The tradeoff of higher velocity for less enjoyment may feel less welcome when it becomes the new baseline and the expectation of employers / customers. The excitement of getting a day's work done in an hour* (for example) is likely to fade once the expectation is to produce 8 of such old-days output per day.
I suspect it doesn't matter how we feel about it mind you. If it's going to happen it will, whether we enjoy the gains first or not.
* setting aside whether this is currently possible, or whether we're actually trading away more quality that we realise.
jodosha 9 minutes ago [-]
> The tradeoff of higher velocity for less enjoyment may feel less welcome when it becomes the new baseline and the expectation of employers / customers
This is what happens with big technological advancements. Technology that enables productivity won’t free people time, but only set higher expectations of getting more work done in a day.
latexr 3 days ago [-]
> The excitement of getting a day's work done in an hour* (for example) is likely to fade once the expectation is to produce 8 of such old-days output per day.
That dumb attitude (which I understand you’re criticising) of “more more more” always reminds me of Lenny from the Simpsons moving fast through the yellow light, with nowhere to go.
> I suspect it doesn't matter how we feel about it mind you. If it's going to happen it will, whether we enjoy the gains first or not.
That is quite the defeatist attitude. Society becoming shittier isn’t inevitable, though inaction and giving up certainly helps that along.
brailsafe 4 hours ago [-]
> That is quite the defeatist attitude. Society becoming shittier isn’t inevitable, though inaction and giving up certainly helps that along.
If the structures and systems that are in-place only facilitate life getting more difficult in some way, then it probably will, unless it doesn't.
Housing getting nearly unownable is a symptom of that. Climate change is another.
popcorncowboy 15 hours ago [-]
> "If it's going to happen it will" - That is quite the defeatist attitude. Society becoming shittier isn’t inevitable
You're right in general, but I don't think that'll save you/us from OP's statement. This is simple economic incentives at play. If AI-coding is even marginally more economically efficient (i.e. more for less) the "old way" will be swept aside at breathtaking pace (as we're seeing). The "from my cold dead hands" hand-coding crowd may be right, but they're a transitional historical footnote. Coding was always blue-collar white-collar work. No-one outside of coders will weep for what was lost.
sarchertech 11 hours ago [-]
> If AI-coding is even marginally more economically efficient (i.e. more for less) the "old way" will be swept aside at breathtaking pace (as we're seeing).
On the scale I’ve been doing this (20 years), that hasn’t been the case.
Rails was massively more efficient for what 90% of companies where building. But it never had anywhere near a 90% market share.
It doesn’t take 1000 engineers to build CRUD apps, but companies are driven to grow by forces other than pure market efficiency.
There are still plenty of people using simple text editors when full IDEs have offered measurable productivity boosts for decades.
>(as we’re seeing)
I work at a big tech company. Productivity per person hasn’t noticeably increased. The speed that we ship hasn’t noticeably increased. All that’s happening is an economic downturn.
throw10920 7 hours ago [-]
I think that you're correct in that Rails and IDEs offer significant productivity benefits but aren't/weren't widely adopted.
But AI seems to be different in that it claims to replace programmers, instead of augment them. Yes, higher productivity means you don't have to hire as many people, but with AI tools there's specifically the promise that you can get rid of a bunch of your developers, and regardless of truth, clueless execs buy the marketing.
Stupid MBAs at big companies see this as a cost reduction - so regardless of the utility of AI code-generation tools (which may be high!), or of the fact that there are many other ways to get productivity benefits, they'll still try to deploy these systems everywhere.
That's my projection, at least. I'd love to be wrong.
sarchertech 2 hours ago [-]
I believe you’re 100% right about trying to replace devs. In that respect it’s like offshoring.
But no matter how hard cost cutters wanted to, they were never able to actually reduce the total number of devs outside of major economic downturns.
shkkmo 14 hours ago [-]
> more economically efficient
I suspect we'll find that the amount of technical debt and loss of institutional knowledge incured by misuse of these tools was initially underappreciated.
I don't doubt that the industry will be transformed, but that doesn't mean that these tools are a panacea.
loandbehold 14 hours ago [-]
I read about AI assistants allegedly creating tech debt but my experience is opposite. Claude Code makes it easy to refactor helping to reduce tech debt. Tech debt usually happens because refactoring takes time but is hard to justify to upper management because upper management only sees new features but not quality of code. With Claude Code refactoring is much faster so it gets done.
shkkmo 16 minutes ago [-]
I would argue that you should only allow Claude to refactor code that you understand. Once that institutional knowledge is lost you would then have to regain it before you can safely refactor it, even with Claude's help.
I also specifically used the term "misuse" to significantly weaken my claim. I mean only to say that the risks and downsides are often poorly understood, not that there are no good uses.
chongli 10 hours ago [-]
Are you talking about refactoring code you’re already familiar with? Or a completely unknown codebase that no one else at the company knows anything about and you’ve been tasked with fixing?
loandbehold 8 hours ago [-]
Both. But I'm not talking about fixing. I'm talking about refactoring.
chongli 4 hours ago [-]
It’s often the case that in order to fix an issue you need to refactor first.
zdragnar 8 hours ago [-]
> “more more more”
If you're a salaried or hourly employee, you aren't paid for your output, you are paid for your time, with minimum expectations of productivity.
If you complete all your work in an hour... you still owe seven hours based on the expectations of your employment agreement, in order to earn your salary and benefits.
If you'd rather work in an output based capacity, you'll want to move to running your own contacting business in a fixed-bid type capacity.
SketchySeaBeast 7 hours ago [-]
That's funny, because, at more than one place I've worked as a salaried employee, when I had to work OT, the narrative was "you're salary because you're paid to get the job done, doesn't matter how many hours it takes". Unfortunately, "the job" somehow never worked out to be less than 40 hours a week.
tom_ 5 hours ago [-]
In many (most?) salary jobs, employees are typically paid both to get the job done, and to supply at least N hours of their time for the company to have them use as it sees fit.
SketchySeaBeast 4 hours ago [-]
Yeah, I've been in industry for over a decade, still don't understand the value of salary for the devs.
dfxm12 8 hours ago [-]
moving fast through the yellow light, with nowhere to go.
My company has been preparing for this for a while now, I guess, as my backlog clearly has years' worth of work in it and positions of people who have left the org remain unfilled. My colleagues at other companies are in a similar situation. Considering round after round of layoffs, if I got ahead a little bit and found that I had nothing else to do, I'd be worried for my job.
Society becoming shittier isn’t inevitable
Yes, I agree, but the deck is usually stacked against the worker, especially in America. I doubt this will be the issue that promotes any sort of collectivism.
bigfudge 14 hours ago [-]
> That is quite the defeatist attitude. Society becoming shittier isn’t inevitable, though inaction and giving up certainly helps that along.
This feels like kicking someone when they’re down! Given the current state of corporate and political America, it doesn’t look likely there will be any pressure for anything but enshittification to me. Telling people at the coal face to stay cheerful seems unlikely to help. What mechanism do you see for not giving up to actually change the experience of people in 10 ish years time?
tehjoker 8 hours ago [-]
Unionization. Work speed-ups are a classic management assault on the working man.
atoav 13 hours ago [-]
> Telling people at the coal face to stay cheerful seems unlikely to help.
That isn't what they said tho. They said you have to do something, not that you should just be happy. Doing something can involve things that historically had a big impact in improving working conditions, like collective action and forming unions.
The opposite advice would be: "Everything's fucked, nothing you can do will change it, so just give up." Needless to say that is bad advice unless you are a targeted individual in a murderous regime or similar.
creesch 12 hours ago [-]
> That dumb attitude (which I understand you’re criticising) of “more more more” always reminds me of Lenny from the Simpsons moving fast through the yellow light, with nowhere to go.
Realizing that attitude in myself at times has given me so much more peace of mind. Just in general, not everything needs to be as fast and efficient as possible.
Not to mention the times where in the end I spend a lot of time and energy in trying to be faster only to end up with this xkcd: https://xkcd.com/1319/
As far as LLM use goes, I don't need moar velocity! so I don't try to min max my agentic workflow just to squeeze out X amount more lines code.
In fact, I don't really work with agentic workflows to begin with. I more or less still use LLMs as tools external to the process. Using them as interactive rubber duckies. Things like deciphering spaghetti code, do a sanity check on code I wrote (and being very critical of the suggestions they come up with), getting a quick jump start on stuff I haven't used again (how do I get started with X of Y again?), that sort of stuff.
Using LLMs in the IDE and other agentic use is something I have worked with. But to me it falls under what I call "lazy use" where you are further and further removed from the creation of code, the reasoning behind it, etc. I know it is a highly popular approach with many people on HN. But in my experience, it is an approach that makes skills of experienced developers atrophy and makes sure junior developers are less likely to pick them up. Making both overly reliant on tools that have been shown to be less than reliable when the output isn't properly reviewed.
I get the firm feeling that velocity crowd works in environments where they are judged by the amount of tickets closed. Basically "feature complete, test green, merged, move on!". In that context, it isn't really "important" that the tests that are green are also refactored by the thing itself, just that they are green. It is a symptom of a corporate environment where the focus is on these "productivity" metrics. From that perspective I can fully see the appeal for LLM heavy workflows as they most certainly will have an impact on metrics like "tickets closed" or "lines of code written".
jckahn 10 hours ago [-]
> Just in general, not everything needs to be as fast and efficient as possible.
It does when you are competing for getting and keeping employment opportunities.
creesch 10 hours ago [-]
Even then it is not always needed, but I also more directly address this already in the comment you are replying to.
atoav 14 hours ago [-]
> That is quite the defeatist attitude. Society becoming shittier isn’t inevitable, though inaction and giving up certainly helps that along.
Correct. But it becoming shittier is the strong default, with forces that you constantly have to fight against.
And the reason is very simple: Someone profits from it being shittier and they have a lot of patience and resources.
furyofantares 2 days ago [-]
> That is quite the defeatist attitude. Society becoming shittier isn’t inevitable, though inaction and giving up certainly helps that along.
The hypothetical that we're 8x as productive but the work isn't as fun isn't "society becoming shittier".
Steven420 1 days ago [-]
How is everyone working shitty jobs not "society becoming shittier"? Seems pretty awful
furyofantares 1 days ago [-]
"Society" is more than just software developers.
We are very well paid for very cushy work. It's not good for anyone's work to get worse, but it's not a huge hit to society if a well-paid cushy job gets less cushy.
And presumably people buy our work because it's valuable to them. Multiplying that by 8 would be a pretty big benefit to society.
I don't want my job to get less fun, but I would press that button without hesitation. It would be an incredible trade for society at large.
pempem 15 hours ago [-]
Well lets think about it.
Software devs jobs getting less cushy is no biggie. We can afford to amp up the efficiency.
Teachers jobs got "less cushy" -> not great for users/consumers or the ppl in those jobs.
Doctors jobs got "less cushy" -> not great for users/consumers or the ppl in those jobs.
Even waiters/ check-out staff, stockists jobs at restaurants, groceries and AMZ got "less cushy" -> not great for users/consumers or the ppl in those jobs. at least not when you need to call someone for help.
These things are not as disconnected as they seem. Businesses are in fact made up of people.
pdntspa 15 hours ago [-]
Maybe everybody's job should be cushy instead. We were not put on this earth to toil away for a bunch of rich fucks
codr7 16 hours ago [-]
If you think software development is cushy, I wonder what kind of software you're writing. Because there are different levels; getting something to work is not the same thing as writing maintainable, high quality software.
I've seen plenty enough people try, really try, to get into software development; but they just can't do it.
advael 9 hours ago [-]
This places a lot of faith in the following assumptions:
1. Efficiency measures as written to benchmark this coupling with economic productivity overall
2. Monetary assessments of value in the context of businesses spending money corresponding with social value
3. The gains of economic productivity being distributed across society to any degree, or the effect of this disparity itself being negligible
4. The negative externalities of these processes scaling less quickly than whatever we're measuring in our productivity metric
5. Aforementioned externalities being able to scale to even a lesser degree in lockstep with productivity without crashing all of the above, if not causing even more catastrophic outcomes
I have very little faith in any of these assumptions
bluefirebrand 16 hours ago [-]
My cushy software job has burned me out so badly that I am on medical leave with massive memory problems and a bit of concern about my heart
So I mean... Yeah
Is software more comfortable generally than many other lines of work? Yes probably
Is it always soft and cushy? No, not at all. It is often high pressure and high stress
furyofantares 1 hours ago [-]
I'm sorry for implying there can't be hardship (significant, even devastating) in this line of work. Thanks for posting about your experience.
griffiths 11 hours ago [-]
What kind of massive memory problems? I might have this but didn't think to attribute it to burnout.
ModernMech 8 hours ago [-]
When I burned out I experienced skill regression and short term memory loss. Like, an inability to remember specific events of the day before, inability to perform skills I had done for decades like play an instrument. Took over a year to stabilize and return to normal.
griffiths 6 hours ago [-]
Mine is more of a long term memory loss. Inability to recall some memorable events from months or even a year ago. I’ll definitely check or go talk with someone.
bluefirebrand 7 hours ago [-]
Yes, this is extremely similar to my experience
I cannot remember events, conversations, or details about important things. I have partially lost my ability to code, because I get partway through implementing a feature and forget what pieces I've done and which pieces still need to be done
I can still write it, but the quality of my work has plummeted, which is part of why I'm off on leave now
cultofmetatron 4 hours ago [-]
was going through something similar. here's my anti burnout protocol thats kept me functional all the way to my current position as founder and CTO of a profitable startup.
