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AI Made Writing Code Easier. It Made Being an Engineer Harder

AI Made Writing Code Easier. It Made Being an Engineer Harder

saikatsg

Comments (198)

  • hackersk
    This resonates. I've shipped 7 side projects in the past year using AI heavily. The code writing part got 10x faster. But I've noticed something counterintuitive: the total time from idea to shipped product barely decreased.Why? Because the bottleneck was never typing code. It was always understanding the problem, making architectural decisions, debugging edge cases, and most importantly - knowing what NOT to build.AI made me faster at producing code, but it also made me produce MORE code, which means more surface area for bugs, more maintenance burden, more complexity to reason about. The discipline of "write less code" is harder now because writing code costs almost nothing.The engineers who thrive will be the ones who can resist the temptation to over-engineer when the marginal cost of adding complexity drops to near zero.
  • Spide_r
    Its worth mentioning that this essay has some signs of being either partially AI generated or heavily edited through an LLM. Some of the signs are there (It's not X, it's Y), With the blog having gone from nearly zero activity between 2015 and 2025 to have it explode in posts and text output since then also raises an eyebrow.
  • manofmanysmiles
    > Here is something that gets lost in all the excitement about AI productivity: most software engineers became engineers because they love writing code.1) I guess I am not included in the set named "most software engineers." 2) If the title is "Software Engineer," I think I should be engineering, not coding.This has probably been beaten to death, but I think this is the biggest disciminating question between "pro ai" and "against ai" in the software world is: "Dp you do (this) becuase you like writing code, or because you like building things for the world?"Of course I don't think it's a binary decision.Although I more more motivated by building things, I do somewhat miss the programmer flow state I used to get more often.
  • oytis
    > you are not imagining things. The job changed. The expectations changed. And nobody sent a memo.Looks like something AI would say. Regardless of how it really was written
  • jatins
  • daemonk
    It's a different skillset and way of thinking. Engineers tend to think vertically deep on technical problems. With AI, you have to think horizontally broad and vertically up on the architectural problem. The trick is to be comfortable relegating the details to AI.One concrete example of this realization was when I was researching how to optimize my claude code environment with agents, skills, etc. I read a lot of technical documents on how these supplemental plugins work and how to create them. After an hour of reading through all this, I realized I could just ask Claude to optimize the environment for me given the project context. So I did, and it was able to point out plugins, skills, agents that I can install or create. I gave it permission to create them and it all worked out.This was a case of where I should not think more technically deeper, but at a more "meta" level to define the project enough for Claude to figure out how to optimize the environment. Whether that gave real gains is another question of course. But I have anecdotally observed faster results and less token usage due context caching and slightly more tools-directed prompts.
  • RevEng
    One supposition I see in this and so many other articles is that using AI to generate code results in not knowing how it works. I believe that's only true for "vibe coding", not for engineers using AI to generate code. The difference is in how much you plan, design, and specify upfront.If you give an AI a very general prompt to make an app that does X, it could build that in any imaginable way. Someone who doesn't know how these things are done wouldn't understand what way was chosen and the trade-offs involved. If they don't even look at the code, they have no idea how it works at all. This is dangerous because they are entirely dependant on the AI to make good decisions and to make any changes in the future.Someone who practices engineering by researching, considering their options, planning and designing, and creating a specification, leaves nothing up to chance. When the prompt is detailed, the outcome is constrained to the engineer's intent. If they then review the work by seeing that it wrote what they had in mind, they know that it worked and they know that the system design matches their own design. They know how it works because they designed it and they can modify that design. They can and have read the code so they can modify it without the help of the AI.If you know what code you want generated, reviewing it is easy - just look and see if it's what you expected. If you didn't think ahead about what the code would look like, reviewing is hard because you have to start by figuring out what the codebase even does.This goes the same for working in small iterations rather than prompting am entire application into existence. We all know how difficult it is to review large changes and why we prefer small changes. Those same rules apply for iterations regardless of whether it was written by a person or an AI.AI code generation can be helpful if the engineer continues acting as an engineer. It's only when someone who isn't an engineer or when an engineer abdicates their responsibilities to the AI that we end up with an unmaintainable mess. It's no different than amateurs writing scripts and spreadsheets without a full understanding of the implications of their implementation. Good software comes from good engineering, not just generating code; the code is merely the language by which we express our ideas.
  • simianwords
    The post is right superficially. It made being an engineer harder because it took away the easy parts that anyone can do and it forces engineers to think of the hard ones.No jobs get easier with automation - they always move a step up in abstraction level.An accountant who was super proficient in adding numbers no longer can rely on those skills once calculator was invented.
