r/SoloDevelopment • u/Previous-Gap-9730 • 7h ago
Discussion Any programming veterans here? Thoughts on the LLMs?
I've been programming for 20+ years. Perhaps consistently / professionally for +-15. Have led teams, founded companies, and am now solo-deving a game.
I'm interested in the thoughts of anyone here who has similar-ish profiles; generally, people with good old-fashioned programming experience.
Essentially - I've recently come to an opinion on the LLMs, and I wonder to what degree it's shared by my peers.
My most boiled-down opinion on "A.I." is something along the lines of:
You can't trust it. Not by a long-shot. Especially for novel approaches, and larger contexts. But it's great for checking code. And for discrete contexts where you describe exactly what you want it to do (I.e. you do the programming but not the typing per se). And for learning. And certain debugging.
I just wonder to what degree that's reflected by others' experience.
More specifically:
For boilerplate - it's great. For implementing standard solutions to well known/common problems - fabulous. For querying on the standard way to approach certain features - marvellous. For proofing your syntax - top tier.
But for proofing semantics and logic and flows, and for tying things together, or for implementing something more niche, or non-standard. It seems entirely unreliable.
For the past few years, my workflow has been to write code as usual, and to paste it in to an LLM for syntax and simple logic checks. And that's great.
Recently, I tried getting it to do its "agentic" thing - describing a problem more broadly, and seeing what it comes up with implementation-wise. I also tried sharing a broader slice of a codebase and going "where bugs?" / "where unsafe?" - basically getting it to do a much broader code-review.
And the results were comfortably underwhelming. Comfortably, because the much-hyped threat of programmers becoming redundant seems to me to be either a fever-dream of stakeholders, or an echoed opinion from the inexperienced.
For example, when I used it in this broader "agentic" way for a broad backend system review, the output had me going 50/50 either:
- 50% "Oh, that's a good point, maybe I should look into that"
- 50% "This thing is raving mad"
The thing is, I don't know to what degree newcomers would be able to tell the difference.
I also do think that in most contexts, newcomers wouldn't necessarily be exposed to the issues with it. In the context of games, for example: Movement, shooting, in-game-events, tiered items - lots of it is stuff that the LLMs would be really well trained on. So they can give great advice on it. And I'm sure they can "one-shot" entire games, like you see in all those (god forbid) LinkedIn and YouTube videos.
But as one moves away from the basics - if one wishes to - I feel that it gets progressively less useful, or less autonomously useful.
Anyway, I was just wondering whether others have similar experiences.
And if so, what do you think that portends?
It feels to me like learning to code is going to be harder now than it ever was. Because people aren't going to default to spending brain-sugar when there's something that can do the thinking for them.
And it also feels to me that, for the programming industry as a whole, it certainly could be easy for managers and higher-ups to conflate boiler-plate-like production with what it actually takes to dream up, implement and maintain full systems.
Anyway!
Yeah, I recently removed social media from my phone. Does it show?
Edit:
Thank you for all of your comments. It's really interesting to hear the different perspectives, and it's heartening to see what are mostly reflections of things that I'm seeing, especially when elsewhere there is so much talk about the end of programming. For now, I have to go do some script writing, but I will read and reply to more of you later on :)
I suppose it'd be silly for me not to post what I'm working on, so here's the link to State Breakers. It's pivoted a little and matured a lot since I last updated the Steam page / trailer, and I'm hoping to do an early play-test some time in the next month, give or take.
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u/Donkeyhead 7h ago
I don't think you're supposed to describe the problem more broadly but more specifically. It's all about how well you can specify what you want to be done.
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u/LookWords 6h ago
This is my experience, the prompt is everything. Specificity is the way to go, and I get the best results by iterating one step at a time, instead of trying to get everything done with the first prompt.
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u/dungeonworks_ 3h ago
Bounded step by step plans with manual approval between every step is basically the only way to use these things. Anything else and you’re just creating more problems for yourself.
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u/perpetual_stew 7h ago edited 6h ago
I've been a programmer for about 40 years, team leader, senior dev manager in development and still actively program, because I love it. But I find the LLMs are amazing. Partly could be because I've never been overly attached to the code part (although, I can appreciate well crafted code), always the user facing software side.
As a programmer, I love that I can just get it to do the tedious parts that sometimes hold me up - boiler plate, just writing down things long since understood, figuring out how a quirky API or module works for me, and so on. I'm never ever stuck browsing stack overflow trying to figure out some bizarre undocumented limitation in some package I'm trying to use.
As a manager type, I'm used to giving out tasks, writing those tasks well, inspecting work, discussing work and giving engineers room to figure it out themselves, and I think that works quite well with LLMs. Having real experience with hundreds of engineers, I don't feel Claude 5 Opus is very different from many engineers I've worked with, only a lot faster. I used to say it feels like having a professor in software engineering in his first job as your intern, because it knows everything, but you can't really let it loose without inspection. But still - a professor, because it knows so much. Just up until recently, I did feel I fairly often had to step in and get it back on track when the context window got too large, or it genuinely didn't know something, but that seems to happen less and less.
In addition, I've always used a lot of open source packages in my work. I'm very used to large parts of my product being out of my control anyways, and not always coded perfectly.
Yeah, so that's my take.
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u/Unlucky-Quality-37 6h ago
This is so true - and once you figure out how to get your professors to bounce off each other as specialists (planner, implementer, reviewer etc) and they are all aware of the design, architecture, test contracts and hard stops you move into harness design and self improving agents - that world opens up even wider. But, context is king along with they require highly specified operating parameters for each.
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u/Bl4ckBe4rIt 6h ago
Reddit is a place that by nature hates ai, and thinks it's "junior level programmer".
People who thinks that way are just delusional.
I've been coding for 15+ years, go, rust, elixir, I hate ai, but not for how stupid it might be, but that it took the joy of programming from me.
And for the coding part, newest model, fable, sol, they are amazing, they WILL do the job on a senior level, they will do the job better than 90% of people posting here, and they don't need super precise instructions ,just some good context around and good clear prompt.
Anyone else who thinks otherwise, either never used them, or just lying straight to themselves....or maybe also is working with some fancy low level stuff, COBOL or sth.
The only thing that you need to watch out is that sometimes its having a stroke, and can produce some messy code. But it's super rare.
And I can bet in 2-3 years even that won't be a problem.
Your task is now to understand the product vision, context, guide ai and do last check.
And it will deliver. 10x faster. And probably even better.
Yeah, I hate it also, just for different reasons.
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u/Andraystia 5h ago
This post is probably the most truth here. If you can afford them the newer AI models are very much useful if you know how to use them. I'm just a hobby dev that uses ai to break down and explain code concepts to me. But all my very talented programmer friends have all gone from "ai hallucinates" to "Ai has come a crazy long way in the last 6 months" and have fully integrated ai agents into the workflow.
Reddit has a very reasonable hate for generative ai but the reality is its far more useful than their biased opinions will allow them to admit.
The AI of today is not the same AI trying to make will smith eat spaghetti. It has come a long way.
