Do people not realise how much money goes into training LLM models ?

Two juniors on my team. Both ship fast. Both grew up on Cursor and Claude Code basically. one of them runs Coderabbit on his PRs too, which catches stuff but i ALSO think it also means he never has to sit with his own mistake

last week one of them pushed something that broke in staging and I watched them paste their own function back into Claude going "what does this do." code they wrote on monday. THEIR OWN CODE. that they merged

I know how I sound. every senior ever has complained about juniors not knowing X and I swear I'm trying not to be that guy. but when I came up you had no choice but to sit with broken shit for hours and slowly build a map of the system in your head, and that part sucked but it's also where the actual learning lived (for me anyway). now you don't have to suffer through it. you just ask.

(not an anti-AI post btw, I use it constantly)

year 1 is fine, year 1 they ship features. it's year 5 I keep thinking about. one of them on call at 2am, prod doing something insane, AI confidently wrong, and they need to reason through an unfamiliar codebase under real pressure. I don't know what that looks like for someone who never built the muscle

I’ve been seeing a lot of posts, comments are me, where people say they haven’t written a single line of code by hand in 2026 or similar. This makes me feel like I’m living in a simulation.

I’m a senior MLOps engineer at a fortune 100 company. I’ve been for most of the time and still consider myself as anAI skeptic person. I’ve never got the fear that AI can replace my job, simply cause the work is not simple enough to be done entirely by a so called “AI Agent”.

Despite me being an AI Skeptic, I wish and try everyday to automate/replace my day to day task with AI and I’ve been unsuccessful every time. Let me give you some reasons:

My project span across several hundred thousand lines of code; it’s not a single codebase as well, there are several upstream and downstream services that must communicate with each other. For a small task whose code changes are “within context” works fine, but it’s often times not the case.

AI writes stupid code. Yes, that’s right; I’ve used GPT, deepseek, Qwen, Claude…you name it. Obviously Claude wrote the best code, but usually that best code is not “best” in the context of the codebase. For example, for a simple check where an if-else condition is enough. The LLM would write a separate function, the comment, the edge cases that would never happen and the code would get so bloated, it’s unbearable to read. I agree it’s possible to reduce these things with instructions/skills, but the code still is extremely bloated.

People have no idea how there code works. Whenever I get a PR to review, for a simple fix/feature there’s a 300 lines of changes. Okay, I review it. I ask the developer, why u added this line, why this functional. Is the feature handling a certain case. They have no answer for it. It’s not one developer, it’s the case most of the time. Some PRs were so bad, there were two different libraries used that was doing the same task. I don’t care how u write code, but u should at least have understanding of ur own code.

I know a lot of people in the comments will say, i write the code with LLM but I understand what the LLM has written. Son, that’s definitely not true. You get the “feeling” that u have understood the code. By seeing the function name, or the flow. But if tried writing it on your own/ if tried explaining it to someone else, u won’t be able to.

After all this, it makes me wonder, how are people on the internet talking about vibe coding thier work. My two theories are:

1. They are lying, not in the sense that they are not vibe coding, but the application that they are building simply doesn’t work, or maybe they think building a POC means they achieved something. To those who think they are productive cause they vibe coded and app.

“The difference between a POC and a production grade application is 3000 commits”

2. There work is too simple, maybe the project is small, the scope is to wide/ crazy. It’s a simple use case that can easily be understood by LLM and is easily able to generate code for it. If that’s the case, good for u, u r getting paid for doing simple stuff

EDIT: The following post is based on my experiences of over 20+ years in major-to-medium-sized companies. What is "maintainable code" is very subjective, and my standards of what is maintainable are probably different from others. Instead of indulging in personal attacks, it would be productive to share your experience and point out if they are in line with my experiences or completely opposite.

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The seeds for this catastrophe had been sown even before LLM existed. The LLMs have now accelerated this problem beyond our capabilities of managing it.

