source code a developer wrote.

Also the compiler helps the llm write “compiled / working code”, if it just spat out machine code it most likely not even run at all.

But yea generally if you can’t write code at all, reviewing it is even harder.

notnullorvoid• 10 days ago

No defense for not writing or reading code if want to call yourself a software engineer or programmer.

However I do think there is reason to use Java or Python (as much as I loathe both) they have GC, and it'd be a lot easier for AI to fuck up memory safety in something like assembly or C.

hirvi742• 10 days ago

I concur.

One has to program computers to be a computer programmer. If one just prompts LLMs, they are a software prompter. I think both can fit under the title of a software developer or perhaps even software engineer.

whattheheckheck2• 10 days ago

Ask the ai what the game theory is for training employees... the Nash equilibrium is under training and self funded certification/training for devs in low trust environments.

lelanthran8• 10 days ago

Apparently it's not obvious to everyone, but if you can't write code, you can't review it.

There's more to it than that: writing is thinking. If you stop writing code, you aren't thinking anymore.

Many argue that they're now thinking at a higher level (maybe they weren't before?), but, guess what, that high-level design can be done better by the LLM than by you anyway. It's only temporary.

enraged_camel• 10 days ago

> There's more to it than that: writing is thinking. If you stop writing code, you aren't thinking anymore.

Humans have been thinking long before writing was invented. Why is code special?

mewpmewp29• 9 days ago

I think writing is summarizing your thoughts outside of thinking. Thinking happens at least for me before I write. I know what I want to do before I write, and writing is just one medium to get it out there. If there was a faster way, to get my thoughts there I would use that.

dzonga• 10 days ago

just to add to your excellent observation

by writing code by hand - you're the author & editor at the same time.

if you're skilled enough - you quickly get to the desired state vs the llm which while might produce a lot of code - but it likely won't give the end state you desire.

an analogy - Jason Fried gave - producing software by llm's is like bragging you're a photographer by pressing the shutter button on an automatic camera.

while the art of photography - is about producing the single perfect photo - that communicates the photographers intent (what they want the world to see & experience).

likewise in software - what we make should be deliberate.

chewz• 8 days ago

Just so you know, most people nowadays can create decent pictures or even movies with smartphone. Not automatic camera, not polaroid, not Polaroid camera, not analog Canon FD, not cardbox camera.

Where will you put a line between photography and pressing button?

My point being - tools change with time.

nojito• 10 days ago

if you can't write code, you can't review it.

I don't write code anymore and I doubt I ever will ever again.

On the flipside I review exponentially more code than ever before.

Just ask Claude to dump out assembly, or a compiled binary, but no, they don't trust the LLM that much

It's not "not trusting" the llm its that the llm has been undergoing reinforcement learning is on coding. Plus generating assembly is extremely token inefficient.

Salgat3• 10 days ago

The difference is that you already learned how to write code. New devs that go straight to genai are missing that.

fuzztester4• 10 days ago

dump out assembly?

aargh! haalp!

Which rock are you living under these days.

Nowadays everything is IR or MLIR ... or AIR ...

whoops, i may have skipped a few generations. hard to keep up with the dynamic pace these days. got a job to save. sorry suh.

mumble javascript mumble framework of the half-week ...

walks off muttering

t435627• 9 days ago

No need for IRs if LLMs are all powerful. Just tell them to generate x86 and ARM and let them get on with it.

satvikpendem4• 10 days ago

Just ask Claude to dump out assembly, or a compiled binary, but no, they don't trust the LLM that much

No, people do advocate for this. It may simply not be as portable however as something that is high level able to be compiled to assembly for many machines.

t435627• 9 days ago

It's the logical outcome of believing that human skills aren't important and that you can "think at a higher level". You can't spend all your time thinking at a higher level if you cannot fully trust the output and the assembler argument is just taking the thing to an extreme to make that point.

zx8080• 10 days ago

Apparently it's not obvious to everyone, but if you can't write code, you can't review it.