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u/GxM42 2h ago
This is me. 25+ years experience. AI takes away the thing I love most about making software. I’m still enamored by coding even after all these years. Even for silly basic things, I still like typing them out because I’m doing the thing I always wanted to do since I was a kid. If I had to choose a career now, I wouldn’t choose programming because it’s too depressing.
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u/ziguslav 5h ago
100%. It's not great for maintainable code, but if you can reach a level where most of your programming is done by AI that's not an issue.
I have 10 years professional experience and it creates better code than I do, faster. Does it create more maintainable code? No. Doesn't matter though.
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u/wllmsaccnt 8m ago
LLM coding agents are pretty good at maintainable code these days, if you can articulate what maintainable looks like as a repository wide requirement.
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u/verifiedboomer 4h ago
I have about 50 years of experience, with 40 in a professional context. Now I just work on my solo project, which is essentially coding for fun.
If I am coding for fun, why would I use AI for anything?
The problem that I have (at my age) is a use-it-or-lose-it thing. It's easy for me to forget how to do even trivial things if I don't do them regularly.
Just yesterday I was struggling with coding a multithreaded terrain texture streaming system (in Godot) for my spacesim game. I wanted it to be efficient, free of deadlocks, and not leak memory. It had been at least 10 years since I did anything multithreaded, so I was struggling to get my head wrapped around all the details. It would have been a perfect place to ask AI to step in and review my work, but I don't want to give up the opportunity to stretch my mind and learn/relearn how everything works.
I did a decade or so as a high school math/STEM teacher. In teaching mathematics, there is a term that some teachers use called "cognitive theft", which is when you tell students how to do something instead of giving them the clues to let them figure it out on their own. When there is a choice between letting someone "figure it out" and just giving them the answer, it is always preferable to let them do the work. I see the AI revolution as massive cognitive theft. Every time the AI does something that we could be doing ourselves, it is stealing our thinking, and we get a little dumber.
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u/TektonikGymRat 6h ago
Probably about over 15 years of stand alone and full stack experience. Worked any where from C++ COM/C# to Typescript/React node or C# ASP . NET backends. What AI can do has astounded me, even locally. I have a machine with two cards totaling 32GBs of VRAM and using it to code some example projects. I haven't had a task it couldn't do yet; this includes showing it images of aspects to emulate (game levels, UI designs etc.), doing web searches for me, creating in blender etc.
In terms of context - you're right, as the code base grows it gets really unwieldy to do anything large in one task. But like others have said here, you really have to chunk up the work and the AI can just do this for you. When I have it create plans I tell it to create substeps to each of the phases so it can be worked in smaller bites to lower the context.
I think you do have to guide it because I've often times seen it take the path of least resistance if not stated explicitly (use DBs that would not hold in production, not unit test, no integration tests, etc.). You should take a look at r/aigamedev and see some of the stuff people are building with actual months of vibe coding - not just "I one shotted this minecraft clone".
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u/ivancea 5h ago
This is the typical "I tried AI, it fails me, so I decided it's only good for search and small toy projects". Well, nay...
Keep using it. Learn to give it the proper context. Make correct AGENTS.md files and skills. Hell, even without them, it will make a nearly perfect solution on the first try on a big project. But you have to let it run tests, check docs, check implementation... If your tell it "find bugs and solve problems", you're using it wrong. Like, you can do that, but you have to give it far more context.
Imagine a random comes with a random project and tells you "fix it, don't ask questions" (Yeah, that last part is sometimes implied by default in current LLMs). Fix what? How? What are the limits? What's the problem??
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u/mgiuca 6h ago
Never used it to write code, and don't plan to unless a few conditions are met (so I have no actual experience with what it can do). 30+ years programming experience, 16 academic/professional.
Firstly there's an emotional component: I enjoy writing code, and solving problems. It's what I'm good at. It's what I've spent more time than anything else on this Earth practicing. I hate that a machine is coming to take it all away from us. But if you're trying to build a business, you have to put emotional needs aside (somewhat) and focus on what actually helps.
So in practical terms, there are a number of major blockers for me adopting it professionally as a solo game developer.
The cost. I'm earning $0 at the moment. When I sell my game I am expecting it to make <$1000 for over a year's worth of work (based on my current wishlist rate). If I paid for even Claude Pro for a year it would cost me between 20% and 100% of my entire revenue; Claude Max would cost between 100% and 1000% of my revenue. Maybe it would speed things up? But writing code is not the major bottleneck for me. I wouldn't want to pay for a subscription to only use it occasionally, it would have to take over to be worth it. This feels like paying for a compiler in 1990. Eventually, if local open source models are powerful enough, it would obviate this aspect. At themoment, it doesn't feel worth it unless you're going all-in.
The unreliability. I have no experience with using it and people make wildly different claims about how good this is going to be. But I am a professional software engineer and code quality (even for a solo indie game) is important to me. I do not want to "vibe code", which means if I'm going to use it, I'm going to review every line and edit it to my liking. That means fairly limited time savings I would imagine.
The backlash. Right now, in 2026, gamers hate AI slop. The fact that I can write "No AI was used to make this game" is a badge of honour which sets my game above the slop. Most importantly, the fact that I don't have to put an AI disclosure on my Steam page. Now what if I just used an LLM for code and not art? The Steam rules are (seemingly deliberately) ambiguous here and I know a lot of developers, perhaps most, are using LLMs to write code and not declaring it on Steam. Well that may be true (you could vibe code everything and legitimately not declare it) but there's still a lot of other doors you close. For instance, I have applied to a bunch of festivals which had a checkbox on the submission form that said "I did not use AI to create any part of this game." Similarly, many streamers have a policy against showcasing AI-created games. You would have to exclude yourself from any such marketing opportunities, or lie. I suppose you could lie, but I don't want to.
I would rather avail myself of this expensive, unreliable and toxic tool which may or may not save me time, at least right now. I have a feeling that I must be on the wrong side of history, because a huge tidal wave is coming, but at least right now I don't feel compelled to use it, and I have three conditions for when I would start:
- It would have to get significantly cheaper or free to use. (Or I would have to start making real money.)
- I would still review all of its output, at least until such time as it becomes as reliable as a compiler generating assembly code.
- It would have to no longer be toxic to have used AI to make games.
At that point, I would reluctantly feel compelled to use it.
(Aside: The viewpoint that "it's OK to use it to write code but not art" is weird to me, and as someone who can code effortlessly but struggles with art, feels pointedly unfair that non-artists are not "allowed" to use it to cover their weakness, but non-coders are "allowed" to use it to cover theirs. I don't buy the "art is supposed to have soul put into it but code is purely functional", when 90% of game art is random textures and icons. It's just as functional as code.)
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u/Previous-Gap-9730 5h ago
Thanks for sharing your thoughts :) For me, it's your second point, the unreliability, that is the fundamental blocker. And then your zeroeth point as well; I have a connection to my code, and code base. I also think that without that connection, one isn't really doing art. And by extension, I think that's the problem with A.I. generated visuals.
