> I've never been more productive

Maybe it’s because my approach is much closer to a Product Engineer than a Software Engineer, but code output is rarely the reason why projects that I worked on are delayed. All my productivity issues can attributed to poor specifications, or problems that someone just threw over the wall. Every time I’m blocked is because someone didn’t make a decision on something, or no one has thought further enough to see this decision was needed.

It irks me so much when I see the managers of adjacent teams pushing for AI coding tools when the only thing the developers know about the project is what was written in the current JIRA ticket.

>Why bother playing when I knew there was an easier way to win? This is the exact same feeling I’m left with after a few days of using Claude Code. I don’t enjoy using the tool as much as I enjoy writing code.

My experience has been the opposite. I've enjoyed working on hobby projects more than ever, because so many of the boring and often blocking aspects of programming are sped up. You get to focus more on higher level choices and overall design and code quality, rather than searching specific usages of libraries or applying other minutiae. Learning is accelerated and the loop of making choices and seeing code generated for them, is a bit addictive.

I'm mostly worried that it might not take long for me to be a hindrance in the loop more than anything. For now I still have better overall design sense than AI, but it's already much better than I am at producing code for many common tasks. If AI develops more overall insight and sense, and the ability to handle larger code bases, it's not hard to imagine a world where I no longer even look at or know what code is written.

The calculator made it less important to be relatively good with arithmetic. Many people just cannot add or subtract two numbers without one. And it feels like they lose intuition, somehow: if numbers don't "speak" to you at all, can you ever realize that 17 is roughly a third of 50? The only way you realise it with a calculator is if you actually look for it. Whereas if you can count, it just appears to you.

Similar with GPS and navigation. When you read a map, you learn how to localise yourself based on landmarks you see. You tend to get an understanding of where you are, where you want to go and how to go there. But if you follow the navigation system that tells you "turn right", "continue straight", "turn right", then again you lose intuition. I have seen people following their navigation system around two blocks to finally end up right next to where they started. The navigation system was inefficient, and with some intuition they could have said "oh actually it's right behind us, this navigation is bad".

Back to coding: if you have a deep understanding of your codebases and dependencies, you may end up finding that you could actually extract some part of one codebase into a library and reuse it in another codebase. Or that instead of writing a complex task in your codebase, you could contribute a patch to a dependency and it would make it much simpler (e.g. because the dependency already has this logic internally and you could just expose it instead of rewriting it). But it requires an understanding of those dependencies: do you have access to their code in the first place (either because they are open source or belong to your company)?

Those AIs obviously help writing code. But do they help getting an understanding of the codebase to the point where you build intuition that can be leveraged to improve the project? Not sure.

Is it necessary, though? I don't think so: the tendency is that software becomes more and more profitable by becoming worse and worse. AI may just help writing more profitable worse code, but faster. If we can screw the consumers faster and get more money from them, that's a win, I guess.

I'm a little older now, over 60. I'm writing a spaceflight simulator for fun and (possible) profit. From game assets to coding, it seems like AI could help. But every time I try it out, I just end up feeling drained by the process of guiding it to good outcomes. It's like I have an assistant to work for me, who gets to have all the fun, but needs constant hand holding and guidance. It isn't fun at all, and for me, coding and designing a system architecture is tremendously satisfying.

I also have a large collection of handwritten family letters going back over 100 years. I've scanned many of them, but I want to transcribe them to text. The job is daunting, so I ran them through some GPT apps for handwriting recognition. GPT did an astonishing job and at first blush, I thought the problem was solved. But on deeper inspection I found that while the transcriptions sounded reasonable and accurate, significant portions were hallucinated or missing. Ok, I said, I just have to review each transcription for accuracy. Well, reading two documents side by side while looking for errors is much more draining than just reading the original letter and typing it in. I'm a very fast typist and the process doesn't take long. Plus, I get to read every letter from beginning to end while I'm working. It's fun.