Why review it at all? The trend is to vibe code everything with agent harnesses and tokenmaxxxing.

byzantinegene2• 10 days ago

churning out assembly code would cost far more in tokens, wouldn't make financial sense for the improved performance which doens't matter that much for most use cases.

lazyasciiart• 10 days ago

This isn’t obvious at all. Editors can evaluate and improve the work of writers even without being bestselling novelists themselves. Richard Williams coached his girls to world championships without winning one himself. Roger Ebert never even made a movie.

asdff2• 10 days ago

No one gets hurt or dies when roger ebert whiffs on a movie review. Now imagine I tell you I've built a bridge. I have no idea how to perform the necessary calculations. I have no idea how to verify the necessary calculations. But, I've built you a bridge. It kind of looks like a bridge. Will you drive across it?

Not all software is mission critical. But some software is.

streetfighter64• 9 days ago

First of all, obviously there's more training data on high level languages than assembly / compiled binaries. Secondly, Python, Java or even C is portable to another device. You know, one of the main points of high level languages: that you don't have to rewrite your app from scratch each time you want to change the machine it runs on.

Thirdly, compilers also do type checking and other static analysis and dynamic checks (array length etc). So it's not only got more guardrails against "mistakes" by the LLM, but it's also most likely "easier" for the LLM to "reason" about (in the sense that LLMs can reason).

There's no intrinsic value to having humans read the code, so as soon as LLMs are good enough to work on their own, companies will no longer need to keep developers who can read code as a backup solution.

rdksu• 10 days ago

exactly how many times do you plan on posting this here

minimaxir2• 10 days ago

https://news.ycombinator.com/item?id=48883660

TrackerFF• 10 days ago

If we look at the progress made from ChatGPT 3.5 (Nov 2022) and up to today...shoot, I'm really starting to wonder if we'll even be reviewing code in 4 years.

And I'm not saying this as some sort of AI maximalist. If progress keeps up, I seriously doubt software engineering and development will, as we know it today, will be a thing in the next 5-10 years. Maybe humans will be left with designing the UI, but everything else will be abstracted away and AI will be doing all the actual work behind the scenes.

softwaredoug16• 10 days ago

The thing is with a wish machine, you can one shot something very easily.

But then you realize software is the accumulation of 1000s of wishes. And you want this but not that. Many little micro decisions of exactly what you want in every nook and cranny.

In the current paradigm (LLMs) we still have to manage all this. But maybe in the future we have something impossible to imagine.

weakfish• 10 days ago

You’re assuming that progress will continue at the same rate (it’s plateaud a bit as far as I can tell, I can look for sources tomorrow but am on phone now :))

& I think it’s fairly demonstrated that the industry isn’t profitable for training ever increasingly huge models, which get exponentially more expensive each iteration

galaxyLogic5• 10 days ago

I wonder, LLMs have progressed at great speed, because they have learned to duplicate what humans did and recorded in the documents and source-code that became the training materials for the LLMs. But now that humans don't write any more code, there is no new learning materials for the LLMs. There are no new things for them to learn. Therefore I expect they will plateau, the progress is no longer so fast.

And maybe we'll get something like a Mad Cow Disease, when AI "eats its own brains". To avoid that from happening we will need continued human inputs, and review.

zelphirkalt6• 10 days ago

Already loathing the idea of not even being able to directly blame humans and their incapability for making shitty websites, that require JS for everything, including typing a text in an input field. If we get there and the LLMs build the same crap, dialed up to 110, because even more suits want first and foremost fancy looks, rather than function, and because that's the majority of training data corpus they learned from ... I might have an existential crisis coming in. The web already sucks hard enough. At least let me blame incapable human beings for this situation.

andai3• 10 days ago

It’s our job to build the software factory - not just the software. Software engineers maintain the assembly line allowing anyone to prompt for a change and ship immediately.

The job of the software engineer increasingly becomes to make himself unnecessary: to empower the nontechnical business users to do as much as reasonably possible, without his/her intervention.

This has, of course, been the dream of computing, since its inception! And the true aim of every "high level" or "beginner friendly" (looking at you javascript!) language.

But finally, now that the computer actually speaks English (and is beginning to stop making completely insane errors), it gradually becomes feasible.