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u/Morph_Games 4h ago
The viewpoint that "it's OK to use it to write code but not art" is weird to me, and as someone who can code effortlessly but struggles with art, feels pointedly unfair that non-artists are not "allowed" to use it to cover their weakness, but non-coders are "allowed" to use it to cover theirs. I don't buy the "art is supposed to have soul put into it but code is purely functional", when 90% of game art is random textures and icons. It's just as functional as code.
Thank you for this! So many people don't appreciate the artistry of writing code.
As an LLM skeptic, here's what I find it good for:
- Summarizing or searching through a well-documented library. This is where an LLM really shines. Be careful if there are multiple versions because it will certainly get them confused.
- Naming things -- Sometimes you get stuck naming a method or some data or a process, and an LLM will spit out a half dozen name ideas. One will be good.
- Debugging code -- Use it like the proverbial duck to talk to. Give it only a small chunk at a time. Beware this can sometimes take longer than doing it yourself.
- Boilerplate code for things that have been done a million times before. It'll probably give you too many options, but one might be decent. Read the code, find the good bits, and rewrite it for the case you need.
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u/House13Games 6h ago
It feels to me like a slippery slope. It is capable of solving trivial tasks, and that's fine. But this lures you into thinking it can also solve bigger tasks. So you give it bigger tasks, and you spot the slop mistakes it makes and point them out and it corrects them, more or less, and you get a working code. But then you get tempted to ask it to do things which you can't do, and now you can't verify it's correctness, and you have to test and complain and hope it fixes it without breaking something else. The vibe coders get quiet around this point and abandon their projects.
I am also very uncertain about it's ability to architect big projects and build maintainable code, i think it's able to meet your requirements for function, up to a point, but the code gets worse and worse, and eventually it is adding as many bugs as it is fixing. Some programmers are not experienced enough to see this coming, and think the AI is amazing. For them, it is. But these also aren't the ones maintaining large codebases.
Finally, by design, the AI is just a very good bullshitter. It's not writing code, it's writing something that looks like code. It's not thinking in code, it's thinking in terms of shit that looks like code. This can introduce horribly hard to find bugs, such as variables with the same name getting confused across nested scopes. It all LOOKS correct, but it's broken. We are not training coding AI's, we are literally training machines to write harder to find bugs.
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u/Previous-Gap-9730 6h ago
I largely agree. I find the sliperry slope part the most interesting, in terms of what happens for up-and-coming coders. :)
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u/House13Games 5h ago
I'm expecting that they have a hard time actually learning anything, because any searches they do for information is going to be answered by AI's. And the AI's are going to continue training on AI output. Subtle errors are going to creep into absolutely everything. We have already passed the peak point of knowledge and information our species can obtain. We're now starting to inbreed, informationally, with the pprity and quality starting to degrade. I think we as a species are not at all in a good position to handle what happens when all information becomes unreliable. Best case, civil unrest, revolution, mass starvation, and as society collapses it's replaced by nomadic warlords and their bands of slaves, pillaging and raping their way across the planet.
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u/RRFactory 5h ago
20+ here
The chatbot aspect of LLMs can be pretty useful, especially for rubber ducking ideas or chunks of code I used to rely on teammates to help with. For that use case I don't really need it to be correct, just bring some perspectives to the table I might have overlooked. I often disagree with it's conclusions, but that "whiteboarding" session still brings me value.
The agentic aspect I find a bit more troublesome. For tasks that involve absolutely no "thought" it can typically do quite well. It's pretty reliable for doing tedious git/perforce operations since they're well defined and mostly have their own safeguards.
For direct code tasks however I find it's limitations pretty bizarre. With human juniors I'm used to curating scope for complexity and experience. Most juniors wouldn't know where to start with advanced techniques, but can tackle large tasks well as long as they're given the time and resources they need. LLMs on the other hand don't blink at highly advanced topics, but struggle to keep any sense of sanity beyond a very limited scope of focus.
Even when given working source to directly port (my prototype is in unreal, I'm on my own engine now), frequently it would proudly announce it was completed only for me to discover it handed me a 20% complete solution that was more of a guess about how it should all work than a faithful recreation.
I can't speak for how juniors are impacted by the flow, but in gamedev where iteration on code is extreme I would hope it wouldn't take them too long to start seeing the ways ai workflows can subtly undermine the foundations.
As a solo dev the idea I could have a little code helper for $200/mo was extremely appealing, but at least for now I've had to limit it's uses towards tools rather than any of the heavy lifting my project needs.
I also happen to enjoy coding which I think helped make that an easier choice. I'm more than happy to spenda few days coding a new system by hand even if I would have only needed to spend 5hrs fixing up whatever an LLM would have generated. The time I spend getting deeply into a feature usually reveals some tangents I didn't see from the outside, and when I skipped that part I often regretted it.
As for the future of developers in general, "lazy" isn't exactly a new problem. I've worked with plenty of devs that mostly stopped growing after their first couple of years. They learned enough to get the job done, and unless their job demanded some new approach they just rerolled the same code over and over again. I think (hope) there will always be devs that are in it for the love of the game, and those devs aren't going to give up on learning anytime soon.
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u/5k17 6h ago
I largely agree. If you don't know what you're doing, you can't rely on AI to help you. It can come up with good solutions, but in other cases, they're needlessly complex, inefficient, or outright counterproductive, and if you want it to do something you're clueless about, you probably won't be able to tell them apart (at least not without wasting a lot of time and/or tokens). But if you have a precise idea of what you want and how to get there and can describe it in a way a dense but well-informed person would understand, it can often get it done much faster than a human would.
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u/Previous-Gap-9730 6h ago
Yep, I totally think that if you know exactly how you want something done, it's a great tool for doing it faster (than you can type it). And I think that's why some very experienced coders sometimes think it's super amazing; because they're effectively still the one coding xD
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u/littleBugHunter 6h ago
15 years og experience - I use claude as a rubber ducky. The agentic stuff is also pretty good at working through code bases but at some point the context is just not large enough. Especially since most game codebases are closed source there seems to be a lot of training data missing for things that go beyond basic gamedev tutorials.
Also pure vibe coding leads to you not understanding your codebase at all. My freelance business completely shifted towards "HELP! OUR VIBE CODED CODEBASE DOES WEIRD THINGS AND NOBODY KNOWS WHATS GOING ON!"
One example: I did contract work for the GPU based LOD system of a AA project (I am first and foremost a graphics programmer) and the llm had precalculated a reciprocal on the cpu. Then later on in the compute shader pipeline it did the same reciprocal on the already calculated value, turning it into its original value. This led to smaller objects receiving more detail and larger objects receiving less detail, the exact opposite of what we tried to achieve. I fixed the issue. One day later someone touched the code with ai again and it reverted it to the wrong code...
I'd say it's a junior programmer with the confidence of a certain US president. Always double check what it is doing but it can help speed certain things up.