So after several years of periodically experimenting with the latest LLM tools, I still haven't found a use for them in my personal life and hobbies. I'm not sure what the future world of engineering and art will look like, but I suspect it will be very different.

My wife spins wool to make yarn, then knits it into clothing. She doesn't worry much about how the clothing is styled because it's the physical process of working intimately with her hands and the raw materials that she finds satisfying. She is staying close to the fundamental process of building clothing. Now that there are machines for manufacturing fibers, fabrics and garments, her skill isn't required, but our society has grown dependent on the machines and the infrastructure needed to keep them operating. We would be helpless and naked if those were lost.

Likewise, with LLM coding, developers will no longer develop the skills needed to design or "architect" complex information processing systems, just as no one bothers to learn assembly language anymore. But those are things that someone or something must still know about. Relegating that essential role to a LLM seems like a risky move for the future of our technological civilization.

I think this particular anxiety was explored rather well in the anonymous short story 'The End of Creative Scarcity':

https://www.fictionpress.com/s/3353977/1/The-End-of-Creative...

Some existential objections occur; how sure are we that there isn't an infinite regress of ever deeper games to explore? Can we claim that every game has an enjoyment-nullifying hack yet to discover with no exceptions? If pampered pet animals don't appear to experience the boredom we anticipate is coming for us, is the expectation completely wrong?

As far as hobby projects are concerned, I'd agree: A bit more "thinking like your boss" could be helpful. You can now focus more on the things you want your project be able to do instead of the specific details of its code structure. (In the end, nothing keeps you from still manually writing/editing parts of the code if you want some things specifically done in a certain way. There are also projects where the code structure legitimately is the feature, I.e. if you want to explore some new style of API or architecture design for its own sake)

The one part that I believe will still be essential is understanding the code. It's one thing to use Claude as a (self-driving) car, where you delegate the actual driving but still understand the roads being taken. (Both for learning and for validating that the route is in fact correct)

It's another thing to treat it like a teleporter, where you tell it a destination and then are magically beamed to a location that sort of looks like that destination, with no way to understand how you got there or if this is really the right place.

I think AI is posing a challenge to people like the person in TFA because programming is their hobby and one that they’re good at. They aren’t used to knowing someone or something can do it better and knowing that now makes them wonder what the point is. I argue that amateur artists and musicians have dealt with this feeling of “someone can always do it better” for a very long time. You can have fun while knowing someone else can make it better than you, faster, without as much struggle. Programmers aren’t as used to this feeling because, even though we know people like John Carmack exist, it doesn’t fly in your face quite like a beautiful live performace or painted masterpiece does. Learning to enjoy your own process is what I think is key to continuing what you love. Or, use it as an opportunity to try something else — but you’ll eventually discover the same thing no matter what you do. It’s very rare to be the best at something.

All articles of this class, whether positive or negative, begin "I was working on a hobby project" or some variation thereof.

The purpose of hobbies is to be a hobby, archetypical tech projects are about self-mastery. You cannot improve your mastery with a "tool" that robs you of most of the minor and major creative and technical decisions of the task. Building IKEA furniture will not make you a better carpenter.

Why be a better carpenter? Because software engineering is not about hobby projects. It's about research and development at the fringes of a business (, orgs, projects...) requirements -- to evolve their software towards solving them.

Carpentry ("programming craft") will always (modulo 100+ years) be essential here. Powertools do not reduce the essential craft, they increase the "time to craft being required" -- they mean we run into walls of required expertise faster.

AI as applied to non-hobby projects -- R&D programming in the large -- where requirements aren't specified already as prior art programs (of func & non-func variety, etc.) ---- just accelerates the time to hitting the wall where you're going to shoot yourself in the foot if you're not an expert.

I have not seen a single take by an experienced software engineer have a "sky is falling" take, ie., those operating at typical "in the large" programming scales, in typical R&D projects (revision to legacy, or greenfield -- just reqs are new).