Freeing the masses from the tyranny of the nerds!

inigyou5• 9 days ago

This isn't the first or even the tenth attempt at making computer programming accessible to everyone. Remember COBOL? COBOL made the computer speak English. It didn't help.

A specification detailed enough to control every aspect of the resulting product is called a program. Compilers are AI. The prevalence of compilers hasn't harmed the programming industry at all, quite the opposite.

andai3• 9 days ago

Well, it's harmed the assembly programming industry.

andai3• 9 days ago

Update: since I have posted this my computer has made several completely insane errors. I guess we're not quite there yet haha.

supermdguy• 10 days ago

“Do you know what the industry term for a project specification that is comprehensive and precise enough to generate a program?

Code. It’s called code.”

- CommitStrip (https://www.reddit.com/r/ProgrammerHumor/comments/1p70bk8/sp...)

I think if you’re doing it right, the core of your code should be the simplest expression of the underlying business logic. Of course there’s always going to be supporting layers, and maybe those don’t need to be reviewed. But if you haven’t read the code, there’s an extent to which you don’t know the business logic.

teddyh• 10 days ago

Original link: <https://web.archive.org/web/20260521130338/https://www.commi...>

softwaredoug16• 10 days ago

My other article on this topic advocates for using code over specs :)

It’s ok to talk to the agent in code. Or create examples for it to follow.

https://softwaredoug.com/blog/2026/07/04/write-code-not-spec...

bluefirebrand2• 10 days ago

It’s ok to talk to the agent in code. Or create examples for it to follow

If you're doing this, then why not just write the effing code?

gblargg• 10 days ago

My other article on this topic advocates for using code over specs :)

Code is executable. Specs are not.

imhoguy2• 10 days ago

What I miss in Claude Code is code completion at prompt line.. ah wait it gets back to IDE and Copilot.

noosphr• 10 days ago

This is why you need lisp.

First you write a programming language in which the language primatives are the business logic primatives, then you write a trivial program that describes what the business does in the new language.

podgietaru• 10 days ago

I was thinking about an experience I had recently, and how it relates to my feelings about AI... And it bummed me out a lot.

So I took over an open source project called Omnivore. It's a reading app in the vein of Pocket. The hosted version used pdf-lib to inject some functionality into the pdf viewer. Namely, highlighting, note taking, and storing location. pdf-lib is a licensed application, so when taking it to fully self-hosted this needed to change.

I migrated it over to pdf.js. And I went through the entire process. I added all the functionality bit by bit. It didn't take exceptionally long, maybe 1-3 days. But that process was really satisfying. I found a bug, fixed it, and then found a stackoverflow issue where someone was also experiencing the same issue and suggested the fix. https://stackoverflow.com/questions/59151218/pdfjs-error-on-...

I'm pretty sure an ai could have done all of this. And therein lies my fear and my upset with AI. Not only would it have robbed me of that experience, but it shows that I have in a way been devalued. Because I do think that took a level of skill. And now that's gone...

softwaredoug16• 10 days ago

I think what we’re learning is that up front slower experience can be valuable for maintaining the maintainers own understanding of the project

I’ll be very curious how / if the Bun port to Rust works out.

throwatdem12311• 10 days ago

If you’re not writing code it won’t be long until you get to a point where your agent won’t be able to dig you out of whatever hole you’ve dug for yourself and then you are fubar because you’ve just completely forgotten how.

jv222222• 10 days ago

At this point I haven't looked at code for many months. Before that, I spent 4 years hand coding a Google Docs competitor in JS without any libraries.

My brain feels equally as exercised (in fact more so as I am not as good at agentic coding as I was at real coding)

But now I'm making highly polished Mac OS apps and I really like that move from JS.

I feel... conflicted.

softwaredoug16• 10 days ago

Do you like to look at code? I’m finding it’s really just a personal preference. And honestly not worth getting worked up about either way.

jv222222• 10 days ago

This is weird but I think I like to focus wherever I feel needs polish.

So, making a real time collaborative tool from scratch there was a lot of deep work in things like sockets, queues, memory structures, etc. That's just what needed attention.