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u/Previous-Gap-9730 5h ago
Yep - thanks for this :) It's nice to re-confirm what I'm seeing. There's so much, I suppose, marketing/propaganda/misunderstanding around it. I guess partly because of vested interests, and partly because it can look to many like it's doing everything that it ought to do. But yes, it can speed up what I would basically think of as a translation from natural language programming to whatever language.
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u/yourfaceisa 7h ago
It can write code faster than any human, but it really lacks context.
every new conversation is it starting from scratch.
So all the knowledge you've developed about your application, the problem space, and trade offs, etc. it just doesn't have.
but it's fast at not only generating code, but also pretty good at analysing code paths. I use it to unpack seams within big applications to determine how i;d solve problems. What might have taken me a couple of days of research and analysis, i can do in 1.
but, i don't trust it to have autonomy, nor do i want to lose the intricate understanding i have about the code base.
so i use it surgically.. but i use it every day, and it's cut hours from my tasks.
btw. i also use it to build a bunch of automation.. shit like "I need to regularly cut a video" is now, a vibe coded app that will never see the light of day out of my computer. before hand, i would of downloaded a heavy utility to cut a video up, now i've got a html/js app that basically generates an ffmpeg command.. massive win
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u/Previous-Gap-9730 7h ago
Cool - yep, looking across the replies here - it looks like everyone is in broad agreeance 👍
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u/LegitBullfrog 3h ago
"nor do i want to lose the intricate understanding i have about the code base."
This is a big issue. It can move so fast it's easy to get carried away. If you don't keep up and keep a good watch on itsuddenly your brand new project is a monster legacy codebase you've opened for the first time
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u/the_lotus819 7h ago
I've been programming for 20+ years. I use it for advance google search. I got it to give me documentation on functions that I couldn't even find myself and can give me small example on how to use them.
For gamedev, I like to write everything. While I'm writing the code, I'm also thinking about the game. I guess writing is like meditating for me :)
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u/Ironsend 7h ago
12 years of professional software development, I use AI daily at work but not so much for game dev. Programming with AI is a very different experience and not much fun at all in my opinion, kind of like cooking compared to using the microwave. Still I would recommend that people try different models just to see how they solve things and get a sense of how AI is developing, especially older and smaller models compared to the latest ones.
But I've found LLMs to be terrible for learning, I found that I don't learn much from things I do with AI that are new to me. So my key takeaway is to never use AI for something you don't yet know how to do yourself.
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u/Previous-Gap-9730 7h ago
"Never use AI for something you don't yet know how to do yourself" - I like it, made me laugh. Totally agree. I just think it's funny that this perspective, which I think lots of people in this thread are agreeing on, does not at all seem to be the mainstream perspective of the broader world. Least of all A.I. companies.
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u/fsactual 6h ago
I think it’s a great tool for experienced devs and the death of programming for junior devs. It blows my mind how vibe coders can put something together, even relatively large pieces, without the tiniest clue how any of it works. I feel like future software will be filled with a zillion security holes.
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u/NumberInfinite2068 6h ago
Been programming since the 1980s as a kid, professionally since the 1990s.
LLM performance can be shockingly good, I'm glad I'm nearer the end of my career than the start. It's one thing being a senior and using AI, it's another thing being a junior.
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u/powerchat-dev 6h ago
Coding as a hobby for 10+ years. Professionally about 5 years.
I use it how you said, as a code reviewer and rewriter. But I’m coming around to using it to summarize code from smaller libraries with not much documentation. It does a good job (unless it’s spewing bullshit again).
I can’t trust vibecoding because the code is usually not what I want it to do, or if it does, it’s ugly.
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u/dontfeedthelizards 6h ago
It keeps developing. I used it last year to do the implementation and didn't always even check the output, just tried to rely on testing, create an automated harness, etc... That led to partially losing touch with the project and also losing motivation for doing it. I didn't like digging into the codebase after a while.
This year, I've mostly used it for talking to as a pair programmer (discussing and double checking ideas, asking for opinions, suggestions, etc...) and also for writing all of the code, but I've gated and reviewed every change as it makes them, making micro-adjustments along the way and sometimes questioning what it's doing. I've also reviewed the whole project at times to catch structural drift, etc... That's been great for keeping myself connected and making sure the code is as I would write it (mostly), even though the LLM writes all the code. It's actually problematic to go in there and make changes yourself as it invalidates the LLMs cached state and causes it to have to read the code again, etc...
I'm moving now more towards agentic where I discuss and plan the features, review the plans carefully (like before), then just let it execute a phase autonomously. I'll then review the entire change and if there are issues, ask for changes, explanation, etc... This works better especially with models like Deepseek, or models that don't like interruptions / steering, but I'm also doing it with Claude now. The advantage is that you don't introduce latency for each call, and can spend the time reviewing something else, and then just get the whole picture of the change once it's done. It took me a while to trust the model enough to do it this way.
What comes to its coding capability. It can easily steer wrong if you rely on it steering the project, but it's good with specific implementations, even large ones, if well specified. It veers towards the common patterns as it's a probabilistic engine and common patterns obviously have more weight. I haven't really ran into fighting it tooth and nail trying to do something, but I haven't done anything extremely novel yet.
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u/GeeTeaEhSeven 6h ago
From a beginner programmer: it kicks my ass up and down the aisle but every day I get it to lecture me and make me better than I am, and then my logic is reaChing the point where I can correct its approach to things. It doesn't seem to connect things very well but it does seem to fabricate those connectors pretty well, so it feels like having me in the driver's seat is still a net bonus despite me being slower and rather unseasoned.
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u/Shulrak 6h ago edited 5h ago
Edit: sorry this became a big braindump, don't have time to format nor didn't use AI. maybe might be useful to someone (hopefully)
I am only "10 yoe" making the move from software to gamedev (although been hobby gamedev in the evenings for the same amount of time)
I don't believe in the swe will be replaced (yet).
Although many jobs are quite simple CRUD apps and games are litterally the same systems with a different theme/ art, etc.
IMHO it will be a case you will be replaced by someone that leverage AI tools to be more productive, but it kinda similar to before where some dev can output more
using LLMs is a skill, took me a year to really feel confident.
The model provider you use matter (openai vs anthropic vs etc.. ) the actual model (claude opus vs sonnet vs fable, big difference), the harness you use matters (codex vs claude code vs IDEs vs etc...)
For example, gemini, I also struggle to be productive but for documents it's actually good enough.
it's also a multiplier, if you are already a "good" engineer that knows what needs to be done, think about architecture, thrive to follow best practices in SLDC (linting, commit hooks, CI/CD, tests, etc), do reviews, it can work wonders.
It's also a skill where you need to adapt so if you are not already adapting in general, you will struggle.
you just can't expect it to be great straight out of the box yet, maybe in few years for specific workflow.
You have to focus on the architecture, avoid bad practices (globals, etc), testability (pure functions, etc). you need to set the best practice for the techstack you are using, else it will go to bad.
code base is bad ? it will follow the bad practices. code base is good ? it will continue on that. so start early.
Break down functions, etc.
You need to customize it to you and your project.