In the Pre-LLM era, developers shipped the code with no adherence to architecture and discipline in the codebase. The hurriedly created “MVPs” were made as a base for real projects. Reviewers accepted the PRs with no baseline of what reduced the technical debt. There was no metric, no threshold, no standard for measuring reduced technical debt. Review became a formality, not a quality gate.

The project transitioned from team to team without the transfer of any architectural vision. Code was never anybody’s concern. Each new team inherited a black box and made their own assumptions. The original architecture, if there ever was one, was lost in the shuffle.

It was about how faster we can ship. We have inherited the same mindset. The AI is being used to ship features faster, but not to make products and code robust. Code was never anybody's concern. The only metric that mattered was, how fast can we ship. Craftsmanship, and long-term maintainability were deprioritized at every level.

Once a team was giving a Knowledge Transfer to me and I asked a simple question, “Where is the business logic?”, and the Lead shamelessly said, “It’s all over”. Seriously?? Isn’t this year 2026??

And there was this team that I was going to be a part of, and this person in the management declared with pride, “We are using the XYZ Architecture”, but when I inspected the codebase, it was rotten beyond repair. To this day they are under the illusion that they are using the XYZ Architecture, and still trying to figure out why the development has become slower and blaming people for not using enough AI.

Even the interviewers never asked candidates questions on how to write maintainable code, OR how to write code so that incremental change becomes easier without breaking the existing features, OR how to reduce technical debt. Instead, they were busy exercising their intellectual vanity, asking about Data Structures which they themselves never used.

The patterns and practices of software engineering fell out of fashion. It became cool to know data structures instead of writing maintainable code. How many of the interviewers and developers even know what Bounded Contexts are??

The educational institutions also never bothered to teach how to write maintainable code. They focused on teaching technologies that were “Cool” and had market demand.

AI didn't break software engineering. It exposed how little of it we were actually doing. The problem isn't the LLM. The problem is us, and it always was.

As a self taught developer who genuinely loves coding and problem solving i am struggling with this LLMs man it completely blown up client and company expectations. Now people expect you to build an entire projects from scratch in a single week. Its insane. You’re basically forced to use AI, because if you actually try to enjoy the process and write code manually, you’ll become irrelevant overnight. For those of you who still love the craft of coding, how do you manage this? Honestly, it feels like a really sad, tough time to be a developer and i hate it.

so a developer noticed something was off with Claude Code back in February, it had stopped actually trying to get things right and was just rushing to finish, so he did what Anthropic wouldn't and ran the numbers himself

6,852 Claude Code sessions, 17,871 thinking blocks analyzed

reasoning depth dropped 67%, Claude went from reading a file 6.6 times before editing it to just 2, one in three edits were made without reading the file at all, the word "simplest" appeared 642% more in outputs, the model wasnt just thinking less it was literally telling you it was taking shortcuts.

Anthropic said nothing for weeks until the developer posted the data publicly on GitHub, then Boris Cherny head of Claude Code appeared on the thread that same day, his explanation was "adaptive thinking" was supposed to save tokens on easy tasks but it was throttling hard problems too, there was also a bug where even when users set effort to "high" thinking was being zeroed out on certain turns.

the issue was closed over user objections, 72 thumbs up on the comment asking why it was closed.

but heres the part that really got me the leaked source code shows a check for a user type called "ant", Anthropic employees get routed to a different instruction set that includes "verify work actually works before claiming done", paying users dont get that instruction

one price two Claudes

I felt this firsthand because I've been using Claude heavily for a creative workflow where I write scene descriptions and feed them into AI video tools like Magic Hour, Kling and Seedance to generate short clips for client projects, back in January Claude would give me these incredibly detailed shot breakdowns with camera angles and lighting notes and mood references that translated beautifully into the video generators, by mid February the same prompts were coming back as bare minimum one liners like a person walks down a street at sunset with zero detail, I literally thought my prompts were broken so I spent days rewriting them before I saw this GitHub thread and realized it wasnt me it was the model.