1. 1 tablespoon of cold extracted cod liver oil EVERY MORNING
2. 30 min of running 3-4 times a week
3. 2-3 weight lifting sessions every week
4. regular walks.
5. cross train on different intellectually stimulating subjects. doing the same cognitive tasks over and over is like repetive motion on your muscles
6. regularly scheduled "fallow mind time." I set aside an 30 min to an hour everyday to just sit in a chair and let my mind wander. its not meditation. I jsut sit and let my mind drift to whatever it wants.
7. while it should be avoided, in the event that you have to crunch, RESPECT THE COOLDOWN. take downtime after. don't let your nontechnical leads talk you out of it. thinking hard for extended periods of time requires appropriate recovery.
the human brain is a complex system and while we think of our mind as abstract and immaterial, it is in reality a whole lot of physical systems that grow, change and use resources the same way any other physical system in your body does. just like muscles need to recover after a workout to get stronger, so too does your brain after extended periods of deep thinking.
ModernMech 6 hours ago [-]
Hang in there, it gets better and the skills come back. From my github:
2,350 contributions in 2021
2,661 contributions in 2022
381 contributions in 2023 <--- burnout
794 contributions in 2024 <--- recovery
1,632 contributions in 2025 (so far)
My recovery took about 18 months. It took time, and a lot of rest. I'd have to sleep like 12 hours a day sometimes.
bluefirebrand 2 hours ago [-]
Thank you for the kind encouragement
I hope my recovery doesn't take that long, but if it does it does
I would rather give myself the space and time to really get better, rather than simply rush back to work and burn out again
mrbombastic 10 hours ago [-]
Also asking for a friend…
bluefirebrand 7 hours ago [-]
Really sorry to hear that
All I can suggest is see a doctor as soon as possible and talk to them about it
bluefirebrand 7 hours ago [-]
Difficult to explain because it's inconsistent
But I am struggling to remember things I did not used to struggle with
Going to an event on a weekend with my wife and completely forgetting that we ran into a friend there. Not just "oh yeah I forgot we saw them", like feeling my wife is lying to me when she tells me we saw them. Texting them to ask and they agree we saw each other
These are people I trust with my life so I believe they would not gaslight me, my own memory has just failed
Many examples like this, just completely blacking out things. Not forgetting everything, but blacking out large pieces of my daily life. Even big things
politician 7 hours ago [-]
FWIW, I am not your doctor: Taking a daily antioxidant, glutathione, has helped me manage memory-related symptoms that appeared coincident with other burnout symptoms.
Disclaimer: talk to your doctor. I don’t know if your doctor can tell you whether this is a good idea, but it might help in some countries with good medical systems.
bluefirebrand 7 hours ago [-]
I might as well ask my doctor about it, thanks
anothernewdude 15 hours ago [-]
Okay, but the reality of society becoming shittier is society becoming shittier.
theshrike79 3 days ago [-]
The trick is not telling anyone you spent an hour to do 7 hours of work.
That's stupid and detrimental to your mental health.
You do it in an hour, spend maybe 1-2 hours to make it even better and prettier and then relax. Do all that menial shit you've got lined up anyway.
creesch 13 hours ago [-]
> The trick is not telling anyone you spent an hour to do 7 hours of work.
I wish that the hype crowd would do that. It would make a for a much more enjoyable and sane experience on platforms like this. It's extremely difficult to have actual conversations subjects when there are crowds of fans involved who don't want to hear anything negative.
Yes, I also do realize there are people completely on the other side as well. But to honest, I can see why they are annoyed by the fan crowd.
carlmr 9 hours ago [-]
>I wish that the hype crowd would do that.
Exactly, IME the hype crowd is really the worst at this. They will spend 8h doing 8 different 1h tries at getting the right context for the LLM and then claim they did it in 1h.
They claim to be faster than they are. There's a lot of mechanical turking going about as soon as you ask a few probing questions.
pavel_lishin 3 hours ago [-]
Until your coworkers who've never heard of work-life balance start bragging about it, and volunteering to spend 8 hours to do 56 hours of work, or maybe spending 11 hours to impress the boss.
specproc 2 days ago [-]
The most challenging thing I'm finding about working with LLM-based tools is the reduction in enjoyment. I'm in this business because I love it, and I'm worried about that going forward.
r_lee 13 hours ago [-]
Yup. not sure if it's just me but the trend seems to be just ship slop as fast as you can, nothing else matters, just ship ship ship
a_bonobo 18 hours ago [-]
For the longest time, IT workers were 'protected' from Marx's alienation of labor by the rarity of your skill, but now it's coming for you/us, too. Claude Code is to programmers what textile machines were to textile workers.
>In the capitalist mode of production, the generation of products (goods and services) is accomplished with an endless sequence of discrete, repetitive motions that offer the worker little psychological satisfaction for "a job well done." By means of commodification, the labour power of the worker is reduced to wages (an exchange value); the psychological estrangement (Entfremdung) of the worker results from the unmediated relation between his productive labour and the wages paid to him for the labour.
Less often discussed is Marx's view of social alienation in this context: i.e., workers used to take pride in who they are based on their occupation. 'I am the best blacksmith in town.'
Automation destroyed that for workers, and it'll come for you/us, too.
codr7 16 hours ago [-]
Nope, not until AI is writing high quality, maintainable software; and no one knows if that's even possible yet.
hudon 16 hours ago [-]
What caused textile machines to replace the manual labor wasn’t the quality of their output, it was quantity. In fact, manually made clothing was of higher quality than what was machine-produced.
gibagger 13 hours ago [-]
A low quality fabric makes the fashion police come and arrest you.
Low quality software kills people.
nullandvoid 12 hours ago [-]
Safety critical (will kill someone if not bug free) code makes up <1% of what's shipped, safety clothes which must be of high quality else risk harm to someone make up a similarly small percent
Both will stay manual / require high level of review they're not what's being disrupted (at-least in near term) - it's the rest.
sarchertech 11 hours ago [-]
Nearly all clothing is still produced in an extremely manual process.
What was automated was the production of raw cloth.
hudon 10 hours ago [-]
This is a distinction without a difference. Even if you take a rudimentary raw cloth comparison like cotton vs heavy wool (the latter being fire resistant and used historically used by firemen, ie. “Safety critical”), the machines’ output quality was significantly lower than manual output for the latter.
This phenomenon is a general one… chainsaws vs hand saws, bread slicers vs hand slicing, mechanical harvesters vs manual harvesting, etc.
sarchertech 9 hours ago [-]
That’s just not the general case at all. Automated or “powered” processes generally lead to a more consistent final product. In many cases the quality is just better than what can be done by hand.
gibagger 8 hours ago [-]
There are many corporate nightmare level scenarios out there. There is no need to reach loss of life situations to make my point.
A large enough GDPR or SOX violation is the boogeyman that CEO's see in their nightmares.
sarchertech 11 hours ago [-]
That’s a misconception.
The machines we’re talking about made raw cloth not clothing and it was actually higher quality in many respects because of accuracy and repeatability.
Almost all clothing is still made by hand one piece at a time with sewing machines still very manually operated.
hudon 10 hours ago [-]
“ …by the mid‑19th century machine‑woven cloth still could not equal the quality of hand‑woven Indian cloth. However, the high productivity of British textile manufacturing allowed coarser grades of British cloth to undersell hand‑spun and woven fabric in low‑wage India” [0]
“…the output of power looms was certainly greater than that of the handlooms, but the handloom weavers produced higher quality cloths with greater profit margins.” [1]
The same can be said about machines like the water frame. It was great at spinning coarse thread, but for high quality/luxury textile (ie. fine fabric), skilled (human) spinners did a much better job. You can read the book Blood in the Machine for even more context.
The problem with those quotes is the lack of definition of “quality”. Machine woven cloth in many ways is better because of consistency and uniformity.
If your goal is to make 1000 of the exact same dress, having a completely consistent raw material is synonymous with high quality.
It’s not fair to say that machines produced some kind of inferior imitation of the handmade product, that only won through sheer speed and cost to manufacture.
codr7 15 hours ago [-]
Yes, but they still filled their purpose.
AI slop code doesn't even work beyond toy examples.
hudon 10 hours ago [-]
After the operating system and the spreadsheet, most software is toys.
skydhash 8 hours ago [-]
There are a lot of professional software out there. CAD, DAW, software that automated some services, and software to support all of those.
codr7 8 hours ago [-]
That isn't even close to true; we've based more or less our entire society on software, and it's getting worse every day.
baq 15 hours ago [-]
Why wouldn’t it be possible if meat computers can do it more or less reliably? The construction of such a machine is a matter of time; whether it’s a year or a century is anyone’s guess.
When it is eventually made, though… it’s either aligned or we’re in trouble. Job cushiness will be P2 or P3 in a world where a computer can do everything economically viable better than any human.
codr7 15 hours ago [-]
Speak for yourself, I'm not a computer.
baq 13 hours ago [-]
Your opinion on the matter is not relevant whether you are or aren't one. Besides, if our brains aren't computers, what are they?
crabmusket 13 hours ago [-]
> what are they?
They are brains. I think it's on you to prove they're the same, rather than assuming they're the same and then demanding proof they aren't!
alansammarone 13 hours ago [-]
Turing machines are universal. Anything that does anything is, at most, a Turing machine.
sarchertech 10 hours ago [-]
Turing machines are not universal. They can compute anything computable, that’s a huge difference.
bluefirebrand 16 hours ago [-]
In fairness to AI, many software devs are not writing high quality, maintainable software
But in fairness to human devs, most are still writing software that is leagues better than the dog shit AI is producing right now
hnfsfdsd 16 hours ago [-]
Exactly, maybe "prompt engineering" is really a skill, but the reward for getting better at this is just pumping out more features at a low skill grade. What's excited about this ? Unless I want to spend all my time building minimum viable product.
Cthulhu_ 13 hours ago [-]
Prompt engineering is just writing acceptance criteria; it's moving from someone who writes code to someone who writes higher level feature descriptions. Or user stories, if you will.
Thing is though, many people don't know how to do that (user stories / acceptance criteria) properly, and it's been up to software developers to poke holes and fill in the blanks that the writer didn't think about.
willtemperley 3 days ago [-]
Short-term, automated tech debt creation will yield gains.
Long term the craftsperson writing excellent code will win. It is now easier than ever to write excellent code, for those that are able to choose their pace.
pureliquidhw 2 days ago [-]
Given it's 2025 and companies saddled with tech debt continue to prioritize speed of delivery over quality, I doubt the craftperson will win.
If anything we'll see disposable systems (or parts) and the job of an SE will become even more like a plumber, connecting prebuilt business logic to prebuilt systems libraries. When one of those fails, have AI whip up a brand new one instead of troubleshooting the existing one(s). After all, for business leader it's the output that matters, not the code.
For 20+ years business leaders have been eager to shed the high overhead of developers via any means necessary while ignoring their most expensive employees' input. Anyone remember Dilbert? It was funny as a kid, and is now tragic in its timeless accuracy a generation later.
lmm 15 hours ago [-]
> it's 2025 and companies saddled with tech debt continue to prioritize speed of delivery over quality
Maybe. I'm seeing the opposite - yes, the big ships take time to turn, but with the rise of ransomware and increasing privacy regulation around the world, companies are putting more and more emphasis on quality and avoiding incidents.
skydhash 8 hours ago [-]
Also, companies are expected to adapt more faster or see their lunch money taken by startups (unless you're in a heavily regulated space). There's a lot of quality opensource software out there, so you don't need much to bootstrap. The tech debt that was ok because you can take your sweet time to deliver some feature is no longer so.
willtemperley 2 days ago [-]
Yes there will be a class of developer like that, but it would only be considered winning if you're satisfied with climbing some artificial institutional hierarchy.
pureliquidhw 2 days ago [-]
Indeed, the job of an SE is deviating further and further from code, much like how very few people write assembly anymore.
An earlier iteration of your reply said "Is that really winning?" The answer is no. I don't think any class of SE end up a winner here.
yifanl 2 days ago [-]
Climbing institutional hierarchy usually comes with being rewarded with more credits that I can trade for food, and I like eating food.
bravetraveler 2 days ago [-]
Avocado toast strikes again
AstroBen 17 hours ago [-]
Can you give an example that's playing out today?
pdntspa 15 hours ago [-]
That is certainly how it played out for me. Give your employers an inch and they will take a mile.
never_inline 12 hours ago [-]
> The excitement of getting a day's work done in an hour* (for example) is likely to fade once the expectation is to produce 8 of such old-days output per day.
It's not really about excitement or enjoyment of work.
It's the fear about the __8x output__ being considered as __8x productivity__.
The increase in `output/productivity` factor has various negative implications. I would not say everything out loud. But the wise can read between the lines.
shiandow 12 hours ago [-]
I always feel most productive when I remove more code than I add.
utyop22 9 hours ago [-]
Simplicity is the ultimate sophistication.
darkwater 3 days ago [-]
> The tradeoff of higher velocity for less enjoyment may feel less welcome when it becomes the new baseline and the expectation of employers / customers. The excitement of getting a day's work done in an hour* (for example) is likely to fade once the expectation is to produce 8 of such old-days output per day.
