5 ms·

Going full AI engineer, not touching code anymore

55 points by maxheyer 5mo ago

edrobap 5mo ago
[dead]
hootz 5mo ago
But the question is, will this atrophy our ability to write and understand code? Is reviewing enough? Won't we inevitably get lazy and stop reading enough code? Reading always was a worse way to learn than doing. When we stop doing, we will have to triple our reading (if that's even enough), but will we do that or just trust the agents more and more?
- maxheyer 5mo ago
  Trust creep is the part I worry about too. Today I read every diff.
- Glohrischi 5mo ago
  I think I read so much code over the last 15 years, that its not a thing i will lose. But at least for me, I really read a lot of code, a lot of PRs from others and evaluated them.
- jrflo 5mo ago
  I wonder if people thought something similar when moving from writing low level machine code by hand to high-level languages. No one looks at the actual machine instructions anymore! Will our ability to understand low level instructions atrophy?
  - hootz 5mo ago
    And they did atrophy! I only know assembly because I deliberately studied it and practiced it for reverse engineering. But in my view, no longer being able to understand high level code is a much, much bigger problem than not understanding assembly.
    - weakfish 5mo ago
      Especially because Markdown --> code is _non-deterministic_
      - hootz 5mo ago
        Yeah. Actually, that's a cool thing to think about. Will it be possible in the future for an LLM to be deterministic enough to the point of becoming essentially a text to code compiler? Like, an entire class of LLMs that are meant to be deterministic to the point that even upgrades to the model wouldn't completely change the outputs (it could have some breaking changes).
  - hedgehog 5mo ago
    There's clearly a range of outcomes, from the people pushing the envelope in system performance (look at the state of networking ASICs and the code to drive them) to people adopting hyper-complex frameworks for cloud orchestration and job coordination that turn a few screens of code into system so slow and complex it needs a team to maintain it. It's all happening at once, and it's probably ok. Keep in mind, knowing how to write assembly and knowing how to get good performance out of a CPU are two different things, modern chips are insanely complicated and the mental model is a long way from the days of the 386 or 68030 (let alone pre-MMU computing).
  - righthand 5mo ago
    This analogy is always weird to me, the change your talking about was still deterministic. Switching from programming to describing programming and having a machine make a best guess is not a deterministic shift as previously happened.
  - dijksterhuis 5mo ago
    reality is more nuanced. some people still need to inspect machine code by hand. people who primarily write SaaS django boilerplate don’t. the arguments were made back then, im sure. but, according to the worst offending and persistent ai-hyper comments on this site, this is apparently a paradigm shift unlike anything that’s done before. according t them we don’t even need to understand high level languages, let alone machine code. which is frankly ridiculous. i’m an “AI luddite”. but i accept there are useful use cases. that’s not where all the wasted money is going though.
  - snek_case 5mo ago
    The difference is that LLMs are not compilers. You can't trust the output to be correct. They routinely make bad design choices. If you're prototyping some kind of throwaway MVP, you're just sketching something, it's probably fine not to review it. If you're trying to build a piece of software that's going to survive for years, why are you doing this? The tech is clearly not yet fully mature. Just yesterday, I was trying to use Claude Opus 4.7 to debug an issue in a program that I wrote, and its solution was to remove a feature, change the design to eliminate the problem without consulting me. I only found out that it had removed this feature through testing. Imagine not reviewing things like that. How can people argue for this with a straight face? We'll probably get there eventually, but there's no need to rush before the tech is ready. Doing that is just being clueless.
    - soraminazuki 5mo ago
      The comparison with compilers is absurd on its face, yet some keep pushing it as if repeating it enough times will make it true.
      - DerArzt 5mo ago
        Why is it absurd?
        soraminazuki 5mo ago
        For the same reason others have explained here and elsewhere, with some writing entire articles on the topic. Compilers produce semantically equivalent translation of source code into target code. That's not at all what LLMs do. They produce unpredictable results from ambiguous specifications written by people who may or may not understand software engineering. Big difference.
      - snek_case 5mo ago
        The people who make that comparison are just showing how clueless they are IMO.
  - cguess 5mo ago
    It did atrophy, but more importantly understanding what's going on below the code you are writing, even if your project isn't assembly, also atrophied. When you're coding an Electron app with Javascript you're so far removed from any concept of the efficiency a modern CPU can achieve you stop caring about optimization. Speed and memory management don't matter and then you get... well, the modern web.
    - hootz 5mo ago
      And the modern web being usable is basically thanks to the people who understand lower level optimization.
  - linksnapzz 5mo ago
    The move to HLLs created new classes of problems that assembly programmers didn't face; so while the # of problems that necessitated understanding hw didn't shrink, it did relative to the list of things that could now go wrong.
  - dadoum 5mo ago
    The compiler has been written by a lot of very smart people, it is very well tested and sometimes has even been formally proven to output exactly what the language specifies, and I have a mental model of what the code it outputs does in relation to what I write. Nobody can be sure of what the LLM will output for a certain prompt. If you don't review what it outputs, it will not necessarily match your expectations. You could argue that it is the same as when you assign an intern to the task, but I personally would check what the intern writes (and in my experience they are more reliable than current AIs, of course not as quick).
  - cortesoft 5mo ago
    They absolutely did: https://vivekhaldar.com/articles/when-compilers-were-the--ai--that-scared-programmers/ https://vivekhaldar.com/articles/when-compilers-were-the--ai...
- lenerdenator 5mo ago
  I don't think it's necessarily a question of laziness. It's more about velocity. Your CTO was just shown a demo where a fairly complex piece of software was spat out in MVP form within a few hours. Something that used to take months is now more-or-less completed in a two-week period, including deployment. The CTO knows that competitors are seeing the exact same thing and are going to try it for themselves. Now your company has to use the LLM because that's going to enable the development speed seen in the demo if they want to stay in business. There's the iron triangle of engineering: fast, cheap, good. You used to have to pick two. And in reality, you still have to pick two, but a lot of this technology is sold as allowing you to pick all three. It lets you pump out a MVP: 1. fast - it's done in a few days 2. cheaply - you don't have to pay engineers as much or at all 3. it's "good" - it looks good enough for the client to accept it instead of suing you and give you revenue. The third part is where this breaks down. Like you say, people aren't reviewing this code. It's probably 85%-95% of the way to fulfilling all use cases, but that 5%-15% is the critical part where there's SLA violations and risks to business, property, or people. The thing is, clients have to find that within the first 90 days to have it impact the books for that quarter, and they probably won't. Also, you have lawyers who can drag it out further. If the company really gets screwed by quality problems, well, sell to a competitor or someone and return value to shareholders that way. There's always some way to get cash back. So we've pushed out code faster, gotten revenue booked, and have a way to not lose money in the short-term, which is ultimately the only term that matters. The goal was never making good code; it was making money as fast as possible. Velocity. LLMs deliver on that.