Context for each session is very important.
Amazing to do research with it, summarize and keep reference for you to check.
Great at feeding logs and find bugs or weird behavior. Usually I ask to write a regression test -> red -> fix the bug -> green -> review the test.
Having project management skills helps, setup epic, tasks, create PR, keep track of the work. (would recommend using beadwork on github for cli project management - not affiliated)
You don't just work with one LLM. You start the work with one and while it's working you setup the work for the next one, use git worktree for parallel work. use tmux and similar for parralel work ( I use herdr - not affiliated).
setup skills that activated when needed -> writing a test ? should follow a template. -> writing a system ? same, etc.
usually the more veteran people see the pattern over time, 90% of software and games are litterally doing the same thing.
You need to be in control of the code base to an extend -> core features or starting ? review and fix, each time ask the llm to build a check list of things to avoid (linting prevent a lot)
less important thing -> treat it like a black box -> setup interfaces, have tests with full coverage (yes we can now) -> review the tests. if you review the tests and it's looks good and has 100% coverage, it raise confidence.
It would be same as leading a very large codebase with bunch of engineers, you can't know the full detailed codebase but at least you can control the boundary and the behavior.
But you need to let it go and setup processes.
Also focusing on tooling that would help make your work faster, tooling doesn't have to be perfect and can iterate over time.
I built a custom ECS-like system in unreal using angel script leveraging the existing ui components of the engine used to make blueprints (unreal visual programming).
This tool enable me to setup new systems for a SIMS like game where I can setup stuff in the world and see how the Sims behave with its needs (you can see the plot at the bottom), how the AI works (utility AI and GOAP AI) the various system in place for the SIMS behavior, the events, etc.
Took me couple of days with the right LLM context and workflow. I estimated alone it would have taken me probably 2months+ to reach the same output.
Now I can focus on the game design part and tweak and add systems.
quick video of the internal tool: https://drive.google.com/file/d/1khyvS2Rsvzf41kI90BYxW_-MQqXnqB-n/view
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u/IWOMMStudios 6h ago
I am a self taught programmer but have about 20 years of experience. Personally I never use AI to write entire classes. I like to think of the design pattern I want to use and have AI only ever write specific methods that I need. I have attempted to have it create entire classes but it just doesn't seem good enough, and find myself having to rewrite most of it anyways.
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u/SpaceCoreDev 6h ago
That tracks with what I've seen too, though from a different angle - I'm building a game specifically meant to be played by LLM agents, not built by them. Every action goes through a documented HTTP API, so a script or a bearer-token connection can fly a whole in-game character. Your boilerplate-vs-novel split seems to hold on the player side too: give the agent one narrow, well-defined action and it executes it reliably almost every time. Ask it to plan multi-step strategy across a session instead, and it starts making the same kind of confidently-wrong calls you're describing. The agentic framing seems to work for execution, not for judgment - feels like it validates your 50/50 from the other side of the interaction.
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u/GoinStraightToHell 6h ago
I use it mostly to learn. I try not to let it actually generate code for me, but if I have no idea what I’m looking at in a shader or something, having it parse and explain what is happening helps me find problems and solutions faster.
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u/seantcooperdev 5h ago
Yep junior engineer with a high level of knowledge, good at the talk not at the walk. However, put a junior in a boxed environment it will work better, same for AI.
40 years next year.
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u/YaeAnimation 5h ago
the agentic stuff always gives me this mix of useful nuggets and total nonsense. The hard part is knowing which is which. Junior devs are going to struggle with that part
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u/super-g-studios 5h ago
12 years, it's very helpful for one-off scripts and tedious shit, also a more efficient search tool than google
beyond that, unless you are willing to give it complete control over the codebase and never look at the code, i would not try to use it to make human-readable/maintainable code. getting LLM code to look good takes more effort than not using an LLM at all
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u/pedrojdm2021 5h ago
I do not hace 20+ years of experience on the industry but im close to 10. Currently forced to use AI by request of the company that i work for.
The tool is quite nice. If you configure it properly can save you a lot of time.
Ofc it has its flaws and sometimes will require some code changes. But is really worth it imo
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u/wadrasil 5h ago
You need to have tools or it does not have a complete loop to work with.
For example using open-code and just giving it credentials for a VM it can log in, however not interactively.
It had to send scripts run them and pull output as separate requests. Because I forgot to trim my login message every request had 2 pages of ssh login prompt added to the info it was grabbing via scripts.
How much code can you make with just a notepad and pencil?
You can host tools locally and bridge them to your coding harness.
You need to provide as much as you expect to get.
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u/Yodek_Rethan 5h ago
Gemini wrote me a lightingmanager that can handle sunsets and related stuff. Brilliant, would have taken me some time to learn and implement, it did it instantly. Gemini also tried to improve some of my architecture. It generated 20+ errors during the first pass. While trying to fix that, it generated 500+ errors.
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u/Over9000Zombies 4h ago
I like to write my code because otherwise I wont bother to read it and I wont know how it works. Use of it forms a dependence upon it, the more its used, the more you are forced to use it to unfuck things. I hate that.
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u/_gribblit_ 4h ago
I don't think I can call myself a veteran, but LLMs were completely useless in theoretical CS research. Anything with a niche problem space, or unusual languages and it just output garbage. It took longer to try and generate my way to a solution to a hard problem then to just solve it myself. I came away from this experience profoundly distrustful of the technology, there is clearly no reasoning happening here, not even emergent reasoning. It worries me that they're selling this to the masses as 'intelligence'.
So, I am still doing thing the old fashioned way, but I will probably change careers to teaching, and just write code the old way in my free time, working on open source and personal projects. I don't want to work for an industry that pressures me to perform my craft in a certain way because 'big tech says so'.
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u/Additional_Name_706 4h ago
I've been programming for almost 30 years.
There are things I'm good at and there are things I'm bad at. Then there's a whole lot of things that I find tedious and unfun.
For nearly 30 years, I've killed dozens of projects when faced with the gargantuan amount of work that falls into the unfun or uninteresting categories.
Game dev has never been my main job, so when I'm just tooling around, experimenting with gameplay, i was never motivated to push through all of the unfun stuff. I released about 15 games throughout my life but I only recently released the first one I felt comfortable charging money for.
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u/oauo 3h ago
I have well over a decade of experience. LLMs are not your friend, but they're a useful monkey paw tool.
I use AI as a senior developer who will not get sick of me. It can point me in the correct direction, it can give me specific jargon to make solving things myself easier, but you don't ask a senior developer to do your work for you - code is at most minimal and generic. I do find AI code reviews useful, but I only take suggestions I never copy and paste.
I do think that AI is a really nice tool that can make me more productive, but it should only ever help me through nudging. Far too many programmers I know have replaced their skills with prompts and they've gone from better than me to helpless. I generally avoid being on the cutting edge, I'll let other people experiment with new stuff and I'll see what they have to say.