That's why we should be against it but hey, we can provide more value to shareholders!
an0malous 9 hours ago [-]
You won’t enjoy any of the gains, the company will be worth 10x and you’ll get a 10% raise to match inflation
cmiles74 7 hours ago [-]
Even if the developer is keeping the quality of the LLM generated code high (by constant close reading of the output, rejecting low quality work and steering with prompts) does this mean the project as a whole is improving? I have my doubts! I'm also skeptical that this developer has increased their velocity as much as they believe, IMHO this has long been a difficult thing to measure.
Overall, is this even a good thing? With this increase in output, I suspect we'll need to apply more pressure to people requesting features to ensure those requests are high quality. When each feature takes half the time to implement, I bet it's easy to agree to more features without spending as much time evaluating their worth.
ramesh31 13 hours ago [-]
>The tradeoff of higher velocity for less enjoyment may feel less welcome when it becomes the new baseline and the expectation of employers / customers.
This is precisely the question that scares me now. It is always so satisfying when a revolution occurs to hold hands and hug each other in the streets and shout "death to the old order". But what happens the next morning? Will we capture this monumental gain for labor or will we cede it to capital? My money is on the latter. Why wouldn't it be? Did they let us go home early when the punch card looms weaved months worth of hand work in a day? No, they made us work twice as hard for half the pay.
antonvs 5 hours ago [-]
> The tradeoff of higher velocity for less enjoyment
I'm enjoying exactly what the author describes, so it's different strokes for different folks.
I always found the "code monkey" aspect of software development utterly boring and tedious, and have spent a lot of my career automating that away with various kinds of code generators, DSLs, and so on. \
Using an LLM as a general-purpose automated code monkey is a near-ideal scenario for me, and I enjoy the work more. It's especially useful for languages like Go or Java where repetitive boilerplate is endemic.
I also find it helps with procrastination, because I can just ask an LLM to start something for me and get over the initial hump.
> whether we're actually trading away more quality that we realise.
This is completely up to the people using it.
deadbabe 14 hours ago [-]
If there are 8 days per day worth of work to be done (which I doubt), why wouldn’t you want to have it done ASAP? You’re going to have to do it eventually, so why not just do it now? Doesn’t make sense. You act like they’re just making up new work for you to do when previously there wouldn’t have been any.
lvnfg 13 hours ago [-]
Yes, work will expand to fill all your available hours due to unaligned incentives between who does the work (the SWE in this example) and who decide the quantity, timeline, and cost of work.
If the SWE can finish his work faster, 8x faster in this case, then backlogs will also be pushed to complete 8x faster by the project manager. If there are no backlogs, new features will be required at 8x faster / more by sales team / clients. If no new features are needed, pressures will be made until costs are 8x lower by finance. If there are no legal, moral, competitive, or physical constraints, the process should continue until either there’s only a single dev working on all his available time, or less time but for considerably less salary.
guappa 13 hours ago [-]
The reward for being faster is to do more work.
gyosko 11 hours ago [-]
I really don't get it.
While letting the AI write some code can be cool and fascinating, I really can't undersand how:
- write the prompt(and you need do be precise and think and express carefully what you have in mind)
- check/try the code
- repeat
is better than writing the code by myself. AI coding like this feels like a nightmare to me and it's 100x more exhausting.
nbaugh1 9 hours ago [-]
For me, on small personal projects, I can get a project to a point in about 4 hours where previous to new AI tools it would’ve taken about 40. At work, there is a huge difference due to the complexity of the code base and services. Using agents to code for me in these cases as 100% been the loop of iterating on something so often, I would’ve been better off with a more hands on approach, essentially just reviewing PRs written by AI.
david-gpu 10 hours ago [-]
I bet some people felt the same way when we collectively moved from assembly to compilers.
gyosko 10 hours ago [-]
Yeah, if not only for the small fact that you are leaving a well defined set of rules for pure chaos and randomness this time around.
foolserrandboy 9 hours ago [-]
Yeah, I don't understand this comparison. I've programmed for years in higher level languages professionally and never learned assembly and never got stuck because the higher level language was limited or doing something wrong.
Whenever I use an LLM I always need to review its output because usually there is something not quite right. For context I'm using VS copilot, mostly ask and agent mode, in a large brownfield project.
david-gpu 2 hours ago [-]
My career sat at the interface of hardware and software. We would often run into situations where the code produced by the compiler was not what we desired. This issue was particularly pronounced when we were transitioning some components from being written in assembly by hand vs using a compiler.
I think the parallels are clear for those of us who have been through this scenario.
utyop22 9 hours ago [-]
Exactly that's the trade-off.
People keep comparing higher-level programming languages to lower-level abstractions - these comparisons are absolutely false. The whole point of higher-level programming languages is for people to get away from working with the lower level stuff.
But with the way software engineers are interacting with LLMs, they are not getting away from writing code because they have to use what comes out of it to achieve their goal (writing and piecing together code to complete a project).
jplusequalt 7 hours ago [-]
In the previous scenario, programmers were still writing the code themselves. The compilers, if they were any good, generated deterministic code.
In our current scenario, programmers are merely describing what they think the code should do, and another program takes their description and then stochastically generates code based on it.
david-gpu 2 hours ago [-]
Compilers are (a) typically non-deterministic and, (b) produce different code from one version to the next, from one brand to the next, and from one set of flags to the next.
ModernMech 7 hours ago [-]
To some degree you're correct -- LLMs can be viewed as the kind of "sufficiently advanced" compiler we've always dreamed of. Our dreams didn't include the compiler lying to us though, so we have not achieved utopia.
LLMs are more like DNA transcription, where some percentage of the time it just injects a random mutation into the transcript, either causing am evolutionary advantage, or a terminal disease.
This whole AI industry right now is trying to figure out how to always get the good mutation, and I don't think it's something that can be controlled that way. It will probably turn out that on a long enough timescale, left unattended, LLMs are guaranteed to give your codebase cancer.
pavel_lishin 3 hours ago [-]
It definitely feels like a move towards management, which is something I've avoided for my entire career.
It's a perfectly cromulent approach and skillset - but it's a wildly different one.
Rinum 9 hours ago [-]
It's a change in mindset. AI is like having your own junior developer. If you've never had direct reports before where you have to give them detailed instruction and validate their code then you're right, it might end up more exhausting than just doing the work yourself.
broast 7 hours ago [-]
So basically what an engineering manager or product manager enjoys doing
ModernMech 7 hours ago [-]
It's not. And people are realizing that, which is causing them to bring back and reinvent aspects of software engineering to AI coding to make it more tolerable. People once questioned whether AI will replace all programming languages with natural language interfaces, it now looks like programming languages will be reinvented in the context of AI to make their natural language interface more tool-like.
ahoka 3 days ago [-]
From the masterpiece, Tragedy of the Man, describing the future where everything is done in the name of efficiency:
THE GREYBEARD
You left your workroom in great disarray.
MICHELANGELO
Because I had to fabricate the chair-legs
To the quality as poor as it can be.
I appeal’d for long, let me modificate,
Let me engrave some ornaments on it.
They did not permit. I wanted as a chance
The chair-back to change but all was in vain.
I was very close to be a madman
And I left the pains and my workroom, too. (stands back)
THE GREYBEARD
You get house arrest for this disorder
And will not enjoy this nice and warm day.
danielscrubs 2 days ago [-]
Can you explain why it is a masterpiece? Im just curious.
jwr 3 days ago [-]
In my experience, listening to music engages the creative part of your brain and severely limits what you can do, but this is not readily apparent.
If I listen to music, I can spend an hour CODING YEAH! and be all smug and satisfied, until I turn the music off and discover that everything I've coded is unnecessary and there is an easier way to achieve the same goal. I just didn't see it, because the creative part of my brain was busy listening to music.
From the post, it sounds like the author discovered the same thing: if you use AI to perform menial tasks (like coding), all that is left is thinking creatively, and you can't do that while listening to music.
freehorse 11 hours ago [-]
There is no “creative part of the brain” and even if there was listening to music would have nothing to do with it.
You may be experiencing getting to different understanding of sth when you switch context. Similar to when you are stack it may be better to go for a walk than keep your head on top of a piece of paper or screen. I have had many of my breakthroughs while taking a shit in the toilet in the midst of working. Others experience similar with showers and whatever.
Afaik most ppl listen to music during certain tasks because it helps focusing. Esp when working in a busy office it really helps me to listen to certain kinds of predictable music to keep me from getting distracted. It creates a sort of entrainment that helps with attention.
Some people find music itself distracting, I myself find some kinds of music distracting, or during certain types of tasks. Then it obviously it does not fill its purpose.
shaan7 3 days ago [-]
I describe it slightly differently. Similar to what the author described, I'll first plan and solve the problem in my head, lay out a broad action plan, and then put on music to implement it.
But, for me the music serves something akin to clocks in microcontrollers (and even CPUs), it provides a flow that my brain syncs to. I'm not even paying attention to the music itself, but it stops me from getting distracted and focus on the task at hand.
elliottkember 12 hours ago [-]
> discover that everything I've coded is unnecessary and there is an easier way to achieve the same goal
In my experience, there is no good shortcut to this realization. Doing it wrong first is part of the journey. You might as well enjoy the necessary mistakes along the way. The third time’s the charm!
Cthulhu_ 13 hours ago [-]
I don't think that's down to music per se, but a more generalized thing. Software developers love being in a flow state, some of them pursue it all the time (...guilty) and get frustrated when their job changes (e.g. moving towards management) so they spend less time in that flow state.
But also, this can create waste, in that people write the Best Code Ever in their flow state (while listening music or not), but... it wasn't necessary in the first place and the time spent was a waste. This can waste anything from an hour to six months of work (honestly, I had a "CTO" once who led a team of three dozen people or so who actually went into his batcave at home for six months to write a C# framework of sorts that the whole company should use. He then quit and became self-employed so the company had to re-hire him to make sense of the framework he wrote. I'm sure he enjoyed it very much though.)
bdhcuidbebe 7 hours ago [-]
Your experience suffers from confirmation bias.
sfn42 1 days ago [-]
I just think it's distracting. I get caught up listening to the lyrics and kind of mentally singing along, stuff like that which disrupts my thought and distracts from what I actually want to be thinking about.
I think this is individual, I have the same problem in social settings - if I'm having a conversation and a song I like is playing in the background I some times stop listening to the conversation and focus on the music instead, unintentionally.
My solution is to listen to music without vocals when I need to focus. I've had phases where I listen to classical music, electronic stuff, and lately I've been using an app I found called brain.fm which I think just plays AI generated lo-fi or whatever and there's some binaural beats thing going on as well that's supposed to enhance focus, creativity etc. I like it but some times I go back to regular music just because I miss listening to something I actually like.
bogtog 11 hours ago [-]
Same here on all fronts about distractions. I can't tell whether when people talk about listening to music while working/studying: (1) they mean music with no lyrics, (2) they are unserious and okay with their work being constantly interrupted, or (3) they can resist thinking about the lyrics.
Some work may allow for seamless pivoting between work vs. enjoyable distraction, e.g., a clerk, but I often hear about people listening to music in other contexts.
skydhash 8 hours ago [-]
The work is not always to implement some complicated algorithm. Sometimes it is just routine work. There's already so much noise outside so having the music give something for the brain to latch on instead of having to react to all those other stimulus. For me it's a playlist that I know very well, which then becomes background noise.
leptons 2 days ago [-]
I'm sorry but that's nonsense. Listening to music is not a creative process, it does not at all take away creativity from somewhere else.
I've never, ever, ever once in 40 years of coding listened to music while coding and later found the code "unnecessary" or anything of the sort.
I engage in many creative pursuits outside of coding, always while listening to music, and I can confidently say that music has never once interfered in the process or limited the result in any way.
DevKoala 3 days ago [-]
I’d probably drop GenAI before I dropped the music that allows me to focus. Also, at this stage of my career, I mainly code for fun, and blasting music across the house is part of it.
I use Zoom rather than Teams, but have no problems playing background music with Spotify. Just have to make sure that “share computer audio” is not enabled when sharing your screen. Also, when I was using the mic of my bluetooth headphones, any music played would be mono and lower quality due to bluetooth bandwidth. Since moving to using a dedicated mic on my desk, the bluetooth headphones are output only and back to good quality stereo (MacOSX and Bose QC35).
tomjakubowski 2 days ago [-]
Not too long ago, I installed a system mixer/EQ on my work computer so I could mix ambient-ish music with Zoom calls while giving space to the (meeting room's) vocals. It works great.
hn_throw2025 2 days ago [-]
Sounds great…
I’m a hobbyist audio engineer so can’t resist tinkering.
My mic input goes to Rogue Amoeba’s Audio Hijack which allows a chain of VST plugins to be used. I use a gentle noise gate, followed by Supertone Clear. This is excellent for removing any noise mixed in with my voice. It handles the dehumidifier near me with ease, and can also handle the portable aircon on heatwave days, which can be very loud. Next in the chain is some gentle and transparent compression, and then the output goes to the free Blackhole virtual audio device. Zoom then picks up that device. Tweaked Zoom settings and “original sound for musicians” button then stops it from compromising the sound as much as possible. I am tempted to have some EQ plugin tweaks too, but I love the character of the mic so I don’t mess around with it.