- doug_durham 5mo ago
  Accountability is the key. You are accountable for the work product. You need to do what is necessary to make sure that the product meets standards. How you do it is of secondary importance. If reading code is what is needed to guarantee quality and you stop, that is on you.
- soraminazuki 5mo ago
  Already happening. For many people, coding isn't the only thing they've abandoned. They've also traded science and engineering for LLM punditry. Rather than "focusing on solving problems," as they often claim, they spend their time chasing unscientific debates about which model or magic prompt "performs better." By unscientific, I mean there's nothing measurable, no reproducible methodology, and no way to validate their hypotheses. Or rather, their wild speculations that change every week.
- infinet 5mo ago
  There is a saying that many countries have offshored building hardware, aka manufacturing. Now they are offshoring software building to AI. Perhaps the silicon valley will grow a rust belt.
4rachelp 5mo ago
Feels AI-written as well and a recycling of 1000 versions of this point.
- droidjj 5mo ago
  Yes, it reads like every goddamn LinkedIn post these days.
  - snek_case 5mo ago
    I wish the tech field wasn't so full of clueless grifters. The most frustrating thing is that this kind of people, the kind who loudly and confidently assert bullshit claim based on insufficient knowledge, have a knack for positioning themselves in positions of power.
    - lenerdenator 5mo ago
      It's not just the tech field. It's everywhere these days.
- jsdalton 5mo ago
  It’s aggressively AI written. I’d rather just read the prompt. It’s unfortunate because many of us are going “full AI” when it comes to coding. And there are some true gives and takes that are interesting to explore. Sadly, this piece reads like pure hype.
liveoneggs 5mo ago
This would be fine if LLMs had a dedicated language or a well-tuned abstraction that suited their abilities well. Right now we are trying to fit our square languages into the LLM's round hole.
- hootz 5mo ago
  Where does my trapezoid-shaped highly compressed and ambiguous natural language go? Well, of course, it goes in the square hole!
righthand 5mo ago
I haven’t touched LLM coding beyond using TabNine originally and that has since been disabled. My LSP is good enough and I haven’t fallen behind on delivering code before deadlines. Not sure what the constant hype is about. And look I wrote all that in 1 paragraph without bullet points detailing anything over and over.
- 7777332215 5mo ago
  People using google translate to speak a language. Except the language contains more complexity, meaning, and compression that the writer can't describe without using more words/tokens than it would be to actually write with the same precision. They could instead use better tools to achieve equal results with higher confidence.
ori_b 5mo ago
Sounds like they're not touching writing either.
aselimov3 5mo ago
I think the main issue with this approach is that your solution space eventually narrows. You go from formulating unique solutions to flagging things that look wrong and then just picking an alternative LLM generated one. I’ve noticed this recently as all my side project work is being done by hand. If I do ask an LLM another question about something small it will offer solutions but doesn’t offer the solution I think makes sense in the architectures I’ve written. Slowly your brain just gets trained to mid thinking like an LLM. At least that’s my theory and I think there was some study that showed that interacting with an LLM at the start of a problem significantly narrowed the solution space to something sub optimal
- kbuchanan 5mo ago
  I agree this is a problem too, but I suspect mostly for novel(ish) software problems. For me, LLMs have expanded the solution space, because, while I used to be decent with SQL in Postgres, now I'm operating on a whole new level—the LLM's ability to make sense of Postgres' full suite of options, and the performance implications of the queries, is far beyond what I could have accomplished.
  - CharlieDigital 5mo ago
    It's a mixed bag. I've been working with Apache AGE (openCypher in Postgres) recently and found that left to its own device, the agent wrote terribly inefficient queries, even when given a test harness and instructions to examine the result of the query plan. It just didn't seem to understand the graph traversal, even when given the graph schema and small snippets. I ended up hand-writing the structural "skeleton" of the main query that I performance tuned to a certain extent and then handed it over to Codex to finish off. Once it had this skeleton to start from, it was able to do a much, much better job of writing this query.
  - aselimov3 5mo ago
    That’s a good point but I think this article above would push back on this point slightly. I certainly am able to do a lot more with LLMs because it can produce a passable solution in a lot of places but I’m not sure it expands my solution space really. I tend to separate what I’m able to build and what I’m able to solve. I can build a frontend with an LLM but I don’t think I’m able to solve frontend engineering problems.
Nesco 5mo ago
After a time the codebase feel foreign…
mfrankel 5mo ago
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supermatt 5mo ago
People bragging that they "dont touch code" and only "argue" with agents are reinventing the slowest possible IDE. Obviously the agents are great at producing large chunks of code, but they often make minor and sometimes trivial mistakes which need amending. Typing something like "in src/auth/session/token_manager.ts the refreshTokenExpiry variable should be refresh_token_expiry. update every reference and make sure nothing else changes" and waiting for the LLM to do its thing takes longer than opening the file and doing the rename yourself. If you are describing microscopic edits in natural language you are not avoiding coding. You are coding through an extremely verbose, lossy interface with higher latency and lower precision. EDIT: flagged?
- deleted 5mo ago
  [deleted]
- qaq 5mo ago
  Codex and CC are actually getting better at reviewing code and flagging issues. False positive rate dropped fairly significantly. Also obviously might be very personal preferency but creating clear specs and iterating on specs really helps to crystalize the approach I want to take to solving a given problem.
- barrkel 5mo ago
  See, I'd say something like: In the latest commit, refreshTokenExpiry should be snake case. Fix and make a note to do that in $LANG. Or otherwise scope the rule. The point is you don't need to be super verbose about it and you get to fix forward too, preventing the same issue reoccurring. You build knowledge and context that let you move faster.
- pluto_modadic 5mo ago
  this seems like a strawman... of /course/ you'd use the IDE to do ref renames?? AI isn't for that...
  - supermatt 5mo ago
    If that is true then you cant claim to be "not touching code anymore".
eranation 5mo ago
I’ve been on and off and on the bandwagon on this. My current verdict. When used properly, and if you actually read the code, pushback when needed and don’t get approval fatigue, and also practice hand coding here and there, you can definitely get immense productivity boosts while not compromising on quality. The issue is blindly accepting AI code, architecture, “are you sure this is prod ready?” “Ok ship it” is not going to end well. Too many times I caught the top SOTA models, 1M context, effort on max, suggest or do terrible things and say it with confidence. TLDR if you read the code (and understand the architecture), and know when to push back. This can work amazingly well. Otherwise you will gradually build a Rube Goldberg machine.
- iririaqq 5mo ago
  How many people actually have this discipline? I think most people dont want that discipline either. engineers in the west live in a world of convenience. The loss of discipline is almost expected. Apart from those who really love it and take pride. And we’ve seen that outsourcing to low cost regions = no discipline.
JBorrow 5mo ago