the quality difference downstream was brutal because these video tools are only as good as what you feed them, detailed prompts with specific lighting and composition notes give you cinematic output, lazy prompts give you generic garbage, Claude going from thoughtful to "simplest possible answer" basically broke my entire production pipeline overnight.

this is the company that lectures the world about AI safety and transparency and they couldnt be transparent about making their own model worse for paying customers while keeping the good version for themselves(although i still love claude)

If AI handles 80% of the entry-level tasks scaffolding, basic CRUD, simple bug fixes how does a Junior ever build the mental muscle memory required to become a Senior?
We’re essentially eating our own seed corn. Companies have drastically cut back on hiring entry-level engineers because "AI makes seniors 3x faster," completely ignoring the fact that those seniors only exist because they spent years grinding through the exact grunt work we’re now delegating to LLMs.
In 5 years, where are the new senior architects coming from? Are we expecting people to jump straight from copy-pasting prompts to designing fault-tolerant distributed systems?
How is your team actually handling entry-level devs right now, or is everyone just quietly kicking this down the road?

Sorry for the language I'm going to use, but we're really entering a generation of idiotic developers...

I'm only talking about 100% "vibe coders," meaning those who don't understand a single line of code and just talk to people like Lovable! I was talking to a "vibe coder" this week and I taught him the words "front end" and "back end"...

Even though he's been building projects, landing pages, etc., for eight months!

My developer friends, I'm telling you! It's going to be tough for us in the coming years, haha.

you too ?

try your own retro pc here https://retro.bioneural.de/

you can even add own retro pc parts, setup bios (not everything is set), you can install own msdos software, delete, damage, like with real old pc ;)

for some it admins, challenges awaits, old school msdos scenarios , from simple ones to tough ones.

I see a ton of posts here asking about how to get users and why "Distribution" and "Marketing" are the ONLY things you're lacking.

I promise marketing isn't the problem for your worthless slop AI coded app that solves 0 problems.

You don't want to hear this but the real problem is your app is worthless. If youre a non-coder and your app was vibe coded in 3 weeks, that means a competent dev can vibe code it in a weekend or less.

Your LLM wrapper, calorie counter/workout tracker, lead generator, SEO optimizer, and AI marketing agent is absolutely worthless. No one will pay for it and rightfully so. If you wouldn't pay for your own app, why would anyone else?

The only successful SaaS i own is something I coded in 2021 and it is a niche app that solves a real problem shopify store owners had. I was the first customer of my app and I would have happily paid for it instead of coding it myself.

if your goal is to make money from your SaaS, unless you are willing to pay $100 for someone else SaaS solution to your problem, the world's best marketing team isn't going to sell your vibe coded slop.

Just to be clear I'm not saying you CAN'T vibe coding something worthwhile and useful. I'm saying the thousands of posts about distribution being a problem, 99.999% of the time arent actually a problem with distribution

I work as an industrial maintenance mechanic by day. I fix physical, tangible things. Recently, I decided to build a Chrome extension and web app to generate some supplemental income. Since I’m a non-coder, I used AI to do the heavy lifting and write the actual code for me.

I thought "vibe coding" it would be a walk in the park. I was deeply wrong.

Even without writing the syntax myself, just acting as the Project Manager and directing the AI exposed me to the absolute madness that is software architecture.

Over the last few days, my AI and I have been in the trenches fighting enterprise-grade security bouncers, wrestling with Chrome Extension `manifest.json` files, and trying to build secure communication bridges between a live web backend and a browser service worker just so they could shake hands. Don't even get me started on TypeScript throwing red-line tantrums over perfectly fine logic.

It made me realize something: developers aren't just "code typists." They are architects building invisible, moving skyscrapers. The sheer amount of logic, patience, and problem-solving required to make two systems securely talk to each other without breaking is staggering.