  • EliRivers
    "the skills that the new engineering landscape actually requires: system design, architectural thinking, product reasoning, security awareness, and the ability to critically evaluate code they did not write."These, surely, are the skills they always needed? Anyone who didn't have these skills was little more than a human chatgpt already, receiving prompts and simply presenting the results to someone for evaluation.
  • __bjoernd
    > Here is something that gets lost in all the excitement about AI productivity: most software engineers became engineers because they love writing code.This resonates somewhat, but for a different reason. My mental model is that there are two kinds of developers, the craftsmen and the artists.The artist considers the act of writing code their actual fulfillment. They thrive on beautifully written code. They are often attached to their code to a point where they will be hurt if someone criticizes (or even deletes) it.The craftsman understands that code exists to serve a purpose and that is to make someone's life easier. This can be a totally non-technical customer/user that now can get their work done better. It could be another developer that benefits from using a library we wrote.The artist hates LLMs as it takes away their work and replaces their works of beauty with generic, templatized code.The craftsman acknowledges that LLMs are another tool in the toolbelt and using them will make them create more benefits for their customers.
  • ukuina
    > code is for humans to readIs this still true?
  • mark-r
    There's nothing new about this pattern. When the tractor was invented, the farmer didn't get to knock off early. He just started producing 10x more. Then the tractors got bigger and more powerful, and the things you used them with got more sophisticated too and suddenly you're producing 100x more.
  • fzysingularity
    AI allows you to accelerate the initial build process, but I think engineering is all about craftsmanship. Today most LLMs have poor taste and chipping away the cruft matters more than ever.
  • devsda
    Ah, just in time summarizing what we went through recently. Our "leaders" officially added these to our already nonsensical list of goals.A. Measurably demonstrate that atleast 50% of code/tests are AI generated.B. X% Faster delivery timelines due to improved productivity tools.You can't expect to make a pizza in 50% less time just because you bought a faster doughmaker. Specially when you don't even know whether the dough comes out under kneaded, over kneaded or as plain lumps!
  • markus_zhang
    Te be frank, a lot of companies don't need engineers. They need someone to do the jobs "quickly", "ASAP" and that's it. They are hiring coders masqueraded as programmers who masqueraded as engineers.I'd say this -- if you really want to be a real engineer, you should avoid many career paths out there. Potentially ANY positions DIRECTLY facing business stakeholders is at best not a good choice, and at worst deprive your already remote chance to be a good engineer. The lower level you move into, the better, because the environment FORCES you to be a true engineer -- either you don't and fail, or you do and keep the job.
  • bgentry
    Here is something that gets lost in all the excitement about AI productivity: most software engineers became engineers because they love writing code.I think there's a big split between those who derive meaning and enjoyment from the act of writing code or the code itself vs. those who derive it from solving problems (for which the code is often a necessary byproduct). I've worked with many across both of these groups throughout my career.I am much more in the latter group, and the past 12mo are the most fun I've had writing software in over a decade. For those in the first group, it's easy to see how this can be an existential crisis.
  • ahokay
    This article is obviously written by ai and it’s just painful for me to read ChatGPT’s writing style day in and day out
  • agentultra
    It might be worth mentioning studies that show the lack of productivity gains from LLM usage. These posts take it as an unequivocal given. Management might still have the expectations that certain tasks are faster. But they aren’t always connected to reality because they’re not thinking as engineers.
  • antaviana
    This is what hapenned 10 years ago, when machine translation entered the professional translation business. Post-editing the translation was often slower than human translating sentences from scratch. Now nearly the whole industry is post-editing machine translations, and there is more and more content that is not even post-edited.
  • seethishat
    One problem I have seen IRL is AI deployment mistakes and IMO Vibe Coders need an IT/Dev Father Figure type to avoid these simple mistakes. Here is one example:A surgeon (no coding experience) used Claude to write a web app to track certain things about procedures he had done. He deployed the app on a web hosting provided (PHP LAMP stack). He wanted to share it with other doctors, but wasn't sure if it was 'secure' or not. He asked me to read the code and visit the site and provide my opinion.The code was pretty reasonable. The DB schema was good. And it worked as expected. However, he routinely zipped up the entire project and placed the zip files in the web root and he had no index file. So anyone who navigated to the website saw the backups named Jan-2026.backup, etc. and could download them.The backups contained the entire DB, all the project secrets, DB connection strings, API credentials, AWS keys, etc.He had no idea what an 'index' file was and why that was important. Last I heard he was going to ask Claude how to secure it.
  • andai
    I love learning ChatGPT's opinion on things.
  • jmbwell
    In writing code, as in writing poetry, the mechanical labor is 5% writing, 45% editing, and 50% reading. But the only thing that makes it yours is you.