I just can't get behind this perspective, perhaps because I am a 'bad prompter', simply due to the lack of capability from current models. I end up rejecting them, asking them to implement again, they spew out tons of crap code instead of a 10 line fix, and on, and on. Note that I'm not saying the agents are useless. They certainly write a lot of code and sometimes it is good. But I don't think you can get away without touching code yourself simply because at some level it is often the most concise way to get your idea across. I find it best to implement a core set of changes by-hand, and then ask the system to e.g. replicate them to other dependencies. I genuinely don't understand how anyone can work on a system with any complexity, and get the results they actually want, without touching code.
- doug_durham 5mo ago
  There seems to be a split. There are a substantial group of people like yourself who don't get what they want from LLMs. There are folks like me who get excellent idiomatic code almost every time. Both experiences are real and should be respected. I'm hoping that future investigations will find out why that is the case.
WesolyKubeczek 5mo ago
Feels like what one of those morbidly obese people riding electric scooters would write about not missing walking one bit. God forbid they end up in an area where accessible alternatives to stairs are not a thing.
voidUpdate 5mo ago
What's interesting to me is how many people have found out with the LLM boom that they don't want to be developers/engineers, they want to be managers, delegating all the work to another entity and checking in occasionally to see how the coding is coming along
- DeathArrow 5mo ago
  I do not manage LLMs, I manage people. I always considered myself a builder, a creator. The end result is interesting and it's important for me the end result to be just as I envisioned it. Typing code isn't exciting. Thinking, planning, finding solutions and driving the LLM to implement the finished product is.
  - voidUpdate 5mo ago
    I'm happy for you that you enjoy being a manager. I'm just saying that a lot of people seem to have found they prefer managing another system writing the code for them asking it nicely to do things, rather than writing code myself. I'm in the camp of enjoying typing code, and I do not want to become a manager, either of LLMs or people
- chrisrickard 5mo ago
  I’ve found it interesting too. It’s like I spent 20 years mastering painting in watercolour… nerding out on other painters, canvas options, even the backstory on some guy that makes a specific paint etc. And I don’t regret any of that. but now I’m just loving creating my art 100x faster. I thought I loved the craft (and I did) but more, I loved the product.
  - sph 5mo ago
    So, in your metaphor, you never were an artist. You were just a poser. What I find cringeworthy is that it seems the entire industry is filled with posers and I didn’t learn this fact until now. As mentioned previously, I just wish the ‘posers’ chose a new job title for themselves rather than coopting the name of software engineer, so there is an easy way to tell each other apart. But passing for someone one really isn’t is the modus operandi of the poser.
pavel_lishin 5mo ago
Isn't that just being a manager?
the__alchemist 5mo ago
Everybody knows you don't go full AI engineer.
- ssenssei 5mo ago
  You know any AI war heroes? You went full AI engineer, man. Never go full AI engineer. You don't buy that? Ask Roy Lee, 2025, "Cheat On Everything." Remember? Went full AI engineer, went home empty-handed.
mariopt 5mo ago
I’m forcing myself to write code. This idea of reviewing an architecture that you never coded is just a fantasy. At some point in time, me and a lot of people, thought that using Redux was a great idea until we had to manage verbosity and middlewares. Now we had to deal with the consequences of our decisions and we learned. I also think this article is just a rage bait
- yehosef 5mo ago
  can an architect review a system he didn't design or build?
  - mariopt 5mo ago
    If you never coded that architecture yourself, you are not able to tell if it fits the problem, pros and cons, if the implementation is in accordance. Imagine reviewing CQRS without having built one
- tidewinner 5mo ago
  The people who I work with who have gone full LLM prompt engineer are the people who produced low quality, sloppy work. Generally they never liked to be challenged and never appeared to put much effort in. The same people might have put some effort into responding to a code review before, but now they just prompt the LLM with 'is this a valid point?' and respond with whatever it hallucinates. These are the people that are hard to work with. First thought reading this was yes it's rage bait.
- doug_durham 5mo ago
  You are choosing to be enraged. If a tool works it works.
yehosef 5mo ago
With all the people saying that you're going to have problems because the LLM is not good at refactoring or large code bases or OOP, etc. the point may be that if you're working to develop skills, an LLM herder might be a good one. Even if the models are almost, but not quite, good enough yet - they will be. When looking for a career move you might want to focus on the trajectory more than the current state.
everyone 5mo ago
Is anyone doing this who is not making CRUD web-apps or other very common types of programs for which there is masses of training data to copy from the net? I tend to do oddball stuff (eg. software for custom arcade machines, AR games) and any forays I've made into AI code have made it seem like a total waste of time for me. (ie. I will spend much longer trying to get AI do to a shitty job, compared to just doing it myself)
- the__alchemist 5mo ago
  It is a minefield for structural bio/chem.
- doug_durham 5mo ago
  I write low level highly performance sensitive code and I get excellent results using LLMs. It isn't a narrow area of applicability.
  - everyone 5mo ago
    "low level highly performance sensitive" doesnt mean uncommon. What you're doing may be common with loads of examples to copy. (I dont know cus u didnt say what you're actually doing)
lenerdenator 5mo ago
We're basically doing the same thing where I'm at. I do see the long-term goal as being the elimination of most engineering positions. If you can have an architect - or, even better, some solution manager talking directly to the customer - just prompt a solution into existing and monitor most of it, you can really reduce the headcount.
add-sub-mul-div 5mo ago
Most of the AI submissions are from people who are here to self-promote their own content and have little to no other participation. It's like this stuff appeals to a different audience than made up this site 5 years ago. Everything and everyone feels so nonsubstantive now.
- blanched 5mo ago
  These blogs are AI-written. Claude/ChatGPT love a follow-up. I guarantee they’re suggesting something along the lines of “Great catch on that typo. This is looking good. Ready for plenty of upvotes on Hacker News and Reddit!” And that’s assuming the author isn’t just prompting “I wrote a coding article. Where should I share it for attention?” That’s all to say that I think this /is/ largely a new cohort of the community.
fnoef 5mo ago
"The fun part was never lifting weight. The fun was in being buffed with a 6-pack and picking up women. The fun is in bullying those who are weaker than me. I never liked going to the gym and lifting weights. What I actually love is the result of the lifting, but I never wanted to do the hard work". Not saying this is a 1:1 parallel, or that writing is what makes you a good coder, but I do wonder - if you remove the entire process of making something, what is left there? Sure, people keep arguing that architecting or "managing" AI agents is the actual moat, but is this really? If you do not participate in the craft itself, how would you get better? I mean, I have amazing ideas for wooded furniture I'd like to build. I doubt that if you give me an LLM connected to a router that I would be able to build something by "architecture, review, push back, and argue". I simply lack the knowledge to make something out of wood. And the only way to get this knowledge is to go and make something and not "architect, review, push back, and argue".
the__alchemist 5mo ago
The author appears to have gone full AI blog writer as well.
Havoc 5mo ago
Same here. It’s working well, though only using it for personal projects. The one project that did give me pause was an S3 Server. Not entirely sure I trust that… Toying with the idea of sticking a proxy in between that runs the vibe coded S3 in parallel to a classic server and see if the results track