I'm more and more confident I must be doing something wrong. I (re)tried using Claude about a month ago and I simply stopped using it after about two weeks because on one hand productivity did not increase(perhaps even decreased), but on the other hand it made me angry because of the time wasted on its mistakes. I was also mostly using it on Rust code, so I'm even more surprised about the article. What am I doing wrong? I've been mostly using the chat functionality and auto-complete, is there some kind of secret feature I'm missing?

The thing is: the industry does not need people who are good at (or enjoy) programming, it needs people who are good at (and enjoy) generating value for customers through code.

So the OP was in a bad place without Claude anyways (in industry at least).

This realization is the true bitter one for many engineers.

A question that came up in discussions recently and that I found interesting: How will new APIs, libraries or tooling be introduced in the future?

The models all have their specific innate knowledge of the programming ecosystem from the point in time where their last training data was collected. However, unlike humans, they cannot update that knowledge unless a new finetuning is performed - and even then, they can only learn about new libraries that are already in widespread use.

So if everyone now shifts to Vibe Coding, will this now mean that software ecosystems effectively become frozen? New libraries cannot gain popularity because AIs won't use them in code and AIs won't start to use them because they aren't popular.

It's not true that coding would no longer be fun because of AI. Arithmetic did not stop being fun because of calculators. Travel did not stop being fun because of cars and planes. Life did not stop being fun because of lack of old challenges.

New challenges would come up. If calculators made the arithmetic easy, math challenges move to next higher level. If AI does all the thinking and creativity, human would move to next level. That level could be some menial work which AI can't touch. For example, navigating the complexities of legacy systems and workflows and human interactions needed to keep things working.

> Not only that, the generated code was high-quality, efficient, and conformed to my coding guidelines. It routinely "checked its work" by running unit tests to eliminate hallucinations and bugs.

This seems completely out of whack with my experience of AI coding. I'm definitely in the "it's extremely useful" camp but there's no way I would describe its code as high quality and efficient. It can do simple tasks but it often gets things just completely wrong, or takes a noob-level approach (e.g. O(N) instead of O(1)).

Is there some trick to this that I don't know? Because personally I would love it if AI could do some of the grunt work for me. I do enjoy programming but not all programming.

I may be old, but I had the same feeling for low-level code. I enjoyed doing things like optimizing a low-level loop in C or assembly, bootstrapping a microcontroller, or writing code for a processor which didn't have a compiler yet. Even in BASIC, I enjoyed PEEKing and POKE'ing. I enjoyed opening up a file system in a binary editor. I enjoyed optimizing how my computer draws a line.

All this went away. I felt a loss of joy and nostalgia for it. It was bitter.

Not bad, but bitter.

The author is doing the math the wrong way. For an extra $5/day, a 3rd world country can now pay an engineer $20/day to do the job of a junior engineer in a 1st world one.

The bitter lesson is going to be for junior engineers who see less job offers and don’t see consulting power houses eat their lunch.

I tend to think about the average code review: who actually catches tricky bugs? Who actually takes the time to fully understand the code they review? And who likes it? My feeling is that reviews are generally a "skimming through the code and checking that it looks ok from a distance".

At least we have one person who understands it in details: the one who wrote it.

But with AI-generated code, it feels like nobody writes it anymore: everybody reviews. Not only we don't like to review, but we don't do it well. And if you want to review it thoroughly, you may as well write it. Many open source maintainers will tell you that many times, it's faster for them to write the code than to review a PR from a stranger they don't trust.

To me it’s the exact opposite. I was writing code for the past 20+ years and I recently realized it’s not the act of writing code I love, but the act of creating something from nothing. Over the past few months I wrote two non-trivial utility apps that otherwise I would most probably not write because I didn’t have enough time to do that, but Cursor + Claude gave me the 5x productivity boost that enabled me to do so, and I really enjoyed doing that.

My only gripe is that the models are still pretty slow, and that discourages iteration and experimentation. I can’t wait for the day a Claude 3.5 grade model with 1000 tok/s speed releases, this will be a total game changer for me. Gemini 2.5 recently came closer, but it’s still not there.