EQing the music played sounds interesting. I’ll look at the options. I tend to just have it at a level low enough that I can hear all speakers on the call.
bravetraveler 2 days ago [-]
My position isn't due to incapability
2 days ago [-]
nxpnsv 3 days ago [-]
they can't hear if it is them or music on my phones...
codr7 15 hours ago [-]
Robots don't listen to music, I'm pretty sure that's the longer term plan.
nowittyusername 7 hours ago [-]
Chill instrumental and lo-fi are your friends now. I also noticed I couldn't listen to music anymore but that's only because of vocals. Anything without language works just fine, especially at low volume.
energy123 3 days ago [-]
> writing a blurb that contains the same mental model
Good nugget. Effective prompting, aside from context curation, is about providing the LLM with an approximation of your world model and theory, not just a local task description. This includes all your unstated assumptions, interaction between system and world, open questions, edge cases, intents, best practices, and so on. Basically distill the shape of the problem from all possible perspectives, so there's an all-domain robustness to the understanding of what you want. A simple stream of thoughts in xml tags that you type out in a quasi-delirium over 2 minutes can be sufficient. I find this especially important with gpt-5, which is good at following instructions to the point of pedantry. Without it, the model can tunnel vision on a particular part of the task request.
ForHackernews 3 days ago [-]
Hard to tell if this is parody or not but I chuckled at the idea of replacing tedious programming with a "simple stream" of handwritten XML.
energy123 3 days ago [-]
It's not parody. I'm trying to provide the LLM with what's missing, which is a theory of how the system fits into the world: https://pages.cs.wisc.edu/~remzi/Naur.pdf
Without this it defaults to being ignorant about the trade-offs that you care about, or the relevant assumptions you're making which you think are obvious but really aren't.
The "simple stream" aspect is that each task I give to the LLM is narrowly scoped, and I don't want to put all aspects of the relevant theory that pertains just to that one narrow task into a more formal centralized doc. It's better off as an ephemeral part of the prompt that I can delete after the task is done. But I also do have more formal docs that describe the shared parts of the theory that every prompt will need access to, which is fed in as part of the normal context.
jiggunjer 15 hours ago [-]
So like:
<prompt>
<intent>Generate a metaphor-rich essay on the fragility of digital memory in the age of infinite storage</intent>
<assumptions>
<tech>LLMs understand metaphor but may default to literal interpretations unless nudged</tech>
<audience>Reader is tech-savvy but emotionally attuned</audience>
<bias>We romanticize loss and impermanence; permanence is sterile</bias>
<style>Poetic, but not florid. Think Calvino meets cyberpunk.</style>
</assumptions>
<worldModel>
<digitalMemory>
<definition>Not just data retention, but emotional proxies, identity scaffolding</definition>
<paradox>We remember too much, and thus forget how to forget</paradox>
<analogy>Digital memory is a hoarder’s attic with perfect climate control</analogy>
</digitalMemory>
<humanMemory>
<contrast>Fuzzy, selective, narrative-driven</contrast>
<value>Its gaps are what make it beautiful</value>
</humanMemory>
<systemInteraction>
<modelRole>LLM is not just a scribe, but a co-dreamer</modelRole>
<risk>Model may over-index on coherence, losing the emotional fray</risk>
</systemInteraction>
</worldModel>
<openQuestions>
<q>Can forgetting be designed into digital systems?</q>
<q>Is nostalgia a compression algorithm?</q>
<q>What does it mean to "misremember" in a world of perfect logs?</q>
</openQuestions>
<edgeCases>
<case>Model generates a dystopia instead of a melancholic tone</case>
<case>Model literalizes metaphors (e.g., "clouds forget")</case>
<case>Model assumes user wants a solution, not a meditation</case>
</edgeCases>
<bestPractices>
<tip>Use metaphor as scaffolding, not decoration</tip>
<tip>Let ambiguity breathe—don’t resolve every tension</tip>
<tip>Favor rhythm over precision in sentence structure</tip>
</bestPractices>
<meta>
<duration>Prompt typed in 2 minutes, no edits</duration>
<mood>Sleep-deprived but lucid</mood>
<goal>To make the model feel like it’s dreaming with me</goal>
</meta>
</prompt>
adithyassekhar 9 hours ago [-]
Here’s a first draft of your essay—leaning into metaphor as scaffolding, not ornament, and keeping the tone between elegy and cyberpunk fable:
---
### The Fragility of Digital Memory in the Age of Infinite Storage
We live inside an archive that never closes. Hard drives hum like cathedrals of perfect recall, cloud servers drift like silent librarians in orbit, and every keystroke is another bone set in amber. Memory, once a trembling candle subject to drafts and time, now runs on battery backups and redundant arrays. Forgetting has been engineered out of the system.
And yet, the paradox: by remembering everything, we begin to lose the art of remembering at all. Human memory is a cracked mirror—crooked, selective, shimmering with distortions that make us who we are. Its gaps are the negative space where meaning lives. The story of a childhood is not its complete inventory but its torn edges, the blurred photograph, the half-forgotten lullaby whose missing notes we hum into being.
Digital memory, by contrast, is a hoarder’s attic with perfect climate control. Nothing rots, nothing fades, nothing dares to slip away. Every draft email unsent, every unflattering selfie, every midnight search query—all preserved in pristine sterility. The archive is so complete that it ceases to be a story. It becomes a warehouse of moments that never learned how to decay.
But memory without decay is less than human. Nostalgia itself might be the first compression algorithm: a lossy filter that turns clutter into resonance. Without the soft erasures of time, experience calcifies into raw data, and raw data has no mercy.
Perhaps what we need are systems that misremember. Databases that dream. Algorithms that allow certain files to fray at the edges, to grow fuzzy like old film reels, to tint themselves with the sepia of emotion rather than the fluorescence of metadata. A kind of deliberate forgetting—not loss as failure, but loss as design.
Because what is fragility if not the pulse behind memory’s worth? The hard drive never gasps, never sighs; only the human mind knows the ache of absence, the sweetness of something slipping away. If the future is an archive without end, perhaps our task is to reintroduce the possibility of disappearance. To let silence seep between the entries. To remind the machines that to truly remember, one must first learn how to forget.
---
Do you want me to lean this more toward *meditation* (open-ended, drifting) or *argument* (provoking design questions like “can forgetting be engineered”)?
ForHackernews 8 hours ago [-]
full slop. I kind of worry that long-term exposure to content like this will reduce humans to 8th graders doing a book report on books they haven't read.
> But memory without decay is less than human.
How is it less than human? By definition, the undecayed memory is more complete.
> Nostalgia itself might be the first compression algorithm: a lossy filter that turns clutter into resonance.
What is this even supposed to mean? I guess the idea is something here like "fuzzy" memory == "compression" but nostalgia is an emotional response - we're often nostalgic about clear, vivid memories, experiences that didn't lose their texture to time.
> Without the soft erasures of time, experience calcifies into raw data, and raw data has no mercy.
Eh... kinda. Calcifies is the wrong word here. Raw data doesn't have mercy, but lossily-compressed data is merciful? Is memory itself merciful? Or is it a mercy for the rememberer to be spared their past shames?
So much AI slop is like this: it's just words words words words without ideas behind them.
3 days ago [-]
october8140 3 days ago [-]
What kind of projects are people doing that are feeling the increased velocity?
elros 3 days ago [-]
Whenever I need some sort of quick data pipeline to modify some sort of file into another format, or do some batch transformation, or transform some sort of interface description into another syntax, or things like that, that would normally require me to craft a grep, awk, tr, etc pipeline, I can normally simply paste a sample of the data and with a human language description get what I need. If it’s not working well I can break up the steps in smaller steps.
In my experience, it seems the people who have bad results have been trying to get the AI to do the reasoning. I feel like if I do the reasoning, I can offload menial tasks to the AI, and little annoying things that would take one or two hours start to take a few minutes.
That very quickly adds up to some real savings.
theshrike79 3 days ago [-]
AI is a force multiplier for experienced people.
The ones who know what they want to do, how it should be done, but can't really be arsed to read the man pages or API docs of all the tools required.
These people can craft a prompt (prompt engineering :P) for the LLM that gets good results pretty much directly.
LLMs are garbage in garbage out. Sometimes the statistical average is enough, sometimes you need to give it more details to use the available tools correctly.
Like the fact that `fd` has the `-exec` and `--exec-batch` parameters, there's no need to use xargs or pipes with it.
stavros 3 days ago [-]
Every kind of project is faster with AI, because it writes the code faster.
Then you have to QA it for ages to discover the bugs it wrote, but the initial perception of speed never leaves you.
I think I'm overall slower with AI, but I could be faster if I had it write simple functions that I could review one by one, and have the AI compose them the way I wanted. Unfortunately, I'm too lazy to be faster.
theshrike79 3 days ago [-]
It's like working with a junior coder or an offshore consultant that always says yes.
Of course you need to check their work, but also the better your initial project plan and specifications are, the better the result.
For stuff with deterministic outputs it's easy to verify without reading every single line of code.
stavros 3 days ago [-]
Yeah, I mostly tend to work on web apps, where it's pretty hard to test all the interactions, so I'm hit by the bugs more often.
theshrike79 2 days ago [-]
With web apps playwright-mcp[0] is essential IMO. It lets the AI Agent check its own work before claiming it's done.
With that it can see any errors in the console, click through the UI and take screenshots to analyse how it looks giving it an independent feedback loop.
That's fantastic, thank you! I've had to do all that manually, this sounds like it'll save me a lot of time.
martin_a 3 days ago [-]
Pretty much what somebody else said: AI takes over simple tasks, the "fluff" around the business logic, error handling, stuff like that, so I can focus on doing the harder stuff at the core.
theshrike79 3 days ago [-]
Exactly!
90% of what the average (or median) coder does isn't in any way novel or innovative. It's just API Glue in one form or another.
The AI knows the patterns and can replicate the same endpoints and simple queries easily.
Now you have more time to focus on the 10% that isn't just rehashing the same CRUD pattern.
rimunroe 2 days ago [-]
> 90% of what the average (or median) coder does isn't in any way novel or innovative. It's just API Glue in one form or another.
I hear this from people extolling the virtue of AI a lot, but I have a very hard time believing it. I certainly wouldn't describe 90% of my coding work as boilerplate or API glue. If you're dealing with that volume of boilerplate/glue, isn't it incumbent upon you to try and find a way to remove that? Certainly sometimes it isn't feasible, but that seems like the exception encountered by people working on giant codebases with a very large number of contributors.
I don't think the work I do is innovative or even novel, but it is nuanced in a way I've seen Claude struggle with.
theshrike79 2 days ago [-]
To be more exact, 90% of the _code_ I write is mostly just different types of API glue. Get data from this system, process it and put it in another system.
It's the connectors that are 90-95% AI chow, just set it to task with a few examples and it'll have a full CRUD interface for your data done while you get more snacks.
Then you can spend _more_ of your limited time on the 10% of code that matters.
That said, less than 50% of my actual time spent on the clock is spent writing code. That's the easiest part of the job. The rest is coordinating and planning and designing.
rimunroe 2 days ago [-]
> To be more exact, 90% of the _code_ I write is mostly just different types of API glue
I assumed you were only talking about the actual code. It still seems really odd. Why is there so much unavoidable boilerplate?
theshrike79 2 days ago [-]
Because I need to have a controller that does CRUD operations.
It has a specific amount of code I need to write just to add the basic boilerplate of receiving the data and returning a result from the endpoint before I can get to the meat of it.
IIRC there are no languages where I can just open an empty file and write "put: <business logic>" and it magically knows how to handle everything correctly.
skydhash 8 hours ago [-]
That's why we have snippets and code generators for those. And even in the absence of that, I usually copy code from some other place and gut it out to make place for the new logic. This can be done in 30 seconds or less if the code is organized.
> IIRC there are no languages where I can just open an empty file and write "put: <business logic>" and it magically knows how to handle everything correctly.
Are you sure it's done correctly? Take something like timestamps, or validations: It's easy to get those wrongs.
rimunroe 1 days ago [-]
Does the "<business logic>" part involve a bunch of irreducible boilerplate too or something? What's it like?
If it doesn't, then I feel like even in the JavaScript world of 2015 you could write "app.put("/mypath", business_logic)" and that would do the trick, and that was a very immature language ecosystem.
guappa 13 hours ago [-]
Where I work there are like 2x as many front end developers as there is need for. They spend an insane amount of time doing meetings, they require approval of 2 different people for every simple CSS change.