lysace 5mo ago
My professional career: Year 0-12: Coding lots, learning lots. Year 12-22: A product I built really took off. Now primarily building new stuff by talking to other engineers. Lots of product management/politics. Atrophying coding skills. Year 22-28: I'm tired of building by talking. Re-learning coding. Year 28-: "Here's this thing called Claude Code". I interface with it by... talking.
reeredfdfdf 5mo ago
The problem I have is that I find generic code reviews really, really boring. With agents I write less code but read more code that I didn't write myself, which makes the job more boring than it was. I would rather let AI do the code reviews and focus on test coverage.
randyrand 5mo ago
Very well written article. For my biggest codebase I too read every diff. I know the project intimately. I care about it and I’ll pay the cost if it’s wrong. For smaller greenfield projects it’s up in the air. If it works it works.
bilekas 5mo ago
> After many years into coding I found out that writing the code was the toll I paid to get those decisions into reality. I'm happy they are having fun, but these takes are getting worse and worse every day, this is the equivalent of saying, I don't like writing or typing but I love telling stories. No developer would ever say "I love typing on my split keyboard in vim, it's why I became a developer." Maybe it's not a bad thing though people are different and this is showing them what they really like, delegating certain things to focus on others. Maybe I should try work with an LLM to act as my architect.
bedobi 5mo ago
I'm a Software Engineer and I think the author is probably right that many Software Engineers are misguidedly placing too much weight on their ability to read and write code. The valuable part of Software Engineering isn't PARSING a solution into code and back again, taking into account all the idiosyncrasies and edge casey bugs of any given language chosen for the implementation. Of course that is a discrete and impressive skill, but it's no longer terribly valuable. The valuable part of Software Engineering is "given this problem, what's an elegant, efficient, testable, scalable, maintainable, observable solution?". Most of CS is already a solved problem, so even that is mostly a matter of assembling those solved-problem pieces together and choosing the flavor of how it's expressed. (for me, it's pure functions, for others, it might be OOP) AIs are pretty good at that too, so it seems to me like the Software Engineers role is now to cultivate taste (what, in a perfect world, systems SHOULD look like) and balance it with pragmatism. (what does the system/business/time/resource constraints look like TODAY)
carlos-menezes 5mo ago
This text is regurgitated on a daily basis. I skimmed through the text and could tell not only that but also that the author has given up on writing altogether. > I think harder about the real problems Are you /really/? If an LLM gives you an immediate, coherent answer, there's a risk you accept the framing too quickly instead of doing the harder work of questioning premises, testing alternatives and noticing what might be missing.
- basch 5mo ago
  > If an LLM gives you an immediate, coherent answer, there's a risk you accept the framing too quickly instead of doing the harder work of questioning premises, testing alternatives and noticing what might be missing. Arguably having a conversation with something so confident but random makes me more inclined to "verify before trust" instead of the usual "trust but verify." Im already very question premisy but interacting with ai 10x's that instinct. My skepticism level is higher because of temperature and seeing when I ask something multiple times I get dice roll answers.
chonydev 5mo ago
Following the calculator analogy made by another person here and not disrespectful but joking intentended but this sounds kinda: "I'm done. I'm not going to do a calculation, remember a single formula or theorem anymore. Now I'm just choose the problem that I want to solve and the math branch that I wanna use. I think all these educations stages (decades) was the toll we had to pay and I'm not going to pay anymore. " Also who can say that is able to consider all weights that each decision involves and be able to surpass AI's broad view!?. I mean ... mythos finding a full chain of processes to make an exploit from a single bug? We can beat that ?! For how long ? I don't know where it is going to end up but as a newcomer to the field I 'll try to keep learning programming and build a solid base. Focusing less on knowing all little syntax of each language or library and outsourcing all boring and repetitive tasks to AI. I don't take sides here: I welcome such a wonderful tool but everything has its tradeoffs.
4b11b4 5mo ago
Opposite, I trust less and less the more I use these things. Must write certain things myself, especially types. Sometimes I'll even touch a new file myself (I know, creating files yourself?!) and write some pseudocode in a new file alongside some voice vomit Also, /only/ verifying is exhausting...
redlewel 5mo ago
Only a few sentences in and its like reading linkedin... Obviously written using ai with little to no review. In regards to the title/subject, if you completely stop thinking about code in terms of actual programming comprehension you are setting yourself up for failure. Unless you are a senior with 5+YOE and have an insane list of useful projects completed without using AI, you need to keep learning features of the language and writing code by hand or your skills with atrophy and you will become less effective over time.
deleted 5mo ago
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Folcon 4mo ago
> This is the part I struggle with when I think about it. Years of identity rests on “I am someone who writes code”. That identity is now contingent on a tool stack that’s three years old and could regress. If it breaks, the identity goes with it, and I’m fine with that. > I think that’s the most honest signal I can give about what I actually valued. The thing I was doing all those years wasn’t writing code. I was making decisions and watching them become real. The agents make that loop shorter. Take the agents away and the loop becomes too long again. I’d rather do something else. What's really interesting to me and I'm honestly curious as to how many people are in the same boat as I am vs the author is that I have the same feeling and I'm not ok with it I think if LLM's disappeared tomorrow I could go back to coding without them, however there'd be that transition of scraping the rust off and honestly I don't like that It's really discomforting to feel like the codebase I'm working on is getting ever more foreign and strange, especially as LLM's when they communicate with you are persuasive that they are making things better, and they do work, for a given value of work anyway, it's really hard at times to tell looks right from is right I've come up with some strategies that mitigate this to a degree and I'm slowly trying to find more I think a lot of people are taking refuge in practices, but aren't entirely coming to terms with the actual scale of the difficulty of writing correct code, skating by on it being useful, which don't get me wrong isn't a bad thing, our clients pay us for creating useful things Not turning flops into heat However I get the uneasy feeling like our tools are very inadequate Types measure consistency, not correctness Tests and code coverage are very easy to game, and unless you've put in the discipline of creating something on the order of sqlite's test suite, there's likely to be an ever growing pool of latent footguns sitting in the code you're making And I'm not saying this to be negative or alarmist, at the end of the day it depends on what your goals are, and most working devs and startup folks are just trying to ship And we can't really argue that for many, they do help do that You will ship Something at least I find myself in this odd position of acknowledging that the coding world has shifted in ways that I find exciting and strange, and as much as I've begun to understand how to navigate this new environment, the part of me that felt deeply grounded in the things that I built is still feeling disquiet