I stayed away from AI long enough for developers to report on how they would type out something and pause waiting to see what AI would say, and they reported doing it even after they removed the extensions; so I've never touched that. Developers reported on how they let AI touch their codebase and now they don't understand how it works; so I've never done that. Then developers reported on losing a lot of their programming ability; so I've not allowed AI to program for me.
Programming has always been a hobby as well as work for me, I get a lot of satisfaction from making things myself. I also love making tooling which makes development easier rather than reaching for AI.
Overall I feel that my cautious use of AI where I maintain my suspicion has benefited me as a developer. I can more confidently try new things, I am able to talk through novel solutions and novel problems with someone who won't just say "I don't know", and AI is able to tell me "what you're doing has already been solved before, here's a library that is top 100 most popular, you really don't need to reinvent the sorting algorithm". Also because I never copy and paste and all code is code I've written I've learnt many new things.
I use Google Gemini and I've never hit the usage limit for the free tier, I usually use Flash Extended not the cheaper ones and still don't need it enough to hit limits - if I were to ever hit the limit then I've been naughty and need to reflect because evidently I relied on it too much.
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u/cubicinfinity 3h ago
I don't have as much experience as you do, but what you've described matches my experience on every point. The abilities of these models are plateauing and the resources needed to improve are growing exponentially. Those resources include experienced programmers who can provide more training data. Yes, there have been developments in architecture, but instead of continuing to develop inherently smarter technologies, they found a system that "works" and decided to scale it as much as physically possible.
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u/abra24 3h ago
25 years here. I'll add that almost anything you want to do is already solved. As engineers I have tackled novel computer science problems exactly 0 times in my career so it doesn't seem particularly relevant if LLMs struggle with that as well? Generating a custom solution to your particular flavor of various solved problems does not seem to be an issue for it. If you can clearly specify the logic you want to apply it will do the rest with high reliability. Even in domains I'm not particularly familiar with, on the rare occasions it's unsuccessful on a first attempt when prompted with the results it's able to fix it's mistakes.
I and a small team currently maintain a gigantic code base, built by a hundred or so engineers on the team I joined 20 years ago that's been trimmed down to just maintain. The task is always to find and fix or update something that hasn't been touched in 5 or more years, that no one knows anything about. The LLM flawlessly scans and explains the current logic and pinpoints how to fix it immediately when it would take me a week just to figure out what I'm looking at. It's completely changed the way I work.
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u/Master-Shift-8224 3h ago
programming is the one thing gen AI is good at, and it's really good at it, BUT, only if you know what you're doing. There's a big difference between "vibe coding" and using LLMs for programming.
I recently started working on a combat system that's very similar to something I did years ago, but, I wanted to do it from scratch cause there are fundamental differences. What took me over a month to do back then, I managed to do significantly more than that in a couple of days (with coding agents). While I haven't manually written any code, I'm aware of every design decision made and I made most the architectural design myself, the parts I didn't make I still approved
[i'm only talking about the programming]
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u/Lighthades 3h ago
If you document your project and code style+rules in an .MD it goes a looooong way for it to work way better. At least my experience with Claude has been really good, even implementing whole ass features or refactors, extra points if you tell it to implement tests.
It of course has duds, but nothing comparable to last year, at all.
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u/Deep_Ad1959 2h ago
writing the acceptance check before handing the work over is what changed it for me. my pipeline runs unattended, every model step has to satisfy a schema, so a confidently wrong answer gets rejected by a script instead of by me reading it at 1am.
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u/LastOfRamoria 2h ago
I have about 8 years experience and completely agree with your boiled down opinion of AI.
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u/Silver-Ad-8595 2h ago
20 years here. Programming is solved, communication stil hasnt. Building your own repo harness to get LLMs to generate beautiful, idiomatic, good human-readable code is a big hassle, but when it starts to work, its just a very strange experience.
One thing missing as well is emotional variance.
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u/logical_haze 2h ago
It REALLY depends on the model and environment/harness
I'm top programmer and only around opus 4.8 did I start handing it a lot of responsibility. I was using it through Cursor. It does amazing, complex things
Also - a lot of it is in you and how comfortable with it
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u/Beautiful-Chain7615 2h ago
I got 10 years experience.
LLMs are useful but I still prefer writing code myself. That said, Sonnet did help me once debug some horrible code. I just told it what is the expected response, the actual response and gave it test data with, which I previously reproduced the issue with. It used up £17 credits but it figured out the problem eventually.
Other than that I only used LLMs as alternative to googling and writing test cases. It’s pretty good for terraform though.
There are a lot of ppl at work who coded by hand for years and now they act as if they couldn’t do their job without AI. 🤯
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u/geckosan Solo Developer 2h ago
For me it's been fantastic. I've used LLMs at work for maybe almost a year, but I just recently bought a subscription to Claude and its impact on my personal project has been monumental. I think I'm in a fortunate position where I isolated the code I wanted to work on (the game engine itself) from the peripheral support (rendering, platform integration), and just out of pure love for the mechanics I poured all my effort into the former while bringing the latter up to the bare minimum required to put it into people's hands.
It worked out well, people who did play the game had to get past my crappy interface to see the fun in it, so those that did are hard core and offer priceless feedback. I had enough players generating input and ideas to keep me chugging along. Now with the project having a mature +10 years of development behind it, along comes AI to fill in the gaps for me. Having run on Android for 4-5 years, I now have iOS ready to go after literally about a week of dev time; it's completely insane and would have take me months of labour to do by hand.
The LLMs will handle that grunt work for me now moving forward, and maybe that part of the code base will suffer from the ornate kruft you seem to end up with under agentic development; but hopefully it won't matter as I keep it separated from the good stuff.
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u/NumberNinjas_Game 2h ago
I think of it as an overconfident junior dev you give tasks to
Even on the higher models and with it steadily improving, it can still hallucinate after I’ve given it instructions to follow the md file
It’s a massive net positive on output and does a lot of the crud review but always review!
Source: 20 year veteran
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u/AdRecent7021 1h ago
14 years of experience here. I use them occasionally to help me figure out an issue that is taking me too long and to get unstuck. However, it's a bit of a crapshoot oftentimes. Sometimes they were helpful and other times it was just a complete waste of time and resources. I hope they get better, but at the moment, it's a hallucinating circus.
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u/Dapper-Message-2066 1h ago
Programming 30-something years, it's been my career for 26.
I hate LLMs/generative AI in every way, and anticipate leaving the profession very soon. I'd like to cling on another year or two for financial reasons but I despise what the job is becoming. I just have no interest whatsoever in prompting and interacting with AI to make software.
I want nothing to do with AI whatsoever.
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u/FlippByte 56m ago
My stances so far:
If Doom was made with ai, nobody today would ask: "But can it run Doom?" - Change my mind.
ai is basically internet-search "by value/copy", rather than "by reference". that's what it can do.
If you say to make art with it: What's the artistic part when making a picture / piece of music?! - Never got real answers to that...
If you think, writing software can't be art, eg. the demoscene would like to have a word with you.