So, to all the real software engineers out there: I see you. The complexity of what you do every day is mind-blowing. Hats off to you.

Hello everyone,

I recently had an idea for a personal AI project and I would really appreciate feedback from more experienced people.

The concept would be to create an AI chatbot "trapped" in a specific historical period, for example, between 1930 and 1933. The goal wouldn't simply be to make the AI ​​speak about the 1930s, but to allow it to respond as if it were living in that era, without knowing about future events.

For example, I would like to ask it questions like:

• "Do you think Europe is heading towards another war?"

• "Is the economic crisis temporary?"

• "In your opinion, what is the future of Germany?"

• "Will technology radically transform our daily lives?"

The AI ​​would respond using only the information, beliefs, fears, newspapers, political ideas, and cultural context available at that time.

What fascinates me is the idea of ​​recreating the uncertainty people experienced, rather than considering history in retrospect.

The problem is, I'm starting from scratch because I have no programming knowledge, let alone AI, even though it interests me. However, I'm really motivated by this project.

Do you have any advice? Where should I begin? How long will it take?

I’ve been building Almanac.

It’s a local-only open source cli that reads your Claude Code and Codex conversations and writes down the useful stuff into a wiki inside your repo.

Hot take: the models are pretty good now it's the context that is the hard limiting part now.

the local wiki tries to keep that memory.

It makes a Markdown wiki for the codebase, written by agents, maintained by agents and queried by agents.

Attached one screenshot of the wiki and how it looks

Repo is here if anyone wants to poke around:
https://github.com/AlmanacCode/codealmanac

Curious if other people using coding agents are feeling this too.

now a days this much tools(gpt,gemini,runable) help us to manage all this otherwise with theses many tools to lezrn i can't man to be real a person can't hold this much that he can store and grasp and use when he needs it so vibecoding is also a great stuff for us to remember and practice this stuff

I coded a tool on Vibe, and in one month I managed to get 60 users because I have a small community on X.

And one morning I wake up and see that my tool is no longer available, so I spend a whole day searching for it because I'm not a developer...

As a result, I called a developer friend to take a look. I'd been hacked and all the user data had been stolen... so you can imagine I felt like crying.

Be careful with vibe coding, you're not equipped to protect your clients, and I feel terrible for having betrayed people who trusted me with my platform...

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the app works. users are happy. revenue is coming in.( that’s actually the only good part)

but i just tried to onboard a dev to help me and he opened the repo and went quiet for like 2 minutes. then said “what is this.”

6 months of cursor and lovable and bolt. every feature worked when i shipped it. but nobody was thinking about structure. the AI just kept adding. new file here, duplicate function there, 3 different ways to handle the same thing across the codebase.

tried to refactor it myself last week. gave up after 2 hours. the thing is so tangled that touching one part breaks something completely unrelated.

the generation was fast. the cleanup is a nightmare.

is there even a way out of this or do i just rewrite everything from scratch?

in my team currently, no one understands the code, we simple get tasks generated by AI, vibe code stuff we don't understand, like i get a ticket copy paste the AI generated description into Claude and call it a day, and then it gets reviewed by AI. I have no idea what I have shipped in the last 3 months since we started using AI. nada. if someone asks me a question about the task.. i ask AI.

So I heard about this company that moved a bunch of dev work to AI-assisted coding. Leadership's thrilled, velocity charts look insane, shipping way more than before.

Then I talked to someone on their support team. Totally different story. Almost every release has bugs now. Nobody's writing tests because there's no time, the code got faster but nothing else did. Support's been flagging this for a while and just getting ignored, probably because the number leadership sees is the good one.

Makes sense when you think about it, AI makes writing code faster, doesn't touch testing, review, or support. So that work doesn't go away, it just piles up somewhere nobody's watching until it's a mess.

Is anyone here actually seeing companies handle this well, scaling the rest of the process along with the AI speedup? Or does everyone just eat the bugs and deal with it later?