55 points by maxheyer 5mo ago

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hootz 5mo ago

But the question is, will this atrophy our ability to write and understand code? Is reviewing enough? Won't we inevitably get lazy and stop reading enough code? Reading always was a worse way to learn than doing. When we stop doing, we will have to triple our reading (if that's even enough), but will we do that or just trust the agents more and more?

maxheyer 5mo ago
Trust creep is the part I worry about too. Today I read every diff.
Glohrischi 5mo ago
I think I read so much code over the last 15 years, that its not a thing i will lose. But at least for me, I really read a lot of code, a lot of PRs from others and evaluated them.
jrflo 5mo ago
I wonder if people thought something similar when moving from writing low level machine code by hand to high-level languages. No one looks at the actual machine instructions anymore! Will our ability to understand low level instructions atrophy?
- hootz 5mo ago
  And they did atrophy! I only know assembly because I deliberately studied it and practiced it for reverse engineering. But in my view, no longer being able to understand high level code is a much, much bigger problem than not understanding assembly.
  - weakfish 5mo ago
    Especially because Markdown --> code is _non-deterministic_
    - hootz 5mo ago
      Yeah. Actually, that's a cool thing to think about. Will it be possible in the future for an LLM to be deterministic enough to the point of becoming essentially a text to code compiler? Like, an entire class of LLMs that are meant to be deterministic to the point that even upgrades to the model wouldn't completely change the outputs (it could have some breaking changes).
- hedgehog 5mo ago
  There's clearly a range of outcomes, from the people pushing the envelope in system performance (look at the state of networking ASICs and the code to drive them) to people adopting hyper-complex frameworks for cloud orchestration and job coordination that turn a few screens of code into system so slow and complex it needs a team to maintain it. It's all happening at once, and it's probably ok. Keep in mind, knowing how to write assembly and knowing how to get good performance out of a CPU are two different things, modern chips are insanely complicated and the mental model is a long way from the days of the 386 or 68030 (let alone pre-MMU computing).
- righthand 5mo ago
  This analogy is always weird to me, the change your talking about was still deterministic. Switching from programming to describing programming and having a machine make a best guess is not a deterministic shift as previously happened.
- dijksterhuis 5mo ago
  reality is more nuanced. some people still need to inspect machine code by hand. people who primarily write SaaS django boilerplate don’t. the arguments were made back then, im sure. but, according to the worst offending and persistent ai-hyper comments on this site, this is apparently a paradigm shift unlike anything that’s done before. according t them we don’t even need to understand high level languages, let alone machine code. which is frankly ridiculous. i’m an “AI luddite”. but i accept there are useful use cases. that’s not where all the wasted money is going though.
- snek_case 5mo ago
  The difference is that LLMs are not compilers. You can't trust the output to be correct. They routinely make bad design choices. If you're prototyping some kind of throwaway MVP, you're just sketching something, it's probably fine not to review it. If you're trying to build a piece of software that's going to survive for years, why are you doing this? The tech is clearly not yet fully mature. Just yesterday, I was trying to use Claude Opus 4.7 to debug an issue in a program that I wrote, and its solution was to remove a feature, change the design to eliminate the problem without consulting me. I only found out that it had removed this feature through testing. Imagine not reviewing things like that. How can people argue for this with a straight face? We'll probably get there eventually, but there's no need to rush before the tech is ready. Doing that is just being clueless.
  - soraminazuki 5mo ago
    The comparison with compilers is absurd on its face, yet some keep pushing it as if repeating it enough times will make it true.
    - DerArzt 5mo ago
      Why is it absurd?
      - soraminazuki 5mo ago
        For the same reason others have explained here and elsewhere, with some writing entire articles on the topic. Compilers produce semantically equivalent translation of source code into target code. That's not at all what LLMs do. They produce unpredictable results from ambiguous specifications written by people who may or may not understand software engineering. Big difference.
    - snek_case 5mo ago
      The people who make that comparison are just showing how clueless they are IMO.
- cguess 5mo ago
  It did atrophy, but more importantly understanding what's going on below the code you are writing, even if your project isn't assembly, also atrophied. When you're coding an Electron app with Javascript you're so far removed from any concept of the efficiency a modern CPU can achieve you stop caring about optimization. Speed and memory management don't matter and then you get... well, the modern web.
  - hootz 5mo ago
    And the modern web being usable is basically thanks to the people who understand lower level optimization.
- linksnapzz 5mo ago
  The move to HLLs created new classes of problems that assembly programmers didn't face; so while the # of problems that necessitated understanding hw didn't shrink, it did relative to the list of things that could now go wrong.
- dadoum 5mo ago
  The compiler has been written by a lot of very smart people, it is very well tested and sometimes has even been formally proven to output exactly what the language specifies, and I have a mental model of what the code it outputs does in relation to what I write. Nobody can be sure of what the LLM will output for a certain prompt. If you don't review what it outputs, it will not necessarily match your expectations. You could argue that it is the same as when you assign an intern to the task, but I personally would check what the intern writes (and in my experience they are more reliable than current AIs, of course not as quick).
- cortesoft 5mo ago
  They absolutely did: https://vivekhaldar.com/articles/when-compilers-were-the--ai--that-scared-programmers/ https://vivekhaldar.com/articles/when-compilers-were-the--ai...
lenerdenator 5mo ago
I don't think it's necessarily a question of laziness. It's more about velocity. Your CTO was just shown a demo where a fairly complex piece of software was spat out in MVP form within a few hours. Something that used to take months is now more-or-less completed in a two-week period, including deployment. The CTO knows that competitors are seeing the exact same thing and are going to try it for themselves. Now your company has to use the LLM because that's going to enable the development speed seen in the demo if they want to stay in business. There's the iron triangle of engineering: fast, cheap, good. You used to have to pick two. And in reality, you still have to pick two, but a lot of this technology is sold as allowing you to pick all three. It lets you pump out a MVP: 1. fast - it's done in a few days 2. cheaply - you don't have to pay engineers as much or at all 3. it's "good" - it looks good enough for the client to accept it instead of suing you and give you revenue. The third part is where this breaks down. Like you say, people aren't reviewing this code. It's probably 85%-95% of the way to fulfilling all use cases, but that 5%-15% is the critical part where there's SLA violations and risks to business, property, or people. The thing is, clients have to find that within the first 90 days to have it impact the books for that quarter, and they probably won't. Also, you have lawyers who can drag it out further. If the company really gets screwed by quality problems, well, sell to a competitor or someone and return value to shareholders that way. There's always some way to get cash back. So we've pushed out code faster, gotten revenue booked, and have a way to not lose money in the short-term, which is ultimately the only term that matters. The goal was never making good code; it was making money as fast as possible. Velocity. LLMs deliver on that.
doug_durham 5mo ago
Accountability is the key. You are accountable for the work product. You need to do what is necessary to make sure that the product meets standards. How you do it is of secondary importance. If reading code is what is needed to guarantee quality and you stop, that is on you.
soraminazuki 5mo ago
Already happening. For many people, coding isn't the only thing they've abandoned. They've also traded science and engineering for LLM punditry. Rather than "focusing on solving problems," as they often claim, they spend their time chasing unscientific debates about which model or magic prompt "performs better." By unscientific, I mean there's nothing measurable, no reproducible methodology, and no way to validate their hypotheses. Or rather, their wild speculations that change every week.
infinet 5mo ago
There is a saying that many countries have offshored building hardware, aka manufacturing. Now they are offshoring software building to AI. Perhaps the silicon valley will grow a rust belt.