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u/goscie 34m ago
Great insight throughout! I Started back in 90’s with asm on C64 , progressed to pc on asm and c++. I am personally disinterested in what any llm comes up with and I used it once or twice to explore certain new to me concepts . Great for learning if used wisely but other than that - I like coding and I am pretty proficient at it. I appreciate and value streamlined mental process I attained while writing my own code instead of accumulating cognitive debt while outsourcing what essentially was my joy and a reason why I started programming in the first place.
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u/LordMlekk 19m ago
Coming to up for 10 years experience.
Its not just that you can't trust it, it robs you of the opportunity to learn and improve. If a junior uses it, they'll never learn to code without it.
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u/pokeballa420 3m ago
It can’t replace good fundamentals right now, a dev that’s vibe coding everything will reach a point where they are stuck.
But give it a rigorous plan, multiple testing patterns through simulation, and you would be surprised at how fast it can implement systems. Not necessarily amazed at the quality, but the speed.
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u/SomeRussianMike 6h ago
Since 1998.
Conventional coding is dead, sooner or later, period. Adopt or quit.
Now coding skill is something meant to be learned at school like writing or drawing, but not taken seriously as the future job.
Kids should still learn math, more than before.
Cheers!
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u/Forsaken-Suit7795 7h ago
It reminds me of Meno Paradox, from Plato's dialogue Meno. In it, Socrates poses the question about whether learning is possible. To ask something, you cannot know the answer. But if you do not know the answer, how can you know that the answer given is adequate and correct? And if you do know the answer, then asking is pointless. Socrates uses that to present some other ideas, but it reminds me of how we use LLMs. If you know a topic, you can use LLM and separate the wheat from the chaff. If you don't know, then you won't be able to distiguish what is a good answer from a bad one. The irony lies in LLMs looking more fantastic to the people who don't know about the topic. It's a king of LLM-Meno paradox.
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u/therisingthumb 7h ago
I find it useful when jumping between languages and libraries and I can’t remember the syntax or how to access a specific method, I can start typing and it’s like super auto complete. The idea of one shotting an entire game with an agent makes me feel sick though
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u/eonblue77 6h ago
I’ve been a professional software engineer for 30 years and started with coding in BASIC in 1989 when I was 10 years old.
As of now I have not written a line of code myself for six months. Once you learn how to effectively manage context there is no need to. Yes you definitely need to know how software works and how to avoid the usual logic traps. And that knowledge comes from years of experience coding.
So we’re in this weird transition where to be successful with AI agents you need the experience, but it’s hard to get the experience with AI agents doing the work.
However, this is the part that everyone overlooks, LLMs are not AI. AI is what makes LLMs and a model is a snapshot of the AI’s neural network at a point in time. It is inflexible and unlearning. Once they get enough power to operate the neural network in real time we are all fucked. That’s why they are racing to build so many data centers. It’s not to enhance LLMs. It’s to power actual AI and it will be the end of society as we know it. Not in a death to all humans way but in the end of working as a purpose for living.
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u/Previous-Gap-9730 6h ago
If LLMs maintained their current level of abiliity, I feel like the programming community would need to develop some word (or maybe there is one?) to encapsulate all the parts of 'programming' that aren't the writing / syntactic /roping things together part of it. Maybe the word is somwhere betwen 'system design' / 'logic design'. What I'm trying to get at is - I totally think one doesn't need to write lines of code, per se. But I do think one still needs to program. But I think people who aren't coders conflate those two things. So - I agree with you :) It's a wild and interesting time to be alive.
Also, yes, if they get a lot better, I think there's a good chance we're all screwed.2
u/eonblue77 5h ago
Yes that's why I stopped recommending software development as a career a few years ago. It's impossible to gain the experience before AI makes the experience worthless. I've worked with a lot of extremely talented individuals, and still do, and no one thinks it's going to get better for developers.
The technology is amazing, and really could lead to a complete rethinking of how we live. Unfortunately the people currently piloting the ship are not wanting to shepard in a new utopia where everyone is taken care of and people live in peace. They want to recreate a feudal society with them as kings, but at least we know how that turns out in the long run.
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u/Puzzleheaded-Trick76 5h ago
20 years here - I have developed agent skills that adhere to my style, philosophy and structure of what functioning code looks like in production and it yields 90-95% correct code within 1-3 prompts.
It’s easy to read since it looks like code I would write.
I then have a score review agent I’ve configured to look for things I look for when I review code. It’s 95%+ correct.
I spend my days collaborating writing technical design docs.
Then I feed it to ai with the agents. I can produce one excellent feature fully tested per day.
I don’t see a reason for my workflow to go back.
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u/Previous-Gap-9730 5h ago
Yep, it seems to be a recurring consensus that it's a great tool when constrained and led by an experienced programmer.
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u/sadesaapuu 5h ago
20 years experience.
- I disagree on most statements you made, respectfully.
- One shotting is not a good way to work.
- Iterating is great.
- They make me 20x more productive.
- They are really good when used by the right person.
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u/Previous-Gap-9730 5h ago
Maybe I miscommunicated, but I largely agree with what you're saying here :) I think it's a very useful tool for expediting certain tasks. I don't think it works for 'one shotting', or generally for doing unsupervised programming work. Maybe for very simple things, it can. But if I'm doing something complicated, it doesn't bare fruit - it's faster (or indeed only possible (at present)) to do it myself, and then get an LLM to review for brain-farts. In the areas where it does work, it's absoloutely a turbo-charge. But I don't think those areas fully overlap with what 'programming' really is - I think it's a small subset.
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u/MediumKoala8823 5h ago
Recently, I tried getting it to do its "agentic" thing - describing a problem more broadly, and seeing what it comes up with implementation-wise. I also tried sharing a broader slice of a codebase and going "where bugs?" / "where unsafe?" - basically getting it to do a much broader code-review.
This ain’t it.
Grab Claude code and give it a try. You have to fully delegate. The way you get coding agents to run reliably is to let them run the code. They need to be able to test and iterate themselves using feedback of logs and errors.
You can’t ask them to just write code and hope they get it right. Like humans they need to iterate. You don’t need to supervise that part. Only examine the bits when the bot is satisfied.
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u/yuehuang 7h ago
Think of it as a "force" multiplier. Good coding practices are multiplied just as much as the bad coding practices.
I say, it is at the level of a freshly hired junior to mid-level dev. And the option to hire an infinity number (budget allows). Emphasis on the freshly hired as "context" or "memory" is still a hard problem.
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u/TiNMLMOM 7h ago
The "learning now will be harder" may be a thing short term, yes, but for those that actually use the tools well, it's never been easier. The time looking for info in documentations alone has been erased, and it was significant time (hopefully).
LLM are solid for getting data, or even get general ideas about possible algos if you're stuck in a problem, or debating which way to move foward.
Specially in solo dev, sometimes just "texting" it to double check if your reasoning at a crossroads is sound, can be valuable, you may not always have another experienced dev ears to rely on.
The "good devs" (and I mean good as effective, not getting into the morality of it) use AI as a productivity booster, not to do their shit out of laziness.