  • smokel
    The author introduces the term "Supervision Paradox", but IMHO this is simply one instance of the "Automation Paradox" [1], which has been haunting me since I started working in IT.Interestingly, most jobs don't incentivize working harder or smarter, because it just leads to more work, and then burn-out.[1] https://en.wikipedia.org/wiki/Automation#Paradox_of_automati...
  • acedTrex
    Yep, my day to day is now miserable, LLMs have ruined everything that made this field fun, and greatly enhanced everything that made it suck.
  • Jasonleo
    AI may have sped up coding, but it also exposed that real engineering is about judgment, trade-offs, and responsibility—not just producing code.
  • wesm
    See also The Mythical Agent-Month https://wesmckinney.com/blog/mythical-agent-month/
  • RivieraKid
    Regarding expanding role:The scenario I'm somewhat worried about is that instead of 1 PM, 1 designer and 5 developers, there will be 1 PM, 1 designer and 1 developer. Even if tech employment stays stable or even slightly increases due to Jevons paradox, the share of software developers in tech employment will shrink.
  • zackify
    I've always been motivated by making simple solid foundations in my code the fastest way possible.So for me being able to have AI wrote certain things extremely fast with me just doing voice to text with my specific approach, is amazing.I am all in on everything AI and have a discord server just for openclaw and specialized per repo assistants. It really feels like when I'm busy I can throw it an issue tracker number for things.Then I will ssh via vs code or regular ssh which forwards my ssh key from 1password. My agents have read only repo access and I can push only when I ssh in. Super secure. Sorry for the tangent to the article but I have always loved coding now I love it even more.
  • mads_quist
    AI made programming A LOT MORE FUN for me.What I never enjoyed was looking up the cumbersome details of a framework, a programming language or an API. It's really BORING to figure out that tool X calls paging params page and pageSize while Y offset and limit. Many other examples can be added. For me, I feel at home in so many new programming languages and frameworks that I can really ship ideas. AI really helps with all the boring stuff.
  • MattyRad
    > One engineer captured this shift perfectly in a widely shared essay, describing how AI transformed the engineering role from builder to reviewer.I stopped here. Was this written by an an LLM? This sentence in particular reads exactly like the author supplied said essay as context and this sentence is the LLM's summarization of it. Nowhere is the original article linked, either, further decreasing trust. Moreover, there's an ad at the bottom for some BS "talent" platform to hire the author. This article is probably an LLM generated ad.My trust is vacated.This makes me feel that the SWE work/identity crisis is less important than the digital trust crisis.
  • whstl
    For me, one thing that completely changed almost overnight was dealing with junior developers.In the past, I would give them an assignment and they would take a few days to return with the implementation. I was able to see them struggling, they would learn, they would communicate and get frustrated by their own solution, then iterate.Today, there are two kinds: 1) the ones who take a marginally smaller amount of time because they’re busy learning, testing and self reviewing, and 2) the ones who watch Twitch or Youtube videos while Claude does the job and come to me after two hours with “done, what’s next” while someone has to comb through the mess.Leadership might see #2 and think they’re better, faster. But they are just a fucking boat anchor that drags down the whole team while providing nothing more than a shitty interface to an LLM in return.
  • anon
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  • _pdp_
    I'm not sure if it's made engineering harder, but it's certainly changing what it means to be a good engineer. It's no longer just about writing code. Now it's increasingly about having good taste, making the right decisions, and sometimes just being blessed with the Midas touch.In any case, I think we should start treating the majority of code as a commodity that will be thrown away sooner or later.I wrote something about this here: https://chatbotkit.com/reflections/most-code-deserves-to-die - it was inspired by another conversation on HN.
  • Twey
  • turlockmike
    The role of an engineer is to produce software that probably works. If you are producing more bugs it's because you're skipping provability. AI is also really good at writing tests and doing test-driven development You can get 100% branching coverage. You use a secondary LLM to review the work and make sure everything follows best practices.LLMs Can accelerate you if you use best practices and focus on provability and quality, but if you produce slop LLMs will help you produce slop faster.
  • cheschire
    AI made it so individual developers can outsource their work, not just companies. Maybe there are some lessons to be learned from companies that manage outsourced work successfully.
  • randomtoast
    > This is not a contradiction. It is the reality ...> That is not an upgrade. That is a career identity crisis.This is not X. It is Y.> The trap is ...> This gap matters ...> This is not empowerment ...> This is not a minor adjustment...Your typical AI slop rhetorical phrasing.Phrases like: "identity crisis", "burnout machine", "supervision paradox", "acceleration trap", "workload creep"These sound analytical but are lightly defined. They function as named concepts without rigorous definition or empirical grounding.There might be some good arguments in the article, but AI slop remains AI slop.