4rachelp 5mo ago

Feels AI-written as well and a recycling of 1000 versions of this point.

droidjj 5mo ago
Yes, it reads like every goddamn LinkedIn post these days.
- snek_case 5mo ago
  I wish the tech field wasn't so full of clueless grifters. The most frustrating thing is that this kind of people, the kind who loudly and confidently assert bullshit claim based on insufficient knowledge, have a knack for positioning themselves in positions of power.
  - lenerdenator 5mo ago
    It's not just the tech field. It's everywhere these days.
jsdalton 5mo ago
It’s aggressively AI written. I’d rather just read the prompt. It’s unfortunate because many of us are going “full AI” when it comes to coding. And there are some true gives and takes that are interesting to explore. Sadly, this piece reads like pure hype.

liveoneggs 5mo ago

This would be fine if LLMs had a dedicated language or a well-tuned abstraction that suited their abilities well. Right now we are trying to fit our square languages into the LLM's round hole.

hootz 5mo ago
Where does my trapezoid-shaped highly compressed and ambiguous natural language go? Well, of course, it goes in the square hole!

righthand 5mo ago

I haven’t touched LLM coding beyond using TabNine originally and that has since been disabled. My LSP is good enough and I haven’t fallen behind on delivering code before deadlines. Not sure what the constant hype is about. And look I wrote all that in 1 paragraph without bullet points detailing anything over and over.

7777332215 5mo ago
People using google translate to speak a language. Except the language contains more complexity, meaning, and compression that the writer can't describe without using more words/tokens than it would be to actually write with the same precision. They could instead use better tools to achieve equal results with higher confidence.

ori_b 5mo ago

Sounds like they're not touching writing either.

aselimov3 5mo ago

I think the main issue with this approach is that your solution space eventually narrows. You go from formulating unique solutions to flagging things that look wrong and then just picking an alternative LLM generated one. I’ve noticed this recently as all my side project work is being done by hand. If I do ask an LLM another question about something small it will offer solutions but doesn’t offer the solution I think makes sense in the architectures I’ve written. Slowly your brain just gets trained to mid thinking like an LLM. At least that’s my theory and I think there was some study that showed that interacting with an LLM at the start of a problem significantly narrowed the solution space to something sub optimal

kbuchanan 5mo ago
I agree this is a problem too, but I suspect mostly for novel(ish) software problems. For me, LLMs have expanded the solution space, because, while I used to be decent with SQL in Postgres, now I'm operating on a whole new level—the LLM's ability to make sense of Postgres' full suite of options, and the performance implications of the queries, is far beyond what I could have accomplished.
- CharlieDigital 5mo ago
  It's a mixed bag. I've been working with Apache AGE (openCypher in Postgres) recently and found that left to its own device, the agent wrote terribly inefficient queries, even when given a test harness and instructions to examine the result of the query plan. It just didn't seem to understand the graph traversal, even when given the graph schema and small snippets. I ended up hand-writing the structural "skeleton" of the main query that I performance tuned to a certain extent and then handed it over to Codex to finish off. Once it had this skeleton to start from, it was able to do a much, much better job of writing this query.
- aselimov3 5mo ago
  That’s a good point but I think this article above would push back on this point slightly. I certainly am able to do a lot more with LLMs because it can produce a passable solution in a lot of places but I’m not sure it expands my solution space really. I tend to separate what I’m able to build and what I’m able to solve. I can build a frontend with an LLM but I don’t think I’m able to solve frontend engineering problems.

Nesco 5mo ago

After a time the codebase feel foreign…

mfrankel 5mo ago

[dead]

supermatt 5mo ago

People bragging that they "dont touch code" and only "argue" with agents are reinventing the slowest possible IDE. Obviously the agents are great at producing large chunks of code, but they often make minor and sometimes trivial mistakes which need amending. Typing something like "in src/auth/session/token_manager.ts the refreshTokenExpiry variable should be refresh_token_expiry. update every reference and make sure nothing else changes" and waiting for the LLM to do its thing takes longer than opening the file and doing the rename yourself. If you are describing microscopic edits in natural language you are not avoiding coding. You are coding through an extremely verbose, lossy interface with higher latency and lower precision. EDIT: flagged?

deleted 5mo ago
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qaq 5mo ago
Codex and CC are actually getting better at reviewing code and flagging issues. False positive rate dropped fairly significantly. Also obviously might be very personal preferency but creating clear specs and iterating on specs really helps to crystalize the approach I want to take to solving a given problem.
barrkel 5mo ago
See, I'd say something like: In the latest commit, refreshTokenExpiry should be snake case. Fix and make a note to do that in $LANG. Or otherwise scope the rule. The point is you don't need to be super verbose about it and you get to fix forward too, preventing the same issue reoccurring. You build knowledge and context that let you move faster.
pluto_modadic 5mo ago
this seems like a strawman... of /course/ you'd use the IDE to do ref renames?? AI isn't for that...
- supermatt 5mo ago
  If that is true then you cant claim to be "not touching code anymore".

eranation 5mo ago

I’ve been on and off and on the bandwagon on this. My current verdict. When used properly, and if you actually read the code, pushback when needed and don’t get approval fatigue, and also practice hand coding here and there, you can definitely get immense productivity boosts while not compromising on quality. The issue is blindly accepting AI code, architecture, “are you sure this is prod ready?” “Ok ship it” is not going to end well. Too many times I caught the top SOTA models, 1M context, effort on max, suggest or do terrible things and say it with confidence. TLDR if you read the code (and understand the architecture), and know when to push back. This can work amazingly well. Otherwise you will gradually build a Rube Goldberg machine.

iririaqq 5mo ago
How many people actually have this discipline? I think most people dont want that discipline either. engineers in the west live in a world of convenience. The loss of discipline is almost expected. Apart from those who really love it and take pride. And we’ve seen that outsourcing to low cost regions = no discipline.