Their job is to do meetings, and occasionally add a couple of items to the HTML, which has been mostly unchanged for the past 10 years, save for changing the CSS and updating the js framework they use.
energy123 3 days ago [-]
I'm slowed down (but perhaps sped up overall due to lower rewrites/maintenance costs) on important bits because the space of possibilities/capabilities is expanded, and I'm choosing to make use of that for some load bearing pieces that need to be durable and high quality (along the metrics that I care about). It takes extra time to search that space properly rather than accept the first thing that compiles and passes tests. So arguably equal or even lower velocity, but definitely improved results compared to what I used to be capable of, and I'm making that trade-off consciously for certain bits. However that's the current state of affairs, who knows what it'll look like in 1-2 years.
cluckindan 3 days ago [-]
How do you know they’re durable and high quality?
energy123 3 days ago [-]
I do it based on my subjective judgement, somewhat informed by quantitative measurements of metrics I care about like throughput.
nbaugh1 9 hours ago [-]
Greenfield development of small web apps. I’m familiar enough with everything that I can get something up and running on my own, but I don’t do it regularly so I need to read a lot of docs to be up to date. I can describe the basic design and requirements of an app and have something like Claude Code spit out a prototype in a couple of hours
staticautomatic 3 days ago [-]
I’m building a moderately complex system with FastAPI + PG + Prefect executing stuff on Cloud Run, and so long as I invest in getting the architecture and specs right, it’s really a dream how much of the heavy lifting and grunt work I can leave to Claude Code. And thank god I don’t have to manage Alembic by myself.
CalRobert 3 days ago [-]
Random example:
I set up a model in DBT that has 100 columns. I need to generate a schema for it (old tools could do this) with appropriate tests and likely data types (old tools struggled with this). AI is really good at this sort of thing.
Shorel 6 hours ago [-]
And many tools which are not AI are also really good at this sort of thing.
theshrike79 3 days ago [-]
There's a local website that sells actual physical Blu-rays. Their webshite is a horror show of Javascript.
I had Claude Code build me a Playwright+python -based scraper that goes through their movie section and stores the data locally to an sqlite database + a web UI for me to watchlist specific movies + add price ranges to be alerted when it changes.
Took me maybe a total of 30 minutes of "active" time (4-5 hours real-time, I was doing other shit at the same time) to get it to a point where I can actually use it.
Basically small utilities for limited release (personal, team, company-internal) is what AI coding excels at.
Like grabbing results from a survey tool, adding them to a google sheet, summarising the data to another tab with formulas. Maybe calling an LLM for sentiment analysis on the free text fields.
Half a day max from zero to Good Enough. I didn't even have to open the API docs.
Is it perfect? Of course not. But the previous state was one person spending half a day for _each_ survey doing that manually. Now the automation runs in a minute or so, depending on whether Google Sheets API is having a day or not =)
gonzo41 3 days ago [-]
CRUD work, Boilerplate config for network stuff, converting lots of oracle stored procedures. It's saving me days.
mythrwy 2 days ago [-]
It's hard to get in the zone with an LLM doing crazy stuff.
For instance this week when setting up a Django/Wagtail project GPT helpfully went ahead and created migration files in text instead of "makemigrations". Otherwise it did a bang up job and saved me a couple of hours.
Just no way I can get in the zone wrangling that kind of thing all day.
But I'm not sure getting in the coding zone frequently was all that mentally healthy so oh well.
mckn1ght 3 days ago [-]
It’s a lot more high-level executive functioning now, instead of grinding through endless syntax and boilerplate. Easy to mindlessly code to music, much harder to think about what you want to do next, and evaluate if the result you just got is what you really wanted.
TrietNg 2 days ago [-]
I encounter a problem which is my social media usage increase. The time when you wait for the agent to write code is kinda silly :) You can not switch to do other things as it will make your focus shift away from the code. So usually I just dumb scroll for 1 minute
djmips 16 hours ago [-]
You're expected to run several projects in parallel with latency hiding like a human GPU. No downtime!
whatamidoingyo 2 days ago [-]
For me, it's 1 minute bullet chess.
17 hours ago [-]
nemoniac 3 days ago [-]
The line that stood out for me was that "a 4-hour session of AI coding is more cognitively intense than a 4-hour session of non-AI coding."
Many programmers are rejecting AI coding because they miss the challenge they enjoy getting from conventional programming but this author finds it even more challenging. Or perhaps challenging in a different way?
kitku 3 days ago [-]
There is a distinction I believe between challenging and focusing. The difference lies in difficulty (the former being more dificult) and workload (the latter being more intellectualy labor intensive), which is an interesting approach to intellectual menial labor as distinct from intellectual craft.
sfn42 1 days ago [-]
I think there are (at least) two types of programmer - I am the kind of programmer who wants everything done right. Others don't care as long as it works and the boss is happy.
I suspect that the type of programmer who enjoys vibe coding is the latter. For me it's pretty tiring to explain everything in excruciating detail, it's often easier to just write the code myself rather than explain in English how to write it.
It feels like I am just doing the hard part of programming all the time - deciding how the app should work and how the code should be structured etc, and I never get those breaks where I just implement my plan.
bluefirebrand 15 hours ago [-]
I suspect the difference lies in people who think in code versus people who translate their thoughts into code
I think in code and programming concepts when I am writing software . I don't really know how to explain that, but I don't often feel like there is any friction between my thoughts and the code I make
I think that many coders do not have this. They have an extra "translation" step that introduces friction into their workflow
I don't experience this friction, so LLM coding introduces new friction that I don't like
They do experience this friction, so LLM coding doesn't introduce new friction for them, it may transform their previous friction into a new form that is easier for them to navigate
I don't know. Maybe I'm talking out my ass, this is just a random theory based on no real evidence
skydhash 8 hours ago [-]
Another datapoint of one.
It's not really that I think in code. It's more like code is as much as a language to me as writing english, or holding the pencil to draw something. I got a change request, or I read something from the docs, and the the mental concept I have realign itself to the new knowledge. Getting code out is always effortless. There's no difference between
return the list of names of all the books that have the fantasy tag
Yes, this is exactly what I mean when I say "thinking in code". I feel it isn't accurate either, but it was the best way I had to describe it
More or less just that there is little to no friction for me to think a thought and write the code compared to "translating" the thought into code
tamimio 3 days ago [-]
That's an argument I had with a friend last year. I told him generative AI will make writing code easier, but the life of whoever is writing it far worse. Because writing code without using AI is done with some sort of due diligence: you memorize some stuff, look up other stuff in the docs or online, and you take some time actually solving the problem you have. If you succeed, you would've spent the needed time at YOUR pace, with an intrinsic reward of feeling good that you achieved something. With AI, on the other hand, you are in semi-cheat mode, throwing prompts after prompts and now you are trying to catch someone/something else's pace, zero reward, and more mentally exhausted.
The best approach is to use AI only when you are stuck and looking for potential solutions, but we all know that is not going to happen unless you have extreme self-control.
daemin 9 hours ago [-]
Kind of sounds like using LLMs to generate code is like eating USA junk/fast food. It is quick and tasty, and you get a dopamine rush from that sugar and fat in your body, but it leaves you feeling unsatisfied and unsatiated.
fearface 3 days ago [-]
I let the AI first generate a outline of how it would do it as markdown. I adapt this and then let it add details into additional markdown files about technical stuff, eg how to use a certain sdk and so on. I correct these all.
And then I let the AI generate the classes of the outline one by one.
redog 6 hours ago [-]
Listen to dance music or classical without the lyrics....I've NEVER been able to code/work and listen to music with language/lyrics. Words overwhelm my mental bandwidth. Same shit happens to me with the piano. Please don't speak while I try to play.
Narciss 2 days ago [-]
Fun fact: “praf” (seen in the website domain, praf.me) in Romanian means dust.
If you say “you are praf” in Romanian it means that you are f*cked, wasted, done for, etc.
lioeters 16 hours ago [-]
The same word is "prach" in Czech: dust, powder. The "ch" sounds like "kh" (soft k?). In Czech slang prachy means cash, money.
pona-a 8 hours ago [-]
In Russian прах means ashes.
sublinear 3 days ago [-]
> For frontend code and my side projects, AI coding seems to be even more effective and actually reduces the cognitive load, winning in all dimensions.
Can we see this frontend code? For research purposes, of course.
codr7 15 hours ago [-]
Doing things faster comes way down the priority list where I work. We spend a lot of resources on understanding and improving the code, as well as breaking knowledge silos.
Because the people running the show are experienced software devs, not AI clowns.
dakiol 3 days ago [-]
What happened to coding for joy in your free time? At work I do whatever the company wants as long as I get my money at the end of the month. Java? Sure boss. Golang? Let’s do it. LLMs? Whatever you want. TDD? Yep.
At home I still plan and devise my own worlds with joy. I may use LLMs for boring or repetitive tasks, or help or explanation; but I still can code better than the day before.
As usual, work != career.
stuaxo 2 days ago [-]
Even in the fun stuff there's dog work to do and the LLMs can definitely help there.
Buttons840 8 hours ago [-]
I think AIs should be combined with some sort of spaced-repetition or tutoring software.
This way we can allow AIs to do our work, but the AI can also tutor us and teach us the things necessary to verify their work.
ai_assisted_dev 3 days ago [-]
It definitely changed how I get into flow state for me. But music still works, if not even better when coding with AI (listening to: techno, electro, edm). Generally my flow is to sit down, make a small plan of what I will work on, fire off 2 agents to work on different parts of the code that are lower hanging fruits (takes 2-10 mins for them to complete). Then while this is busy, map out some bigger tasks.
Agents finish, I queue them up with new low hanging fruits, while I architect the much bigger tasks, then fire that off -> Review smaller tasks. It really is a dance, but flow is much easier achieved when I do get into it; hours really just melt together. The important thing to do is to put my phone away, and block all and any social media or sites I frequent, because its easy to get distracted when agents aren just producing code and you're sitting on the sidelines.
AaronAPU 2 days ago [-]
I did that for 2 hours yesterday and then scrapped everything the agents did because it didn’t work and left everything in disarray.
ai_assisted_dev 2 days ago [-]
It takes quite the practice. At least I have been shipping stuff to users like this for the entire year.
imiric 14 hours ago [-]
That's not the same flow state experienced by programmers.
While programming, it's possible to get into a trance-like state where the program's logic is fully loaded and visible in your mind, and your fingers become an extension of your mind that wire you directly to the machine. This allows you to modify the program essentially at the speed of thought, with practically zero chance of producing buggy code. The programmer effectively becomes a self-correcting human interpreter.
Interrupting someone in this state is incredibly disruptive, since all the context and momentum is lost, and getting back into the state takes time and focus.
What you're describing is a general workflow. You can be focused on what you're doing, but there's no state loaded into memory that makes you more efficient. Interruptions are not disruptive, and you can pick up exactly where you left off with ease. In fact, you're constantly being interrupted by those agents running in the background, when they finish and you give them more work. This is a multitasking state, not flow.
So the article is correct. It's not possible to get into a flow state while working with ML tools. This is because it is an entirely different activity from programming that triggers different neural pathways.
ai_assisted_dev 10 hours ago [-]
Nice way of gatekeeping "flow state of programmers", considering I have been a software engineer for the past 2 decades. So I have experienced quite some flow states in my life, and this is no different.
imiric 9 hours ago [-]
Not gatekeeping, just pointing out that they're different activities with very different experiences. What you're talking about and what the article is talking about are different things.
When using ML tools you have no deep understanding of the behavior of the program, since you don't understand the generated code. If you bother to review the code, that is a huge context switch from anything you were doing previously. This doesn't happen during deeply focused programming sessions.
You may have been a software engineer for decades without ever experiencing the programming flow state. I'm not passing judgement.
icetank 3 days ago [-]
My theory as a none scientist is that you need a different part of the brain to think about AI prompts compared to coding yourself. Or maybe that whatever though process you need for coding intersects with the part that enjoys listening to music. And because of that intersection you can't focus on both at the same time.
stgr_codes 11 hours ago [-]
I think that we should start to doubt the idea that "AI made people code faster", that's not the case for a lot of people, if you know the requisites and have an idea in mind music make you code faster because it help focus.
iamflimflam1 3 days ago [-]
He’s talking about being in a state of flow - it’s a lovely feeling when you can get into it.
randcraw 2 days ago [-]
CAN you get into a state of flow when directing an LLM? I don't have a lot of experience using LLMs to code, but it always feels like I'm coaching a junior staff member. No way to flow that, IMHO.
bluefirebrand 15 hours ago [-]
I tend to agree. Even the LLM autocomplete in Cursor feels so intrusive that I cannot get into flow when it is turned on
conductr 3 days ago [-]
It’s the opposite for me. I’ve never been able to listen to music while coding as my thoughts would drown it out or it would keep me from thinking so I’d shut it off. However if I am vibe coding my brain is basically idle and can handle some music
globular-toast 3 days ago [-]
I don't listen to music while doing code reviews either. It also happens to be my least favourite part of the job. The LLM agents just make it feel like I'm constantly code reviewing and I don't think it makes me more productive overall.
dep_b 14 hours ago [-]
I cannot run or code to music. I might be playing music while doing so, but it's super distracting and it's basically just me working at 50% while enjoying myself. I worked with a bunch of guys that always always always had a web radio pumping cheesy hard style stuff all day long.
Got nothing done.
mulhoon 10 hours ago [-]
Same. I’ve been a coder over 25 years. I love music and am a musician, but I can’t listen to music while coding, I need silence. Too distracting. In fact music is often distracting for me during conversations, if it’s on in the background, say in a shop or bar.
johnfn 3 days ago [-]
I'm curious which models the OP is using that produce code so quickly and accurately? I mostly use Claude Code, which is accurate, but it isn't very fast. I certainly don't feel like I'm producing piles of code with it.
satisfice 2 days ago [-]
Who is testing your code? No one? You?