  • ralferoo
    This section very much resonated with me, even though I still haven't tried any of the AI tools:... most software engineers became engineers because they love writing code. Not managing code. Not reviewing code. Not supervising systems that produce code. Writing it. The act of thinking through a problem, designing a solution, and expressing it precisely in a language that makes a machine do exactly what you intended. That is what drew most of us to this profession. It is a creative act, a form of craftsmanship, and for many engineers, the most satisfying part of their day.Actually surprised none of the other comments have picked up on this, as I don't think it's especially about AI. But the periods of my career when I've been actually writing code and solving complicated technical problems have been the most rewarding times in my life, and I'd frequently work on stuff outside work time just because I enjoyed it so much. But the other times when I was just maintaining other people's code, or working on really simple problems with cookie-cutter solutions, I get so demotivated that it's hard to even get started each day. 100%, I do this job for the challenges, not to just spend my days babysitting a fancy code generation tool.
  • badgersnake
    Writing code was never particularly difficult in the first place.
  • retinaros
    Yes its accurate. Ai is a zero sum game for the devs and as usual we cheered for it while they were feeding it all opensource projects
  • xyzsparetimexyz
    I feel like there's a market out there for a weekly newsletter that summarises all the AI takes like this and collects the one meaningful snippet of insight (if any)
  • alephnerd
    > ...most software engineers became engineers because they love writing code. Not managing code. Not reviewing code. Not supervising systems that produce code. Writing it...A SWE who bases their entire identity and career around only writing code is not an engineer - they are a code monkey.The entire point of hiring a Software ENGINEER is to help translate business requirements into technical requirements, and then implement the technical requirements into a tangible feature or product.The only reason companies buy software is because the alternative means building in-house, and for most industries software is a cost-center not a revenue generator.I don't pay (US specific) 200K-400K TCs for code monkeys, I pay that TC for Engineers.And this does a disservice to the large portion of SWEs and former SWEs (like me) who have been in the industry because we are customer-outcome driven (how do we use code to solve a tangible customer need) and not here to write pretty code.
  • bpodgursky
    THERE IS A NEARLY INFINITE DEMAND FOR SKEPTICAL AND COMFORTING TAKES ABOUT AI CODINGTHE MARKET WILL FILL THAT VOIDIT DOES NOT MAKE IT TRUE
  • GeoAtreides
    fuck me another ai written postit's all so fucking tiresome
  • zzzeek
    I still feel like I'm writing code. I tell Claude what to write and I am very specific about it. There's still tons of problems for which Claude has no particular solution and it's on me and other humans to figure out what to do. For those cases where I tell it to just go off and write a whole script that I'm not even looking at, those are throwaway / low-value cases I dont care about where previously I'd not have even taken on that particular job.
  • nemo44x
    Developers will become admins. Responsible for supervising and owning the outcomes of increasingly agentic engineering outputs. Trust is the most important thing in business and it’s worth more than ever.
  • baxuz
    Pangram detects this as a 100% AI generated article. Downvote this hustling slop to oblivion.Also, check out the dude's linkedin: https://www.linkedin.com/in/ivanturkovic/
  • dankobgd
    it didn't do shit
  • locallost
    There's always a grain of truth in everything, but the recent article by the Redis guy (sorry for the lack of name) resonated more with me. It's correct that the load in other areas is increasing also because these tools are not there yet when it comes to for lack of a better word "good taste". I work with someone who hasn't written a line of code in a year and it shows and I'm about tired dealing with the slop. But also there's a bunch of things at work that you either did a million times already, aren't really challenging problems just annoying problems hard to solve because of all the cruft, a lot of boring manual work etc. and for this it's just an amazing help to the point I am more relaxed at work than I was previously. And when it does something that is not quite there, I can either fix it manually or tell it to fix it and it usually "gets it". Of course it it ultimately replaces me I will not be relaxed but that's a different topic.Another little thing that resonated was a tweet that said "some will use it to learn everything and some so that they don't have to learn anything ". Of course it's not really a hard truth. It's questionable how much you can learn without really getting your hands dirty. But I do think people looking at it as a tool that helps then and/or makes them better will profit more than people looking to cut corners.
  • anon
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  • tamimio
    Not really, I disagree. The article did slightly touched on the real issue on why people enjoy writing code, a “craftsmanship”, yes, coding is NOT engineering, it is writing, and the people who enjoy doing it are actually writers not engineers, and I always keep mentioning that. With AI however, those writers have to be doing the engineering work: the goals, architecture design, managing blueprints, process design and refining, among many other things, and that job is not easy hence why engineers are “supposedly” paid well, AI now took the writing role, and you have to do the engineering one.
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  • throwaway613746
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  • nimbus-hn-test
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  • anon
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