Right now I'm building a memory app for AI.

So far I haven't spent much time looking at code on the swift side of things. But I have spent a lot of time up front working on domain driven design, screaming architecture, and module based design.

I think with AI the polish is in deep QA, design taste, running trace logs and constantly asking it to do html diagrams of the architecture and such.

ngl I miss "knowing what's going on" at the code level, but it feels like not a good use of my time to go into those weeds.

When I look at the code it seems well structured due to screaming architecture, and module based design.

hirvi742• 10 days ago

I write organic code in 2026 because I do not have a choice. Which, honestly, I am thankful for most of the time. My employer has no LLM mandates nor do they supply us an LLMs to use.

In my personal life, I cannot justify more than a $20 sub per month. I only use the Web Chat anyway. Shelling out $100-$200 a month for a sub in which I would get little to no ROI is a poor choice. Besides, I've never hit the limit on my $20 a month plan either.

The day I am forced to prompt LLMs all day, every day is the day I am cashing out of programming as a career. Though to be clear, I have no opposition towards anyone that uses LLMs, and think they are fantastic tools when used appropriately. (I love them as a StackOverflow replacement, and have learned a lot from going back and forth with LLMs).

okanat2• 10 days ago

Not because agents are worse at coding that[sic] humans.

And then the whole article shows tangible reasons where the agents are truly worse at code than humans. Code never is just the text. If intelligence you have is not truly general, you cannot expect things like clarifying wider context, hierarchically ordering knowledge based on criteria and producing consistent results despite transfer learning and retraining.

And no, we are not even close to the multimodal capabilities of human brain to hierarchy encode and reproduce knowledge. Otherwise the correct "reasonable" economic action would be genociding all humans, and I'm pretty sure that this is what billionaires effectively want out of AI.

lowsong• 10 days ago

    Writing code helps me think.

Every time I read some take about keeping up one's skills when using agents people get so tantalisingly close to the obvious answer, and then fall short.

If the tools are making you worse, don't use the tools.

h4kunamata2• 10 days ago

This does not seem obvious to AI-developers, you cannot fix what you do not understand.

Also, if you use AI to write your code, you are not a developer either.

Let's say AI completely disappears right now, many of the so called "developers" are unable to write code, are unable to fix code, they cannot code.

There are two kind of developers:

1. Non-developers: Use AI for everything, to write code, to test the code, you name it.

2. Real developers: Search engines are broken right now, they use AI as a tool, as replacement for Google to ASSIST you, not to do the task for you.

As AI is falling apart and companies are hiring people back, these non-developers will find themselves out of work.

squibonpig• 10 days ago

Ai will fall apart as an industry but it's likely that models on par with e.g. opus 4.8 will be runnable on a home server within the next year and a half and that model hosts will still exist. I figure these tools aren't likely to go away.

h4kunamata2• 10 days ago

AI is here to stay, full stop.

The problem is IT professionals who depend on AI for everything. That is crashing down and won't be pretty.

Arubis• 10 days ago

To build software that you understand yourself. Next question.

ccoffey1• 10 days ago

"Instead, we’re switching to this wrong-headed mindset that coding agents are like compilers. That mindset gives us permission to ship terribly written code. Agents aren’t compilers - they’re more like freshly onboarded interns."

I feel this statement these days during code reviews. I know some amazing engineers whose output lately just isn't the same.

dented42• 10 days ago

I feel like this question doesn’t need a blog post to answer.

Why write code in 2026? Because it’s fun.

j16sdiz• 10 days ago

I discovered Doctorow's "Reverse centaurs are the answer to the AI paradox" via a link in this article.

It was a great read.

Recent HN Discussion: https://news.ycombinator.com/item?id=48873855

jillesvangurp2• 10 days ago

The relevant question is who is going to pay you to write code manually. It's something that's increasingly hard to justify. The answer is of course that people are not paying for code to be written or generated but for some problem to be solved. Whoever does that with the least amount of drama and cost gets the business. And using AI tools just allows for compressing the timelines a bit in a way that is hard to ignore.