I had a conversation with a fellow tech founder (Running a $Bn+ val Series D robotics company currently) recently on AI assisted coding tools.

We have both been using or integrating AI code support tools since they became available and both writing code (usually Python) for 20+ years.

We both agree that windsurf + claude is our default IDE/Env now on. We also agree that for all future projects we think we can likely cut the number of engineers needed by 1/3rd.

Based on what I’ve been using for the last year professionally (copilot) and on the side, I’m confident I could build faster, better and with less effort with 5 engineers and AI tools as with 10 or 15. Also communication overhead reduces by 3x which prevents slowdowns.

So if I have a HA 5 layer stack application (fe, be, analytics, train/inference, networking/data mgt) with IPCs between them, instead of one senior and two juniors per process for a total of 15 people, I only need the 5 mid-seniors now.

A relative known youtuber called the primeagen has recently done a challenge sponsored by Cursor themselves where he and some friends would "vibe code" a game in a week. The results were pretty underwhelming. They would have been much faster not using generative Ai.

Compared what you see from game jams where sometimes solo devs create whole games in just a few days it was pretty trash.

It also tracks with my own experience. Yes, cursor quickly helps me get the first 80% done but then I spent so much time cleaning after it that I have barely saved any time in total.

For personal projects where you don't care about code quality I can see it as a great tool. If you actual have professional standards, no. (Except maybe for unit tests, I hate writing those by hand.)

Most of the current limitation CAN be solved by throwing even more compute at it. Absolutely. The question is will it economically make sense? Maybe if fusion becomes viable some day but currently with the end of fossil fuels and climate change? Is generative Ai worth destroying our planet for?

At some point the energy consumption of generative AI might get so high and expensive that you might be better off just letting humans do the work.

I don't really see it. At least the article should address why we would not assume massive price drops, market adjusted pricing and free offerings, as with all other innovation before, that all lead to wider access to better technology.

Why would this be the exception?

>Why bother playing when I knew there was an easier way to win?

>This is the exact same feeling I’m left with after a few days of using Claude Code.

For me what matters is the end result, not the mere act of writing code. What I enjoy is solving problems and building stuff. Writing code is a part.

I would gladly use a tool to speed up that part.

But from my testing, unless the task is very simple and trivial, using AI isn't always a walk in the park, simple and efficient.

"But I predict software development will be a lot less fun in the years to come, and that is a very bitter prediction in deed."

Most professional software development hasn't been fun for years, mostly because of all the required ceremony around it. But it doesn't matter, for your hobby projects you can do what you want and it's up to you how much you let AI change that.

Still think amazement of ai tools as harsh as it sounds signals incompetence of the user. They are useful don’t get me wrong but just today Claude wrote code that literally wouldnt run.

Thought it’s ok to use new for object literal in JS.

I can really relate to the feeling described after modifying save files to get more resources in a game, but I wonder if it's the same kind of 'cheating'. Doing better in a game has its own associsted feeling of achievement, and cheating definitely robs you of that, which to me explains why playing will be less fun. Moving faster on a side project or at work doesn't feel like the same kind of shortcut/cheat. Most of us no longer program in assembly language, and we still maintain a sense of achievement using elite languages, which naturally abstract away a lot of the details. Isn't using AI to hide away implementation details just a natural next step, where instead of lengthy error prone machine level code, you have a few modern language instructions?

The author is essentially arguing that fewer people will be able to build software in the future.

That's the opposite of what's happened over the past year or two. Now many more non-technical people can (and are) building software.

The financial barrier point is really great.

I feel the same with a lot of points made here, but hadn't yet thought about the financial one.

When I started out with web development that was one of the things I really loved. Anyone can just read about html, css and Javascript and get started with any kind of free to use code editor.

Though you can still do just that, it seems like you would always drag behind the 'cool guys' using AI.