This is a other “trust me” post about AI.
Mikhail_Edoshin 15 hours ago [-]
I cannot code to music at all. I miss either the music or the code or keep switching and get tired. I can do a mechanical job, e.g. adding records to a database.
(I also find AI repulsive and have no intention to engage in anything AI-related. Recently I turned off AI "help" in DDG.)
neebz 13 hours ago [-]
Finally someone emphasized upon the cognitive load of AI-assisted coding.
It definitely makes me faster but it's consistent prompt->code-review->prompt->code-review->scratch->prompt-code->review cycle which just requires extreme focus.
time0ut 10 hours ago [-]
For me, it just requires different genres of music.
Brainstorming with LLM? Literal background noise like distant thunderstorm.
Pairing with LLM? Classical.
Solo? Still technical death metal.
mac-mc 3 days ago [-]
I found I couldn't listen to music with words in them while coding. Maybe try wordless music, or music that is in a language you don't understand.
GLdRH 3 days ago [-]
That's why metal works well here.
winrid 3 days ago [-]
JimTV on YT has great programming music.
mckn1ght 3 days ago [-]
Exactly, came here to say this, it happened long ago for me. Classical, jazz, electronica… all great for coding and vibing alike, for me.
Absolutely—I feel like I can ship at a crazy velocity now, like I have a team of interns at my disposal to code up my every silly demand.
It reminds me this scene:
`Cut my eggs`
`Your eggs are cut sir!'
`Cut my milk'
`I can't sir, it's liquid'
`Imbecile! Freeze it, then cut it!'
zwnow 3 days ago [-]
> Absolutely—I feel like I can ship at a crazy velocity now, like I have a team of interns at my disposal to code up my every silly demand.
I also wonder what type of simple CRUD apps people build that have such a performance gain? They must be building well understood projects or be incredible slow developers for LLMs to have such an impact, as I cant relate to this at all.
duncanfwalker 3 days ago [-]
I wonder whether we'll be able to look back on this period in 10 years time and save definitively whether the wide spectrum of responses to LLMs was perception or real feature of our differing jobs.
shermantanktop 3 days ago [-]
Different people have different jobs doing different things? Doesn’t seem shocking to me.
But I certainly wouldn’t assume that other people’s jobs are simple or boring just because they don’t look like yours.
zwnow 2 days ago [-]
Given that AI tools do not deliver well on barely understood fields one can only assume people work on simple things.
Which is absolutely no shame. But people shouldn't expect these gains for their job if they work in less understood environments.
Most non CRUD AI code implementations are flawed/horrendous.
shermantanktop 2 days ago [-]
That’s right, it’s good at things that are common. If your job is mostly filled with uncommon tasks, it won’t be good at helping you.
But for the rest of us, who have a mix of common/boring and uncommon/interesting tasks, accelerating the common ones means spending more time (proportionally) on less common tasks.
Unfortunately we don’t seem to great at classifying tasks as common or uncommon, and there are bored engineers who make complex solutions just to keep their brain occupied.
winrid 3 days ago [-]
There are people using Claude to make entire 3d MMO games, so ...
p0w3n3d 1 days ago [-]
do you have any particular game in mind?
ori_b 7 hours ago [-]
AI coding is the worst part of management without any of the rewards.
glitchc 8 hours ago [-]
I have a solution: Ask the AI to play music while it codes for you.
dexter_it 6 hours ago [-]
Optimistic about AI or not, this is sad.
zachwills 2 days ago [-]
I actually still listen to music heavily when in the zone with AI coding. Totally agree that the focus time feels much more intense now than it did before AI.
triyambakam 3 days ago [-]
I dunno, it is a bit different leveraging a model, but I still listen to music coding. It does depend on the music. I need to listen to really brutal stuff (Arsis, Thyrfing, Dissection, etc.) to focus, though
shmerl 3 days ago [-]
Do things the way you like instead of saying "I miss it".
thatjoeoverthr 10 hours ago [-]
Same. Part of the old experience of building applications is the typing. You have some notion in your head of what you want, and now you've got to go _type_ for six hours to get some effect. This becomes a kind of "manual skill" and you can do it with music. Like running.
That's gone.
My impression of myself is the high leverage strategic work was always subconscious, but I never had to notice; my hands were busy so it felt like I'm "working".
And with the AI typing for me, it doesn't necessarily go that much faster. I've got to go lift weights, play my favourite vintage racing slop (Rush 2) or take a long shower. At some point the plan is revealed to me and I've got to poke the computer and make it do the next thing.
Very strange experience. All of it.
drmpeg 3 days ago [-]
I've never bothered listening to music while coding. If I'm in the zone, it's entirely extraneous and I don't even hear it.
At my first job in Silicon Valley, I used to code right on the production floor totally oblivious to what was going on.
alex1138 17 hours ago [-]
Play techno with high BPM and watch your commits skyrocket
milly171002 2 days ago [-]
I like vibe coding, and I also enjoy listening to music.
cainxinth 1 days ago [-]
I can work to music anytime as long as it has no lyrics.
crawsome 6 hours ago [-]
Not sure if it's been declared generally yet, but debugging is harder with AI.
Once your requests start to veer away from the direction you wanted (Especially if at-any-point, you transition to Cursor's "Free" mode, and it misunderstands and bulldozes all your previously-working features)
Not only is it harder, the physical stress caused by debugging with AI is something new. It gets some requests so-incredibly-wrong and follows directions totally-contrary, your brain forgets it's talking to a computer, and reacts in a way you would to a person who did all the wrong things here.
Version control has never been so important. I never use cursor without it. And even then, sometimes I just open the client, and a bunch of files changed.
excalibur 3 days ago [-]
The answers are in the footnote, switching to frontend is the way.
blueboo 8 hours ago [-]
Coding to music was a flag you were just twiddling. People confuse flow with a pleasant surface engagement. Deep problem solving is when you sit forward, turn the music down, and bring up the big cognitive guns.
sneak 11 hours ago [-]
My take on this is that, while it’s harder to read code than it is to write it - it’s still faster to read code than to write it (it’s just not as much fun).
I suspect it doesn't matter how we feel about it mind you. If it's going to happen it will, whether we enjoy the gains first or not.
* setting aside whether this is currently possible, or whether we're actually trading away more quality that we realise.
This is what happens with big technological advancements. Technology that enables productivity won’t free people time, but only set higher expectations of getting more work done in a day.
That dumb attitude (which I understand you’re criticising) of “more more more” always reminds me of Lenny from the Simpsons moving fast through the yellow light, with nowhere to go.
https://www.youtube.com/watch?v=QR10t-B9nYY
> I suspect it doesn't matter how we feel about it mind you. If it's going to happen it will, whether we enjoy the gains first or not.
That is quite the defeatist attitude. Society becoming shittier isn’t inevitable, though inaction and giving up certainly helps that along.
If the structures and systems that are in-place only facilitate life getting more difficult in some way, then it probably will, unless it doesn't.
Housing getting nearly unownable is a symptom of that. Climate change is another.
You're right in general, but I don't think that'll save you/us from OP's statement. This is simple economic incentives at play. If AI-coding is even marginally more economically efficient (i.e. more for less) the "old way" will be swept aside at breathtaking pace (as we're seeing). The "from my cold dead hands" hand-coding crowd may be right, but they're a transitional historical footnote. Coding was always blue-collar white-collar work. No-one outside of coders will weep for what was lost.
On the scale I’ve been doing this (20 years), that hasn’t been the case.
Rails was massively more efficient for what 90% of companies where building. But it never had anywhere near a 90% market share.
It doesn’t take 1000 engineers to build CRUD apps, but companies are driven to grow by forces other than pure market efficiency.
There are still plenty of people using simple text editors when full IDEs have offered measurable productivity boosts for decades.
>(as we’re seeing)
I work at a big tech company. Productivity per person hasn’t noticeably increased. The speed that we ship hasn’t noticeably increased. All that’s happening is an economic downturn.
But AI seems to be different in that it claims to replace programmers, instead of augment them. Yes, higher productivity means you don't have to hire as many people, but with AI tools there's specifically the promise that you can get rid of a bunch of your developers, and regardless of truth, clueless execs buy the marketing.
Stupid MBAs at big companies see this as a cost reduction - so regardless of the utility of AI code-generation tools (which may be high!), or of the fact that there are many other ways to get productivity benefits, they'll still try to deploy these systems everywhere.
That's my projection, at least. I'd love to be wrong.
But no matter how hard cost cutters wanted to, they were never able to actually reduce the total number of devs outside of major economic downturns.
I suspect we'll find that the amount of technical debt and loss of institutional knowledge incured by misuse of these tools was initially underappreciated.
I don't doubt that the industry will be transformed, but that doesn't mean that these tools are a panacea.
I also specifically used the term "misuse" to significantly weaken my claim. I mean only to say that the risks and downsides are often poorly understood, not that there are no good uses.
If you're a salaried or hourly employee, you aren't paid for your output, you are paid for your time, with minimum expectations of productivity.
If you complete all your work in an hour... you still owe seven hours based on the expectations of your employment agreement, in order to earn your salary and benefits.
If you'd rather work in an output based capacity, you'll want to move to running your own contacting business in a fixed-bid type capacity.
My company has been preparing for this for a while now, I guess, as my backlog clearly has years' worth of work in it and positions of people who have left the org remain unfilled. My colleagues at other companies are in a similar situation. Considering round after round of layoffs, if I got ahead a little bit and found that I had nothing else to do, I'd be worried for my job.
Society becoming shittier isn’t inevitable
Yes, I agree, but the deck is usually stacked against the worker, especially in America. I doubt this will be the issue that promotes any sort of collectivism.
This feels like kicking someone when they’re down! Given the current state of corporate and political America, it doesn’t look likely there will be any pressure for anything but enshittification to me. Telling people at the coal face to stay cheerful seems unlikely to help. What mechanism do you see for not giving up to actually change the experience of people in 10 ish years time?
That isn't what they said tho. They said you have to do something, not that you should just be happy. Doing something can involve things that historically had a big impact in improving working conditions, like collective action and forming unions.
The opposite advice would be: "Everything's fucked, nothing you can do will change it, so just give up." Needless to say that is bad advice unless you are a targeted individual in a murderous regime or similar.
Realizing that attitude in myself at times has given me so much more peace of mind. Just in general, not everything needs to be as fast and efficient as possible.
Not to mention the times where in the end I spend a lot of time and energy in trying to be faster only to end up with this xkcd: https://xkcd.com/1319/
As far as LLM use goes, I don't need moar velocity! so I don't try to min max my agentic workflow just to squeeze out X amount more lines code.
In fact, I don't really work with agentic workflows to begin with. I more or less still use LLMs as tools external to the process. Using them as interactive rubber duckies. Things like deciphering spaghetti code, do a sanity check on code I wrote (and being very critical of the suggestions they come up with), getting a quick jump start on stuff I haven't used again (how do I get started with X of Y again?), that sort of stuff.
Using LLMs in the IDE and other agentic use is something I have worked with. But to me it falls under what I call "lazy use" where you are further and further removed from the creation of code, the reasoning behind it, etc. I know it is a highly popular approach with many people on HN. But in my experience, it is an approach that makes skills of experienced developers atrophy and makes sure junior developers are less likely to pick them up. Making both overly reliant on tools that have been shown to be less than reliable when the output isn't properly reviewed.
I get the firm feeling that velocity crowd works in environments where they are judged by the amount of tickets closed. Basically "feature complete, test green, merged, move on!". In that context, it isn't really "important" that the tests that are green are also refactored by the thing itself, just that they are green. It is a symptom of a corporate environment where the focus is on these "productivity" metrics. From that perspective I can fully see the appeal for LLM heavy workflows as they most certainly will have an impact on metrics like "tickets closed" or "lines of code written".
It does when you are competing for getting and keeping employment opportunities.
Correct. But it becoming shittier is the strong default, with forces that you constantly have to fight against.
And the reason is very simple: Someone profits from it being shittier and they have a lot of patience and resources.
The hypothetical that we're 8x as productive but the work isn't as fun isn't "society becoming shittier".
We are very well paid for very cushy work. It's not good for anyone's work to get worse, but it's not a huge hit to society if a well-paid cushy job gets less cushy.
And presumably people buy our work because it's valuable to them. Multiplying that by 8 would be a pretty big benefit to society.
I don't want my job to get less fun, but I would press that button without hesitation. It would be an incredible trade for society at large.
Software devs jobs getting less cushy is no biggie. We can afford to amp up the efficiency. Teachers jobs got "less cushy" -> not great for users/consumers or the ppl in those jobs. Doctors jobs got "less cushy" -> not great for users/consumers or the ppl in those jobs. Even waiters/ check-out staff, stockists jobs at restaurants, groceries and AMZ got "less cushy" -> not great for users/consumers or the ppl in those jobs. at least not when you need to call someone for help.
These things are not as disconnected as they seem. Businesses are in fact made up of people.
I've seen plenty enough people try, really try, to get into software development; but they just can't do it.