JBorrow 5mo ago

I just can't get behind this perspective, perhaps because I am a 'bad prompter', simply due to the lack of capability from current models. I end up rejecting them, asking them to implement again, they spew out tons of crap code instead of a 10 line fix, and on, and on. Note that I'm not saying the agents are useless. They certainly write a lot of code and sometimes it is good. But I don't think you can get away without touching code yourself simply because at some level it is often the most concise way to get your idea across. I find it best to implement a core set of changes by-hand, and then ask the system to e.g. replicate them to other dependencies. I genuinely don't understand how anyone can work on a system with any complexity, and get the results they actually want, without touching code.

doug_durham 5mo ago
There seems to be a split. There are a substantial group of people like yourself who don't get what they want from LLMs. There are folks like me who get excellent idiomatic code almost every time. Both experiences are real and should be respected. I'm hoping that future investigations will find out why that is the case.

WesolyKubeczek 5mo ago

Feels like what one of those morbidly obese people riding electric scooters would write about not missing walking one bit. God forbid they end up in an area where accessible alternatives to stairs are not a thing.

voidUpdate 5mo ago

What's interesting to me is how many people have found out with the LLM boom that they don't want to be developers/engineers, they want to be managers, delegating all the work to another entity and checking in occasionally to see how the coding is coming along

DeathArrow 5mo ago
I do not manage LLMs, I manage people. I always considered myself a builder, a creator. The end result is interesting and it's important for me the end result to be just as I envisioned it. Typing code isn't exciting. Thinking, planning, finding solutions and driving the LLM to implement the finished product is.
- voidUpdate 5mo ago
  I'm happy for you that you enjoy being a manager. I'm just saying that a lot of people seem to have found they prefer managing another system writing the code for them asking it nicely to do things, rather than writing code myself. I'm in the camp of enjoying typing code, and I do not want to become a manager, either of LLMs or people
chrisrickard 5mo ago
I’ve found it interesting too. It’s like I spent 20 years mastering painting in watercolour… nerding out on other painters, canvas options, even the backstory on some guy that makes a specific paint etc. And I don’t regret any of that. but now I’m just loving creating my art 100x faster. I thought I loved the craft (and I did) but more, I loved the product.
- sph 5mo ago
  So, in your metaphor, you never were an artist. You were just a poser. What I find cringeworthy is that it seems the entire industry is filled with posers and I didn’t learn this fact until now. As mentioned previously, I just wish the ‘posers’ chose a new job title for themselves rather than coopting the name of software engineer, so there is an easy way to tell each other apart. But passing for someone one really isn’t is the modus operandi of the poser.

pavel_lishin 5mo ago

Isn't that just being a manager?

the__alchemist 5mo ago

Everybody knows you don't go full AI engineer.

ssenssei 5mo ago
You know any AI war heroes? You went full AI engineer, man. Never go full AI engineer. You don't buy that? Ask Roy Lee, 2025, "Cheat On Everything." Remember? Went full AI engineer, went home empty-handed.

mariopt 5mo ago

I’m forcing myself to write code. This idea of reviewing an architecture that you never coded is just a fantasy. At some point in time, me and a lot of people, thought that using Redux was a great idea until we had to manage verbosity and middlewares. Now we had to deal with the consequences of our decisions and we learned. I also think this article is just a rage bait

yehosef 5mo ago
can an architect review a system he didn't design or build?
- mariopt 5mo ago
  If you never coded that architecture yourself, you are not able to tell if it fits the problem, pros and cons, if the implementation is in accordance. Imagine reviewing CQRS without having built one
tidewinner 5mo ago
The people who I work with who have gone full LLM prompt engineer are the people who produced low quality, sloppy work. Generally they never liked to be challenged and never appeared to put much effort in. The same people might have put some effort into responding to a code review before, but now they just prompt the LLM with 'is this a valid point?' and respond with whatever it hallucinates. These are the people that are hard to work with. First thought reading this was yes it's rage bait.
doug_durham 5mo ago
You are choosing to be enraged. If a tool works it works.

yehosef 5mo ago

With all the people saying that you're going to have problems because the LLM is not good at refactoring or large code bases or OOP, etc. the point may be that if you're working to develop skills, an LLM herder might be a good one. Even if the models are almost, but not quite, good enough yet - they will be. When looking for a career move you might want to focus on the trajectory more than the current state.

everyone 5mo ago

Is anyone doing this who is not making CRUD web-apps or other very common types of programs for which there is masses of training data to copy from the net? I tend to do oddball stuff (eg. software for custom arcade machines, AR games) and any forays I've made into AI code have made it seem like a total waste of time for me. (ie. I will spend much longer trying to get AI do to a shitty job, compared to just doing it myself)

the__alchemist 5mo ago
It is a minefield for structural bio/chem.
doug_durham 5mo ago
I write low level highly performance sensitive code and I get excellent results using LLMs. It isn't a narrow area of applicability.
- everyone 5mo ago
  "low level highly performance sensitive" doesnt mean uncommon. What you're doing may be common with loads of examples to copy. (I dont know cus u didnt say what you're actually doing)

lenerdenator 5mo ago

We're basically doing the same thing where I'm at. I do see the long-term goal as being the elimination of most engineering positions. If you can have an architect - or, even better, some solution manager talking directly to the customer - just prompt a solution into existing and monitor most of it, you can really reduce the headcount.

add-sub-mul-div 5mo ago

Most of the AI submissions are from people who are here to self-promote their own content and have little to no other participation. It's like this stuff appeals to a different audience than made up this site 5 years ago. Everything and everyone feels so nonsubstantive now.

blanched 5mo ago
These blogs are AI-written. Claude/ChatGPT love a follow-up. I guarantee they’re suggesting something along the lines of “Great catch on that typo. This is looking good. Ready for plenty of upvotes on Hacker News and Reddit!” And that’s assuming the author isn’t just prompting “I wrote a coding article. Where should I share it for attention?” That’s all to say that I think this /is/ largely a new cohort of the community.

fnoef 5mo ago

"The fun part was never lifting weight. The fun was in being buffed with a 6-pack and picking up women. The fun is in bullying those who are weaker than me. I never liked going to the gym and lifting weights. What I actually love is the result of the lifting, but I never wanted to do the hard work". Not saying this is a 1:1 parallel, or that writing is what makes you a good coder, but I do wonder - if you remove the entire process of making something, what is left there? Sure, people keep arguing that architecting or "managing" AI agents is the actual moat, but is this really? If you do not participate in the craft itself, how would you get better? I mean, I have amazing ideas for wooded furniture I'd like to build. I doubt that if you give me an LLM connected to a router that I would be able to build something by "architecture, review, push back, and argue". I simply lack the knowledge to make something out of wood. And the only way to get this knowledge is to go and make something and not "architect, review, push back, and argue".

the__alchemist 5mo ago

The author appears to have gone full AI blog writer as well.