Most code out there isn't all that great. I've been in this industry since the nineties. There are a lot of not so great software engineers doing mediocre work. People are romanticizing how great and magnificent their code is (or used to be). The reality of manually crafted code is of course a lot less flattering. Many code bases become hard to maintain over time and are riddled with bugs. And it's not like sloppy code is a new thing. Poorly executed software projects have been very common for a long time. That's not going to go away.

tonyedgecombe• 10 days ago

There are a lot of not so great software engineers doing mediocre work.

Yeah, and they are all producing 10x as much mediocre work now.

Pavilion2095• 10 days ago

The relevant question is who is going to pay you to write code manually.

Hopefully companies in the industries where software quality matters and is regulated, e.g.: medicine, aviation, nuclear, etc.

Although this market is relatively small.

jillesvangurp2• 10 days ago

You seem to assume that people still have an inherent advantage here. Mostly those sectors compensate for well documented human failures with very rigid and expensive processes and testing. And of course despite that, stuff still goes wrong occasionally.

I actually think AI based automation is going to be a key enabler in those kinds of strict environments as well. Recent work on identifying e.g. security bugs seems to be resulting in a lot of improvement that has somehow escaped decades of human scrutiny. With good quality harnesses (manual or automated), I don't see any big objection against using generated code here.

softwaredoug16• 9 days ago

I personally am advocating for writing small amounts of code because I think it makes you more productive

Spending a day manually reworking the architecture in my experience can save you $1000s in tokens and weeks of headaches.

We’re trying to build a software factory with hands tied behind our back

mintflow• 10 days ago

This resonate with me a lot

Recently I am seriously thinking the time when agent do the work and I was waiting for it's output, I got a bit lost given it really can do a lot but it make me feel some crisis as a human, even it still can provide me a sort of Joy because some task I long want to do but no time to start can be finally take shape, but the Joy is actually not comparable with the Joy when I read the code and hack with it

Concretely, I am letting agent to write some serious part of code to rust and I will consider only let Agent to handle the UI and integration stuffs, and I will take the rust part and rust is a language that I want to learn and be professional given I was do lots of C coding

gloosx• 10 days ago

The OpenGraph preview image for this article is a total ragebait

mahmoudilyan• 10 days ago

I enjoy writing and read code as well, but AI race force me to skip that part to be able to ship faster.

I spend time building AI Agentic guides and skills, then review the code myself. I really miss the old days when you put your headphones on and focus for 3-4 hours

chromadon• 9 days ago

"Why write code in 2026"..

Because AI generated code is STILL complete ass. Even Fable, even whatever custom Pi/opencode leet code harness you have, the output is awful, and, if you cannot distinguish the quality of your code vs the AI's, I've got some bad news for you.

mewpmewp29• 9 days ago

My code is/was worse than AI's, but at least I get paid, so what do I care about the bad news you have.

superze• 9 days ago

You are exactly the person who should be afraid then and you prove his point?!

anthonypasq• 9 days ago

99% of code ever written has always been shit. Most of it has been thrown out or not in use anymore, or EVER used. Most people arent going anything particularly unique or complicated or performance focused.

soundworlds• 9 days ago

The most interesting and creative projects I have worked on required little code, but novel combinations of ideas.

balder19914• 9 days ago

I’d like to recommend people to read the “Programming as a theory building” article and why the code itself isn’t enough to understand the whole context of a complex project.

Every time you work in a complex software project, you have all the context in your head about what you must take into consideration. LLMs don’t, you have to explain every little detail to them, but there’s no telling where it stops: do you have to explain X to it or is it in the training already?

When you try to shape how a LLM should behave and what it should know, you end up writing a Bible of relevant context that’s increasingly difficult to maintain as well, often with outdated or contradictory information, and it is still free to ignore things you have written and proceed however it wants.

That’s why so many people only feel comfortable giving the LLM some limited task to do, because you can judge if that specific task needs just enough context that it can handle by itself.

vonneumannstan• 9 days ago

Arrogance, vanity, ignorance... etc.

Why write code in 2026

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