1. Efficiency measures as written to benchmark this coupling with economic productivity overall
2. Monetary assessments of value in the context of businesses spending money corresponding with social value
3. The gains of economic productivity being distributed across society to any degree, or the effect of this disparity itself being negligible
4. The negative externalities of these processes scaling less quickly than whatever we're measuring in our productivity metric
5. Aforementioned externalities being able to scale to even a lesser degree in lockstep with productivity without crashing all of the above, if not causing even more catastrophic outcomes
I have very little faith in any of these assumptions
So I mean... Yeah
Is software more comfortable generally than many other lines of work? Yes probably
Is it always soft and cushy? No, not at all. It is often high pressure and high stress
I cannot remember events, conversations, or details about important things. I have partially lost my ability to code, because I get partway through implementing a feature and forget what pieces I've done and which pieces still need to be done
I can still write it, but the quality of my work has plummeted, which is part of why I'm off on leave now
1. 1 tablespoon of cold extracted cod liver oil EVERY MORNING
2. 30 min of running 3-4 times a week
3. 2-3 weight lifting sessions every week
4. regular walks.
5. cross train on different intellectually stimulating subjects. doing the same cognitive tasks over and over is like repetive motion on your muscles
6. regularly scheduled "fallow mind time." I set aside an 30 min to an hour everyday to just sit in a chair and let my mind wander. its not meditation. I jsut sit and let my mind drift to whatever it wants.
7. while it should be avoided, in the event that you have to crunch, RESPECT THE COOLDOWN. take downtime after. don't let your nontechnical leads talk you out of it. thinking hard for extended periods of time requires appropriate recovery.
the human brain is a complex system and while we think of our mind as abstract and immaterial, it is in reality a whole lot of physical systems that grow, change and use resources the same way any other physical system in your body does. just like muscles need to recover after a workout to get stronger, so too does your brain after extended periods of deep thinking.
I hope my recovery doesn't take that long, but if it does it does
I would rather give myself the space and time to really get better, rather than simply rush back to work and burn out again
All I can suggest is see a doctor as soon as possible and talk to them about it
But I am struggling to remember things I did not used to struggle with
Going to an event on a weekend with my wife and completely forgetting that we ran into a friend there. Not just "oh yeah I forgot we saw them", like feeling my wife is lying to me when she tells me we saw them. Texting them to ask and they agree we saw each other
These are people I trust with my life so I believe they would not gaslight me, my own memory has just failed
Many examples like this, just completely blacking out things. Not forgetting everything, but blacking out large pieces of my daily life. Even big things
Disclaimer: talk to your doctor. I don’t know if your doctor can tell you whether this is a good idea, but it might help in some countries with good medical systems.
That's stupid and detrimental to your mental health.
You do it in an hour, spend maybe 1-2 hours to make it even better and prettier and then relax. Do all that menial shit you've got lined up anyway.
I wish that the hype crowd would do that. It would make a for a much more enjoyable and sane experience on platforms like this. It's extremely difficult to have actual conversations subjects when there are crowds of fans involved who don't want to hear anything negative.
Yes, I also do realize there are people completely on the other side as well. But to honest, I can see why they are annoyed by the fan crowd.
Exactly, IME the hype crowd is really the worst at this. They will spend 8h doing 8 different 1h tries at getting the right context for the LLM and then claim they did it in 1h.
They claim to be faster than they are. There's a lot of mechanical turking going about as soon as you ask a few probing questions.
>In the capitalist mode of production, the generation of products (goods and services) is accomplished with an endless sequence of discrete, repetitive motions that offer the worker little psychological satisfaction for "a job well done." By means of commodification, the labour power of the worker is reduced to wages (an exchange value); the psychological estrangement (Entfremdung) of the worker results from the unmediated relation between his productive labour and the wages paid to him for the labour.
Less often discussed is Marx's view of social alienation in this context: i.e., workers used to take pride in who they are based on their occupation. 'I am the best blacksmith in town.' Automation destroyed that for workers, and it'll come for you/us, too.
Low quality software kills people.
Both will stay manual / require high level of review they're not what's being disrupted (at-least in near term) - it's the rest.
What was automated was the production of raw cloth.
This phenomenon is a general one… chainsaws vs hand saws, bread slicers vs hand slicing, mechanical harvesters vs manual harvesting, etc.
A large enough GDPR or SOX violation is the boogeyman that CEO's see in their nightmares.
The machines we’re talking about made raw cloth not clothing and it was actually higher quality in many respects because of accuracy and repeatability.
Almost all clothing is still made by hand one piece at a time with sewing machines still very manually operated.
“…the output of power looms was certainly greater than that of the handlooms, but the handloom weavers produced higher quality cloths with greater profit margins.” [1]
The same can be said about machines like the water frame. It was great at spinning coarse thread, but for high quality/luxury textile (ie. fine fabric), skilled (human) spinners did a much better job. You can read the book Blood in the Machine for even more context.
[0] https://en.wikipedia.org/wiki/Industrial_Revolution
[1] https://en.wikipedia.org/wiki/Dandy_loom
If your goal is to make 1000 of the exact same dress, having a completely consistent raw material is synonymous with high quality.
It’s not fair to say that machines produced some kind of inferior imitation of the handmade product, that only won through sheer speed and cost to manufacture.
AI slop code doesn't even work beyond toy examples.
When it is eventually made, though… it’s either aligned or we’re in trouble. Job cushiness will be P2 or P3 in a world where a computer can do everything economically viable better than any human.
They are brains. I think it's on you to prove they're the same, rather than assuming they're the same and then demanding proof they aren't!
But in fairness to human devs, most are still writing software that is leagues better than the dog shit AI is producing right now
Thing is though, many people don't know how to do that (user stories / acceptance criteria) properly, and it's been up to software developers to poke holes and fill in the blanks that the writer didn't think about.
Long term the craftsperson writing excellent code will win. It is now easier than ever to write excellent code, for those that are able to choose their pace.
If anything we'll see disposable systems (or parts) and the job of an SE will become even more like a plumber, connecting prebuilt business logic to prebuilt systems libraries. When one of those fails, have AI whip up a brand new one instead of troubleshooting the existing one(s). After all, for business leader it's the output that matters, not the code.
For 20+ years business leaders have been eager to shed the high overhead of developers via any means necessary while ignoring their most expensive employees' input. Anyone remember Dilbert? It was funny as a kid, and is now tragic in its timeless accuracy a generation later.
Maybe. I'm seeing the opposite - yes, the big ships take time to turn, but with the rise of ransomware and increasing privacy regulation around the world, companies are putting more and more emphasis on quality and avoiding incidents.
An earlier iteration of your reply said "Is that really winning?" The answer is no. I don't think any class of SE end up a winner here.
It's not really about excitement or enjoyment of work.
It's the fear about the __8x output__ being considered as __8x productivity__.
The increase in `output/productivity` factor has various negative implications. I would not say everything out loud. But the wise can read between the lines.
That's why we should be against it but hey, we can provide more value to shareholders!
Overall, is this even a good thing? With this increase in output, I suspect we'll need to apply more pressure to people requesting features to ensure those requests are high quality. When each feature takes half the time to implement, I bet it's easy to agree to more features without spending as much time evaluating their worth.
This is precisely the question that scares me now. It is always so satisfying when a revolution occurs to hold hands and hug each other in the streets and shout "death to the old order". But what happens the next morning? Will we capture this monumental gain for labor or will we cede it to capital? My money is on the latter. Why wouldn't it be? Did they let us go home early when the punch card looms weaved months worth of hand work in a day? No, they made us work twice as hard for half the pay.
I'm enjoying exactly what the author describes, so it's different strokes for different folks.
I always found the "code monkey" aspect of software development utterly boring and tedious, and have spent a lot of my career automating that away with various kinds of code generators, DSLs, and so on. \
Using an LLM as a general-purpose automated code monkey is a near-ideal scenario for me, and I enjoy the work more. It's especially useful for languages like Go or Java where repetitive boilerplate is endemic.
I also find it helps with procrastination, because I can just ask an LLM to start something for me and get over the initial hump.
> whether we're actually trading away more quality that we realise.
This is completely up to the people using it.
If the SWE can finish his work faster, 8x faster in this case, then backlogs will also be pushed to complete 8x faster by the project manager. If there are no backlogs, new features will be required at 8x faster / more by sales team / clients. If no new features are needed, pressures will be made until costs are 8x lower by finance. If there are no legal, moral, competitive, or physical constraints, the process should continue until either there’s only a single dev working on all his available time, or less time but for considerably less salary.
While letting the AI write some code can be cool and fascinating, I really can't undersand how:
- write the prompt(and you need do be precise and think and express carefully what you have in mind)
- check/try the code
- repeat
is better than writing the code by myself. AI coding like this feels like a nightmare to me and it's 100x more exhausting.
Whenever I use an LLM I always need to review its output because usually there is something not quite right. For context I'm using VS copilot, mostly ask and agent mode, in a large brownfield project.
I think the parallels are clear for those of us who have been through this scenario.
People keep comparing higher-level programming languages to lower-level abstractions - these comparisons are absolutely false. The whole point of higher-level programming languages is for people to get away from working with the lower level stuff.
But with the way software engineers are interacting with LLMs, they are not getting away from writing code because they have to use what comes out of it to achieve their goal (writing and piecing together code to complete a project).
In our current scenario, programmers are merely describing what they think the code should do, and another program takes their description and then stochastically generates code based on it.
LLMs are more like DNA transcription, where some percentage of the time it just injects a random mutation into the transcript, either causing am evolutionary advantage, or a terminal disease.
This whole AI industry right now is trying to figure out how to always get the good mutation, and I don't think it's something that can be controlled that way. It will probably turn out that on a long enough timescale, left unattended, LLMs are guaranteed to give your codebase cancer.
It's a perfectly cromulent approach and skillset - but it's a wildly different one.
THE GREYBEARD You left your workroom in great disarray.
MICHELANGELO Because I had to fabricate the chair-legs To the quality as poor as it can be. I appeal’d for long, let me modificate, Let me engrave some ornaments on it.
They did not permit. I wanted as a chance The chair-back to change but all was in vain. I was very close to be a madman And I left the pains and my workroom, too. (stands back)
THE GREYBEARD You get house arrest for this disorder And will not enjoy this nice and warm day.
If I listen to music, I can spend an hour CODING YEAH! and be all smug and satisfied, until I turn the music off and discover that everything I've coded is unnecessary and there is an easier way to achieve the same goal. I just didn't see it, because the creative part of my brain was busy listening to music.
From the post, it sounds like the author discovered the same thing: if you use AI to perform menial tasks (like coding), all that is left is thinking creatively, and you can't do that while listening to music.
You may be experiencing getting to different understanding of sth when you switch context. Similar to when you are stack it may be better to go for a walk than keep your head on top of a piece of paper or screen. I have had many of my breakthroughs while taking a shit in the toilet in the midst of working. Others experience similar with showers and whatever.
Afaik most ppl listen to music during certain tasks because it helps focusing. Esp when working in a busy office it really helps me to listen to certain kinds of predictable music to keep me from getting distracted. It creates a sort of entrainment that helps with attention.
Some people find music itself distracting, I myself find some kinds of music distracting, or during certain types of tasks. Then it obviously it does not fill its purpose.
In my experience, there is no good shortcut to this realization. Doing it wrong first is part of the journey. You might as well enjoy the necessary mistakes along the way. The third time’s the charm!
But also, this can create waste, in that people write the Best Code Ever in their flow state (while listening music or not), but... it wasn't necessary in the first place and the time spent was a waste. This can waste anything from an hour to six months of work (honestly, I had a "CTO" once who led a team of three dozen people or so who actually went into his batcave at home for six months to write a C# framework of sorts that the whole company should use. He then quit and became self-employed so the company had to re-hire him to make sense of the framework he wrote. I'm sure he enjoyed it very much though.)
I think this is individual, I have the same problem in social settings - if I'm having a conversation and a song I like is playing in the background I some times stop listening to the conversation and focus on the music instead, unintentionally.
My solution is to listen to music without vocals when I need to focus. I've had phases where I listen to classical music, electronic stuff, and lately I've been using an app I found called brain.fm which I think just plays AI generated lo-fi or whatever and there's some binaural beats thing going on as well that's supposed to enhance focus, creativity etc. I like it but some times I go back to regular music just because I miss listening to something I actually like.
Some work may allow for seamless pivoting between work vs. enjoyable distraction, e.g., a clerk, but I often hear about people listening to music in other contexts.
I've never, ever, ever once in 40 years of coding listened to music while coding and later found the code "unnecessary" or anything of the sort.
I engage in many creative pursuits outside of coding, always while listening to music, and I can confidently say that music has never once interfered in the process or limited the result in any way.
https://www.youtube.com/watch?v=DrA8Pi6nol8
EQing the music played sounds interesting. I’ll look at the options. I tend to just have it at a level low enough that I can hear all speakers on the call.
Good nugget. Effective prompting, aside from context curation, is about providing the LLM with an approximation of your world model and theory, not just a local task description. This includes all your unstated assumptions, interaction between system and world, open questions, edge cases, intents, best practices, and so on. Basically distill the shape of the problem from all possible perspectives, so there's an all-domain robustness to the understanding of what you want. A simple stream of thoughts in xml tags that you type out in a quasi-delirium over 2 minutes can be sufficient. I find this especially important with gpt-5, which is good at following instructions to the point of pedantry. Without it, the model can tunnel vision on a particular part of the task request.
