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.
latexr · 3h 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.
theshrike79 · 3h 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.
willtemperley · 2h 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.
darkwater · 3h 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!
ahoka · 3h 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.
nxpnsv · 4h ago
If the price is music, then it’s too expensive.
bravetraveler · 3h ago
This is why I reject every Teams call
hn_throw2025 · 2h ago
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).
bravetraveler · 1h ago
My position isn't due to incapability
nxpnsv · 3h ago
they can't hear if it is them or music on my phones...
energy123 · 3h 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 · 3h 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 · 3h 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.
mckn1ght · 3h 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.
ai_assisted_dev · 3h 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.
DevKoala · 3h 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.
What kind of projects are people doing that are feeling the increased velocity?
elros · 3h 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 · 2h 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 · 3h 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 · 2h 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 · 2h 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.
martin_a · 3h 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 · 2h 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.
energy123 · 3h 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 · 3h ago
How do you know they’re durable and high quality?
energy123 · 3h ago
I do it based on my subjective judgement, somewhat informed by quantitative measurements of metrics I care about like throughput.
staticautomatic · 3h 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.
theshrike79 · 2h 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 =)
CalRobert · 3h 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.
gonzo41 · 3h ago
CRUD work, Boilerplate config for network stuff, converting lots of oracle stored procedures. It's saving me days.
jwr · 3h 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.
shaan7 · 2h 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.
icetank · 3h 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.
nemoniac · 2h 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 · 2h 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.
fearface · 4h 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.
johnfn · 4h 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.
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.
iamflimflam1 · 3h ago
He’s talking about being in a state of flow - it’s a lovely feeling when you can get into it.
conductr · 3h 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
mac-mc · 3h 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.
winrid · 3h ago
JimTV on YT has great programming music.
GLdRH · 3h ago
That's why metal works well here.
mckn1ght · 3h 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.
triyambakam · 4h 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 · 4h ago
Do things the way you like instead of saying "I miss it".
p0w3n3d · 4h 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.
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 · 4h 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 · 2h 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 · 3h 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.
winrid · 3h ago
There are people using Claude to make entire 3d MMO games, so ...
drmpeg · 3h 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.
sublinear · 3h 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.
grugagag · 3h ago
Killed all the fun?
globular-toast · 3h 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.
tamimio · 3h 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.
excalibur · 4h ago
The answers are in the footnote, switching to frontend is the way.
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.
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.
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.
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.
That's why we should be against it but hey, we can provide more value to shareholders!
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.
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.
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.
https://www.youtube.com/watch?v=DrA8Pi6nol8
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.
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 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 =)
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.
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.
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?
This is a other “trust me” post about AI.
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.
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.
At my first job in Silicon Valley, I used to code right on the production floor totally oblivious to what was going on.
Can we see this frontend code? For research purposes, of course.
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.