Coding itself can be fun, perhaps especially when one is trying to optimize in some way (faster, less memory usage, more minimal, etc), but at least for me (been S/W eng for 45+ years) I think the real satisfaction is conquering the complexity and challenges of the project, and ultimately the ability to dream about something and conjure it up to become a reality. Maybe coding itself was more fun back in the day of 8-bit micros where everything was a challenge (not enough speed or memory), but nowadays typically that is not the case - it's more about the complexity of what is being built (unless it's some boilerplate CRUD app where there is no fun or challenge at all).

With today's AI, driven by code examples it was trained on, it seems more likely to be able to do a good job of optimization in many cases than to have gleaned the principles of conquering complexity, writing bug-free code that is easy and flexible to modify, etc. To be able to learn these "journeyman skills" an LLM would need to either have access to a large number of LARGE projects (not just Stack Overflow snippets) and/or the thought processes (typically not written down) of why certain design decisions were made for a given project.

So, at least for time being, as a developer wielding AI as a tool, I think we can still have the satisfaction of the higher level design (which may be unwise to leave to the AI, until it is better able to reason and learn), while leaving the drudgework (& a little bit of the fun) of coding to the tool. In any case we can still have the satisfaction of dreaming something up and making it real.

> In some countries, more than 90% of the population lives on less than $5 per day. If agentic AI code generation becomes the most effective way to write high-quality code, this will create a massive barrier to entry … Don't even get me started on the green house gas emissions of data centers...

My (naive?) assumption is that all of this will come down: the price (eventually free) and the energy costs.

Then again, may daughters know I am Pollyanna (someone has to be).

AI will be cheap to run.

The hardware for AI is getting cheaper and more efficient, and the models are getting less wasteful too.

Just a few years ago GPT-3.5 used to be a secret sauce running on the most expensive GPU racks, and now models beating it are available with open weights and run on high end consumer hardware. Few iterations down the line good-enough models will run on average hardware.

When that Xcom game came out, filmmaking, 3D graphics, and machine learning required super expensive hardware out of reach of most people. Now you can find objectively better hardware literally in the trash.

I'm not following the logic here. There are tons of free tier AI products available. That makes the world more fair for people in very poor countries not less.

For me, it’s the opposite, I had somewhat lost my love for my job as a developer between two JavaScript framework wars or wars between craftsmanship and agile. I think we now have the opportunity to return to addressing actual needs. For me, that has always been the driving force, an idea becomes a product. These agents have rekindled my desire to create things.

I can't see why it's a bitter prediction. It's an observation from all my life that boring, mind-numbing but high impact work makes the best money. Now smart people go into coding because it's a thrill, they enjoy doing it for the sake of it. Once this is no longer the case, these people will be out, and competition will become lower and there will be easier bucks to make.

>Will programming eventually be relegated to a hobby?

I don't regard programming as merely the act of outputing code. Planning, architecting, having a high level overview, keeping the objective in focus also matters.

Even if we regard programming as just writing code, we have to ask ourselves why we do it.

We plant cereals to be able to eat. At first we used some primitive stone tools to dig the fields. Then we used bronze tools, then iron tools. Then we employed horses to plough the fields more efficiently. Then we used tractors.

Our goal was to eat, not to plough the fields.

Many objects are mass produced now while they were the craft of the artisans centuries ago. We still have craftsmen who enjoy doing things by hand and whose products command a big premium over mass market products.

I don't have an issue if most of the code will be written by AI tools, provided that code is efficient and does exactly what we need. We will still have to manage and verify those tools, and to do that we will still have to understand the whole stack from the very bottom - digital gates and circuits to the highest abstractions.

AI is just another tool in the toolbox. Some carpenters like to use very simple hand tools while other swear by the most modern ones like CNC.

To put the cost into context, spending $5 a day on tools is ludicrously cheap compared to paying minimum wage, let alone a programmer’s salary. Programming is only free if you already know how to code and don’t value your time.

Many of us do write code for fun, but that results in a skewed perspective where we don’t realize how inaccessible it is for most people. Programmers are providers of expensive professional services and only businesses that spread the costs over many customers can afford us.