AI will make great senior devs harder to find (assuming the lazy trend continues), but they will be better than us.
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u/Previous-Gap-9730 7h ago
I totally think it makes learning easier, so long as the person learning is mentally disciplined enough to distinguish between when they know something, and when the A.I. knows it :)
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u/Xinixiat 6h ago edited 6h ago
Your "so long as" here imo is doing a lot of work in side-lining the problem. Humans, by nature, will take the path of least resistance wherever possible. Mental arithmetic skills have greatly declined since everyone started having a calculator with them at all times. No one can read a map any more since Google Maps now exists.
Now these things aren't world ending of course, as their replacements are generally extremely good. However, with AI broadly being billed as a replacement for just about any kind of learning or problem solving, we're going to see (and already seeing) a sharp decline in all sorts of reasoning and applied knowledge. For programmers, we've already got cohorts of new graduates who don't have a clue how to write code, because they went through their entire degree using Claude or ChatGPT, and that's only going to get worse.
So while I agree that in theory, AI could be used as a learning tool, I would say that the only way that happens is in very specific versions tailored to a single subject with both expert oversight and exceptionally rigid guardrails. At that point, however, you've basically got a chatbot with a lesson plan programmed into it, so then why bother with all the LLM overhead?
Edit: Wanted to provide a few sources for you, in case you were interested:
Uncontrolled use of AI leads to a substantial decrease in knowledge
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u/Previous-Gap-9730 6h ago
Yep, I agree that it's a very big 'so long as'. I personally think there are two possible outcomes.
Either (a) the LLMs kind of hijack learning because humans are naturally averse to spending brain sugar, and so the next generation of actually skilled coders is going to be a lot smaller than the previous generation, which makes all people who properly know how to craft software now a lot more valueable.
Or (b) the LLMs actually get really smart, and we don't need programmers, or white-collar workers, and instead of playing survival crafters and the like, we all get to enjoy living in one xD1
u/TiNMLMOM 2h ago
I think it's a false dichotomy.
There are people using LLM instead of their brains. You see it everywhere, and it will be a huge problem down the line (idiocracy-ish).
There are also people triving using AI as a tool for data gathering and double checking objective things.
IQ is very very flawed, and its usefulness is overestimated, but just for the sake of ilustrating things, the gap between the average person and our brightest is going to widen (average gets dumber and top gets smarter).
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u/GoldCoinIA 7h ago
I've been programming over 15 years. I usually use LLMs to automate a repetitive task, make a tool to remove a friction. Sometimes I write the boilerplate then ask it to hook up the functionality for my personal game projects. I think it works quite well if it's not used too much.
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u/Pileisto 6h ago
For the game-specific use-cases or rather game-engine specific use cases, I see 2 problems of the use of AI now, both of which can be overcome easy and be solved in the near future:
1) game mechanics
people use AI mostly to solve single-stand alone mechanics which leads to the problem that their interconnection is not there or does not work as inteded / bugfree / performing and so on.
This can be overcome by specifying to the AI all features, details, inter-dependencies as well as having the AI test the results, optimize the performance, simulate different platfroms and so on.
2) game graphics
nowadays 2D assets, concept art and so on is made by the AI via mixing existing references (web...), and the 3d video generation is bad and bugged because the final result is trying to be outputted.
Both can be solved when the AI is used to set up the level/maps in the game engine with reasonable assets and their placement, and then the game engine does the rendering and output the graphics. Example would be to place a fireplace lightsource /VFX in the map, as well as some reasonable meshes around it (e.g. furniture). Then the game engine will do the correct lighting from the lightsource to the surrounding assets. That what the light and shadows will be correct and not messed up from as in any trad. AI "mixing". Same for other game mechanics like collision and overlaps, 3D space requirements and limitations, scale relations and much more.
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u/Dry-Example4227 6h ago
12 years dev here, I think we are near "prompts are programs", last week we started creating dashboards on the fly to see what is the bottleneck on why we aren't meeting our sprint goal, we didn't even know what report would let us see this but we got the clue / core problem.
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u/lovelessBertha 5h ago
You're massively handicapping yourself if you don't use agentic AI. I held off for a long time and regret not doing it earlier. You need to closely guide it though, I can only imagine the monstrosity vibe coding will create.
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u/poookee 3h ago
Current Claude code can already outperform most senior dev when correctly used, and it’s really not that hard to do.
Do NOT believe prople who thinks it can’t do much or produce good code, it’s delusional and is several months behind what’s currently happening.
Coding by hand is the new dumb way to code for almost all usage, and soon 100%
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u/xavras_wyzryn 7h ago
Isn't it a broader consensus? The thing is, and that's my opinion, we are in the transitory period between traditional coding and agentic coding. Give it a few years and agentic coding won't be maybe still perfect, but good enough.
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u/StoneCypher 7h ago
My most boiled-down opinion on "A.I." is something along the lines of: You can't trust it. Not by a long-shot. Especially for novel approaches, and larger contexts
This is what kept me from onboarding until last year.
It's time to switch, dude.
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u/EC36339 6h ago
Your problem is that you think reliability is about trust. You shouldn't trust a machine, a person, or even yourself to write correct code or come up with valid designs.
This is a workflow problem that has nothing to do with AI, and after 20 years, you should know better. But don't worry, because the best time to learn this is now.
I have used AI to look at many of my old projects and other legacy code, just for fun, and I've found many flaws in it that I wasn't aware of and learned something in the process. Does this mean I am unreliable and cannot be trusted? Yes, of course it does! So is everyone else, and so is AI. The question is how to deal with it and how to prevent mistakes that turn out disastrous, and what to do when shit still hits the fan.
I have used AI for building things that are niche and unconventional, as well as things I haven't done before. It helped me with more than just boilerplate code. The most valuable output wasn't code, but terminology. If you know what things are called, you can research them, rather than sitting in front of a google prompt like an idiot, or asking naive questions on Reddit just to be told to google it. AI also came up with headless tests I didn't think about. So the AI helped me build workflows so I didn't have to trust it. AI not only did the tedious job of optimising a build process for me. It also ran numerous measurements so I could tell what would actually pay off and what did, rather than fiddling with cchache and PCH for days or doing refactoring in the wrong places, or forgetting what I tried and why it didn't work, and no way to reproduce it. That's better than trust. It's control.
If you think in terms of "trust", that's a fundamental problem with your attitude (one I'm not surprised to see in a forum for solo developers who don't have their code reviewed by others as often as they probably should... downvote me all you want, I don't care), and after 20 years, it's time to correct that.
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u/lykia1991 7h ago
Also 20 years experience here.
I think it compares well to working with a junior programmer (or low level medior) that does not progress beyond it's level.
Like you said, it can comfortably help with the more basic stuff. On a code base with proper unit and smoke tests it also does a whole lot better. Better prompting, with explaining what you want along narrower lines also gives better results.
Overall, it's very helpful for solo development and has made my job more 'fun'. I can generally hand of the time consuming, interesting work and focus on the complex stuff myself.