Havoc 5mo ago

Same here. It’s working well, though only using it for personal projects. The one project that did give me pause was an S3 Server. Not entirely sure I trust that… Toying with the idea of sticking a proxy in between that runs the vibe coded S3 in parallel to a classic server and see if the results track

lysace 5mo ago

My professional career: Year 0-12: Coding lots, learning lots. Year 12-22: A product I built really took off. Now primarily building new stuff by talking to other engineers. Lots of product management/politics. Atrophying coding skills. Year 22-28: I'm tired of building by talking. Re-learning coding. Year 28-: "Here's this thing called Claude Code". I interface with it by... talking.

reeredfdfdf 5mo ago

The problem I have is that I find generic code reviews really, really boring. With agents I write less code but read more code that I didn't write myself, which makes the job more boring than it was. I would rather let AI do the code reviews and focus on test coverage.

randyrand 5mo ago

Very well written article. For my biggest codebase I too read every diff. I know the project intimately. I care about it and I’ll pay the cost if it’s wrong. For smaller greenfield projects it’s up in the air. If it works it works.

bilekas 5mo ago

> After many years into coding I found out that writing the code was the toll I paid to get those decisions into reality. I'm happy they are having fun, but these takes are getting worse and worse every day, this is the equivalent of saying, I don't like writing or typing but I love telling stories. No developer would ever say "I love typing on my split keyboard in vim, it's why I became a developer." Maybe it's not a bad thing though people are different and this is showing them what they really like, delegating certain things to focus on others. Maybe I should try work with an LLM to act as my architect.

bedobi 5mo ago

I'm a Software Engineer and I think the author is probably right that many Software Engineers are misguidedly placing too much weight on their ability to read and write code. The valuable part of Software Engineering isn't PARSING a solution into code and back again, taking into account all the idiosyncrasies and edge casey bugs of any given language chosen for the implementation. Of course that is a discrete and impressive skill, but it's no longer terribly valuable. The valuable part of Software Engineering is "given this problem, what's an elegant, efficient, testable, scalable, maintainable, observable solution?". Most of CS is already a solved problem, so even that is mostly a matter of assembling those solved-problem pieces together and choosing the flavor of how it's expressed. (for me, it's pure functions, for others, it might be OOP) AIs are pretty good at that too, so it seems to me like the Software Engineers role is now to cultivate taste (what, in a perfect world, systems SHOULD look like) and balance it with pragmatism. (what does the system/business/time/resource constraints look like TODAY)

carlos-menezes 5mo ago

This text is regurgitated on a daily basis. I skimmed through the text and could tell not only that but also that the author has given up on writing altogether. > I think harder about the real problems Are you /really/? If an LLM gives you an immediate, coherent answer, there's a risk you accept the framing too quickly instead of doing the harder work of questioning premises, testing alternatives and noticing what might be missing.

basch 5mo ago
> If an LLM gives you an immediate, coherent answer, there's a risk you accept the framing too quickly instead of doing the harder work of questioning premises, testing alternatives and noticing what might be missing. Arguably having a conversation with something so confident but random makes me more inclined to "verify before trust" instead of the usual "trust but verify." Im already very question premisy but interacting with ai 10x's that instinct. My skepticism level is higher because of temperature and seeing when I ask something multiple times I get dice roll answers.

chonydev 5mo ago

Following the calculator analogy made by another person here and not disrespectful but joking intentended but this sounds kinda: "I'm done. I'm not going to do a calculation, remember a single formula or theorem anymore. Now I'm just choose the problem that I want to solve and the math branch that I wanna use. I think all these educations stages (decades) was the toll we had to pay and I'm not going to pay anymore. " Also who can say that is able to consider all weights that each decision involves and be able to surpass AI's broad view!?. I mean ... mythos finding a full chain of processes to make an exploit from a single bug? We can beat that ?! For how long ? I don't know where it is going to end up but as a newcomer to the field I 'll try to keep learning programming and build a solid base. Focusing less on knowing all little syntax of each language or library and outsourcing all boring and repetitive tasks to AI. I don't take sides here: I welcome such a wonderful tool but everything has its tradeoffs.

4b11b4 5mo ago

Opposite, I trust less and less the more I use these things. Must write certain things myself, especially types. Sometimes I'll even touch a new file myself (I know, creating files yourself?!) and write some pseudocode in a new file alongside some voice vomit Also, /only/ verifying is exhausting...

redlewel 5mo ago

Only a few sentences in and its like reading linkedin... Obviously written using ai with little to no review. In regards to the title/subject, if you completely stop thinking about code in terms of actual programming comprehension you are setting yourself up for failure. Unless you are a senior with 5+YOE and have an insane list of useful projects completed without using AI, you need to keep learning features of the language and writing code by hand or your skills with atrophy and you will become less effective over time.

deleted 5mo ago

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Folcon 4mo ago

> This is the part I struggle with when I think about it. Years of identity rests on “I am someone who writes code”. That identity is now contingent on a tool stack that’s three years old and could regress. If it breaks, the identity goes with it, and I’m fine with that. > I think that’s the most honest signal I can give about what I actually valued. The thing I was doing all those years wasn’t writing code. I was making decisions and watching them become real. The agents make that loop shorter. Take the agents away and the loop becomes too long again. I’d rather do something else. What's really interesting to me and I'm honestly curious as to how many people are in the same boat as I am vs the author is that I have the same feeling and I'm not ok with it I think if LLM's disappeared tomorrow I could go back to coding without them, however there'd be that transition of scraping the rust off and honestly I don't like that It's really discomforting to feel like the codebase I'm working on is getting ever more foreign and strange, especially as LLM's when they communicate with you are persuasive that they are making things better, and they do work, for a given value of work anyway, it's really hard at times to tell looks right from is right I've come up with some strategies that mitigate this to a degree and I'm slowly trying to find more I think a lot of people are taking refuge in practices, but aren't entirely coming to terms with the actual scale of the difficulty of writing correct code, skating by on it being useful, which don't get me wrong isn't a bad thing, our clients pay us for creating useful things Not turning flops into heat However I get the uneasy feeling like our tools are very inadequate Types measure consistency, not correctness Tests and code coverage are very easy to game, and unless you've put in the discipline of creating something on the order of sqlite's test suite, there's likely to be an ever growing pool of latent footguns sitting in the code you're making And I'm not saying this to be negative or alarmist, at the end of the day it depends on what your goals are, and most working devs and startup folks are just trying to ship And we can't really argue that for many, they do help do that You will ship Something at least I find myself in this odd position of acknowledging that the coding world has shifted in ways that I find exciting and strange, and as much as I've begun to understand how to navigate this new environment, the part of me that felt deeply grounded in the things that I built is still feeling disquiet