Without this it defaults to being ignorant about the trade-offs that you care about, or the relevant assumptions you're making which you think are obvious but really aren't.
The "simple stream" aspect is that each task I give to the LLM is narrowly scoped, and I don't want to put all aspects of the relevant theory that pertains just to that one narrow task into a more formal centralized doc. It's better off as an ephemeral part of the prompt that I can delete after the task is done. But I also do have more formal docs that describe the shared parts of the theory that every prompt will need access to, which is fed in as part of the normal context.
---
### The Fragility of Digital Memory in the Age of Infinite Storage
We live inside an archive that never closes. Hard drives hum like cathedrals of perfect recall, cloud servers drift like silent librarians in orbit, and every keystroke is another bone set in amber. Memory, once a trembling candle subject to drafts and time, now runs on battery backups and redundant arrays. Forgetting has been engineered out of the system.
And yet, the paradox: by remembering everything, we begin to lose the art of remembering at all. Human memory is a cracked mirror—crooked, selective, shimmering with distortions that make us who we are. Its gaps are the negative space where meaning lives. The story of a childhood is not its complete inventory but its torn edges, the blurred photograph, the half-forgotten lullaby whose missing notes we hum into being.
Digital memory, by contrast, is a hoarder’s attic with perfect climate control. Nothing rots, nothing fades, nothing dares to slip away. Every draft email unsent, every unflattering selfie, every midnight search query—all preserved in pristine sterility. The archive is so complete that it ceases to be a story. It becomes a warehouse of moments that never learned how to decay.
But memory without decay is less than human. Nostalgia itself might be the first compression algorithm: a lossy filter that turns clutter into resonance. Without the soft erasures of time, experience calcifies into raw data, and raw data has no mercy.
Perhaps what we need are systems that misremember. Databases that dream. Algorithms that allow certain files to fray at the edges, to grow fuzzy like old film reels, to tint themselves with the sepia of emotion rather than the fluorescence of metadata. A kind of deliberate forgetting—not loss as failure, but loss as design.
Because what is fragility if not the pulse behind memory’s worth? The hard drive never gasps, never sighs; only the human mind knows the ache of absence, the sweetness of something slipping away. If the future is an archive without end, perhaps our task is to reintroduce the possibility of disappearance. To let silence seep between the entries. To remind the machines that to truly remember, one must first learn how to forget.
---
Do you want me to lean this more toward *meditation* (open-ended, drifting) or *argument* (provoking design questions like “can forgetting be engineered”)?
> But memory without decay is less than human.
How is it less than human? By definition, the undecayed memory is more complete.
> Nostalgia itself might be the first compression algorithm: a lossy filter that turns clutter into resonance.
What is this even supposed to mean? I guess the idea is something here like "fuzzy" memory == "compression" but nostalgia is an emotional response - we're often nostalgic about clear, vivid memories, experiences that didn't lose their texture to time.
> Without the soft erasures of time, experience calcifies into raw data, and raw data has no mercy.
Eh... kinda. Calcifies is the wrong word here. Raw data doesn't have mercy, but lossily-compressed data is merciful? Is memory itself merciful? Or is it a mercy for the rememberer to be spared their past shames?
So much AI slop is like this: it's just words words words words without ideas behind them.
In my experience, it seems the people who have bad results have been trying to get the AI to do the reasoning. I feel like if I do the reasoning, I can offload menial tasks to the AI, and little annoying things that would take one or two hours start to take a few minutes.
That very quickly adds up to some real savings.
The ones who know what they want to do, how it should be done, but can't really be arsed to read the man pages or API docs of all the tools required.
These people can craft a prompt (prompt engineering :P) for the LLM that gets good results pretty much directly.
LLMs are garbage in garbage out. Sometimes the statistical average is enough, sometimes you need to give it more details to use the available tools correctly.
Like the fact that `fd` has the `-exec` and `--exec-batch` parameters, there's no need to use xargs or pipes with it.
Then you have to QA it for ages to discover the bugs it wrote, but the initial perception of speed never leaves you.
I think I'm overall slower with AI, but I could be faster if I had it write simple functions that I could review one by one, and have the AI compose them the way I wanted. Unfortunately, I'm too lazy to be faster.
Of course you need to check their work, but also the better your initial project plan and specifications are, the better the result.
For stuff with deterministic outputs it's easy to verify without reading every single line of code.
With that it can see any errors in the console, click through the UI and take screenshots to analyse how it looks giving it an independent feedback loop.
[0] https://github.com/microsoft/playwright-mcp
90% of what the average (or median) coder does isn't in any way novel or innovative. It's just API Glue in one form or another.
The AI knows the patterns and can replicate the same endpoints and simple queries easily.
Now you have more time to focus on the 10% that isn't just rehashing the same CRUD pattern.
I hear this from people extolling the virtue of AI a lot, but I have a very hard time believing it. I certainly wouldn't describe 90% of my coding work as boilerplate or API glue. If you're dealing with that volume of boilerplate/glue, isn't it incumbent upon you to try and find a way to remove that? Certainly sometimes it isn't feasible, but that seems like the exception encountered by people working on giant codebases with a very large number of contributors.
I don't think the work I do is innovative or even novel, but it is nuanced in a way I've seen Claude struggle with.
It's the connectors that are 90-95% AI chow, just set it to task with a few examples and it'll have a full CRUD interface for your data done while you get more snacks.
Then you can spend _more_ of your limited time on the 10% of code that matters.
That said, less than 50% of my actual time spent on the clock is spent writing code. That's the easiest part of the job. The rest is coordinating and planning and designing.
I assumed you were only talking about the actual code. It still seems really odd. Why is there so much unavoidable boilerplate?
It has a specific amount of code I need to write just to add the basic boilerplate of receiving the data and returning a result from the endpoint before I can get to the meat of it.
IIRC there are no languages where I can just open an empty file and write "put: <business logic>" and it magically knows how to handle everything correctly.
> IIRC there are no languages where I can just open an empty file and write "put: <business logic>" and it magically knows how to handle everything correctly.
Are you sure it's done correctly? Take something like timestamps, or validations: It's easy to get those wrongs.
If it doesn't, then I feel like even in the JavaScript world of 2015 you could write "app.put("/mypath", business_logic)" and that would do the trick, and that was a very immature language ecosystem.
Their job is to do meetings, and occasionally add a couple of items to the HTML, which has been mostly unchanged for the past 10 years, save for changing the CSS and updating the js framework they use.
I set up a model in DBT that has 100 columns. I need to generate a schema for it (old tools could do this) with appropriate tests and likely data types (old tools struggled with this). AI is really good at this sort of thing.
I had Claude Code build me a Playwright+python -based scraper that goes through their movie section and stores the data locally to an sqlite database + a web UI for me to watchlist specific movies + add price ranges to be alerted when it changes.
Took me maybe a total of 30 minutes of "active" time (4-5 hours real-time, I was doing other shit at the same time) to get it to a point where I can actually use it.
Basically small utilities for limited release (personal, team, company-internal) is what AI coding excels at.
Like grabbing results from a survey tool, adding them to a google sheet, summarising the data to another tab with formulas. Maybe calling an LLM for sentiment analysis on the free text fields.
Half a day max from zero to Good Enough. I didn't even have to open the API docs.
Is it perfect? Of course not. But the previous state was one person spending half a day for _each_ survey doing that manually. Now the automation runs in a minute or so, depending on whether Google Sheets API is having a day or not =)
For instance this week when setting up a Django/Wagtail project GPT helpfully went ahead and created migration files in text instead of "makemigrations". Otherwise it did a bang up job and saved me a couple of hours.
Just no way I can get in the zone wrangling that kind of thing all day.
But I'm not sure getting in the coding zone frequently was all that mentally healthy so oh well.
Many programmers are rejecting AI coding because they miss the challenge they enjoy getting from conventional programming but this author finds it even more challenging. Or perhaps challenging in a different way?
I suspect that the type of programmer who enjoys vibe coding is the latter. For me it's pretty tiring to explain everything in excruciating detail, it's often easier to just write the code myself rather than explain in English how to write it.
It feels like I am just doing the hard part of programming all the time - deciding how the app should work and how the code should be structured etc, and I never get those breaks where I just implement my plan.
I think in code and programming concepts when I am writing software . I don't really know how to explain that, but I don't often feel like there is any friction between my thoughts and the code I make
I think that many coders do not have this. They have an extra "translation" step that introduces friction into their workflow
I don't experience this friction, so LLM coding introduces new friction that I don't like
They do experience this friction, so LLM coding doesn't introduce new friction for them, it may transform their previous friction into a new form that is easier for them to navigate
I don't know. Maybe I'm talking out my ass, this is just a random theory based on no real evidence
It's not really that I think in code. It's more like code is as much as a language to me as writing english, or holding the pencil to draw something. I got a change request, or I read something from the docs, and the the mental concept I have realign itself to the new knowledge. Getting code out is always effortless. There's no difference between
And If I can describe something, I can code it.More or less just that there is little to no friction for me to think a thought and write the code compared to "translating" the thought into code
The best approach is to use AI only when you are stuck and looking for potential solutions, but we all know that is not going to happen unless you have extreme self-control.
If you say “you are praf” in Romanian it means that you are f*cked, wasted, done for, etc.
Can we see this frontend code? For research purposes, of course.
Because the people running the show are experienced software devs, not AI clowns.
At home I still plan and devise my own worlds with joy. I may use LLMs for boring or repetitive tasks, or help or explanation; but I still can code better than the day before.
As usual, work != career.
This way we can allow AIs to do our work, but the AI can also tutor us and teach us the things necessary to verify their work.
Agents finish, I queue them up with new low hanging fruits, while I architect the much bigger tasks, then fire that off -> Review smaller tasks. It really is a dance, but flow is much easier achieved when I do get into it; hours really just melt together. The important thing to do is to put my phone away, and block all and any social media or sites I frequent, because its easy to get distracted when agents aren just producing code and you're sitting on the sidelines.
While programming, it's possible to get into a trance-like state where the program's logic is fully loaded and visible in your mind, and your fingers become an extension of your mind that wire you directly to the machine. This allows you to modify the program essentially at the speed of thought, with practically zero chance of producing buggy code. The programmer effectively becomes a self-correcting human interpreter.
Interrupting someone in this state is incredibly disruptive, since all the context and momentum is lost, and getting back into the state takes time and focus.
What you're describing is a general workflow. You can be focused on what you're doing, but there's no state loaded into memory that makes you more efficient. Interruptions are not disruptive, and you can pick up exactly where you left off with ease. In fact, you're constantly being interrupted by those agents running in the background, when they finish and you give them more work. This is a multitasking state, not flow.
So the article is correct. It's not possible to get into a flow state while working with ML tools. This is because it is an entirely different activity from programming that triggers different neural pathways.
When using ML tools you have no deep understanding of the behavior of the program, since you don't understand the generated code. If you bother to review the code, that is a huge context switch from anything you were doing previously. This doesn't happen during deeply focused programming sessions.
You may have been a software engineer for decades without ever experiencing the programming flow state. I'm not passing judgement.
Got nothing done.
This is a other “trust me” post about AI.
(I also find AI repulsive and have no intention to engage in anything AI-related. Recently I turned off AI "help" in DDG.)
It definitely makes me faster but it's consistent prompt->code-review->prompt->code-review->scratch->prompt-code->review cycle which just requires extreme focus.
Brainstorming with LLM? Literal background noise like distant thunderstorm.
Pairing with LLM? Classical.
Solo? Still technical death metal.
I also wonder what type of simple CRUD apps people build that have such a performance gain? They must be building well understood projects or be incredible slow developers for LLMs to have such an impact, as I cant relate to this at all.
But I certainly wouldn’t assume that other people’s jobs are simple or boring just because they don’t look like yours.
Which is absolutely no shame. But people shouldn't expect these gains for their job if they work in less understood environments.
Most non CRUD AI code implementations are flawed/horrendous.
But for the rest of us, who have a mix of common/boring and uncommon/interesting tasks, accelerating the common ones means spending more time (proportionally) on less common tasks.
Unfortunately we don’t seem to great at classifying tasks as common or uncommon, and there are bored engineers who make complex solutions just to keep their brain occupied.
That's gone.
My impression of myself is the high leverage strategic work was always subconscious, but I never had to notice; my hands were busy so it felt like I'm "working".
And with the AI typing for me, it doesn't necessarily go that much faster. I've got to go lift weights, play my favourite vintage racing slop (Rush 2) or take a long shower. At some point the plan is revealed to me and I've got to poke the computer and make it do the next thing.
Very strange experience. All of it.
At my first job in Silicon Valley, I used to code right on the production floor totally oblivious to what was going on.
Once your requests start to veer away from the direction you wanted (Especially if at-any-point, you transition to Cursor's "Free" mode, and it misunderstands and bulldozes all your previously-working features)
Not only is it harder, the physical stress caused by debugging with AI is something new. It gets some requests so-incredibly-wrong and follows directions totally-contrary, your brain forgets it's talking to a computer, and reacts in a way you would to a person who did all the wrong things here.
Version control has never been so important. I never use cursor without it. And even then, sometimes I just open the client, and a bunch of files changed.