So if anything, these new tools will make some kinds of bespoke software development more accessible to people who couldn’t afford professional help before.

Although, most people don’t need to write new code at all. Using either free software or buying off-the-shelf software (such as from an app store) works fine for most people in most situations. Personal, customized software is a niche.

this article precisely captures what i have been thinking recently. it’s really demotivating me.

>I just missed writing code.

Even before AI really took of that was an experience many developers, including me, had. Outsourcing has taken over much of the industry. If you work in the west, there is a good probability that a large part of your work is managing remote teams, often in India or other low cost countries.

What AI could change is either reducing the value of outsourcing or make software development so accessible that managing the outsourcing becomes unnecessary.

Either way, I do believe that Software Developers are here to stay. They won't be writing much code in any case. A software developer in the US costs 100k a year and writing software simply will never again be worth 100k year. There are people and programs who are much cheaper.

It's normal flow of things in the industry, isn't it? It used to be an important skill for a programmer to optimize constantly. Tasks like "We need to cut halfkilobyte at least!" were challenging, and satisfying puzzles. And today you open a news webpage, it takes 1.5Gib and who cares? Typing speed used to be an important skill too, and nowadays one can be a decent software developer using two fingers. Memorizing names, and parameters used to be extremely important until autocomplete, and autosuggest appeared. I can expand this list to a hundred points probably.

Sure, we can throw code over the wall faster. Is that all that matters though? Just like in poetry, prose, images, etc, AI generates average or worse code. Sure, it may do the job and if your goal is to be average, fine, you should be worried. But has anyone with deep knowledge in programming and a desire to excel actually looked at AI-generated code and thought "omg, this is a work of art. it's so perfect and maintenance will be much easier than anything I could have done! plus, it matches all the requirements from the stakeholders"?

Don't get me wrong, it lets me be more productive sometimes but people that think the days of humans programming computers are numbered have a very rosy (and naive) view of the software engineering world, in my opinion.

> Forty-six percent of the global population lives on less than $5 per day. In some countries, more than 90% of the population lives on less than $5 per day. If agentic AI code generation becomes the most effective way to write high-quality code, this will create a massive barrier to entry. Access to technology is already a major class and inequality problem. My bitter prediction is that these expensive frontier models will become as indispensable for software development as they are inaccessible to most of the world’s population.

Forty-six percent of the global population has never hired a human programmer either because a good human programmer costs more than $5 a day{{citation needed}}.

The main use I find for LLMs is code review and corrections following a list of criteria. It helps to detect overlooked issues.

It is also useful for learning from independent code snippets, for e.g., learning a new API.

AI has made me love programming again. I can finally focus on the creative parts only.

Cost of AI coding tools may decrease in future making it more accessible for everyone. And we will all be forced to move up the value ladder.

We move up, down or sideways on the stack. That's the outcome. Not necessarily bad. It requires soul searching to find out new place.

The idea of "breaking the game" here is similar to that expressed in this other recent post: https://news.ycombinator.com/item?id=43650656 . The focus here is a bit different though.

> It makes economic sense, and capitalism is not sentimental.

I find this kind of fatalism irritating. If capitalism isn't doing what we as humans want it to do, we can change it.

Some people like to whittle wood. It’s no longer a career choice with strong prospects.

As for: ” In some countries, more than 90% of the population lives on less than $5 per day.”

Well, with the orders of magnitude difference already in place, this is not going to meaningfully impact that at all.

Im not dismissing this: I’m saying that it isn’t much of a building block in thinking about all of the things AI is going to change and should be addressed as a result because it’s simply in the pile of problems labeled “was here before, will be here after”.

And really, it ought to be thought of in the context of “can we leverage AI to help address this problem in ways we cannot do so now?”

my ai-pilled co worker committed some code using a promise with a lambda that resolved it in a one liner, the parameter was called resolve.

for some reason he also included a import for "resolve from dns".

(the code didn't even need a promise there)

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