Comment by suriya-ganesh
1 day ago
>Yegge is leaning into the true definition of vibecoding with this project: “It is 100% vibecoded. I’ve never seen the code, and I never care to.”
I don't get it. Even with a very good understanding of what type of work I am doing and a prebuilt knowledge of the code, even for very well specced problem. Claude code etc. just plain fail or use sloppy code. How do these industry figures claim they see no part of a 225K+ line of code and promise that it works?
It feels like we're getting into an era where oceans of code which nobody understands is going to be produced, which we hope AGI swoops in and cleans?
This is also my experience. Everything I’ve ever tried to vibe code has ended up with off-by-one errors, logic errors, repeated instances of incorrect assumptions etc. Sometimes they appear to work at first, but, still, they have errors like this in them that are often immediately obvious on code review and would definitely show up in anything more than very light real world use.
They _can_ usually be manually tidied and fixed, with varying amounts of effort (small project = easy fixes, on a par with regular code review, large project = “this would’ve been easier to write myself...”)
I guess Gas Town’s multiple layers of supervisory entities are meant to replace this manual tidying and fixing, but, well, really?
I don’t understand how people are supposedly having so much success with things like this. Am I just holding it wrong?
If they are having real success, why are there no open source projects that are AI developed and maintained that are _not_ just systems for managing AI? (Or are there and I just haven’t seen them?...)
In my comment history can be found a comment much like yours.
Then Opus 4.5 was released. I had already had my CC cluade.md, and Windsurf global rules + workspace rules set up. Also, my main money making project is React/Vite/Refine.dev/antd/Supabase... known patterns.
My point is that given all that, I can now deploy amazing features that "just work," and have excellent ux in a single prompt. I still review all commits, but they are now 95% correct on front end, and ~75% correct on Postgres migrations.
Is it magic? Yes. What's worse is that I believe Dario. In a year or so, many people will just create their own Loom or Monday.com equivalent apps with a one page request. Will it be production ready? No. Will it have all the features that everyone wants? No. But it will do that they want, which is 5% of most SaaS feature sets. That will kill at least 10% of basic SaaS.
If Sonnet 3.5 (~Nov 2024) to Opus 4.5 (Nov 2025) progress is a thing, then we are slightly fucked.
"May you live in interesting times" - turns out to be a curse. I had no idea. I really thought it was a blessing all this time.
Yeah, it sounds like "you're holding it wrong"
Like, why are you manually tidying and fixing things? The first pass is never perfect. Maybe the functionality is there but the code is spaghetti or untestable. Have another agent review and feed that review back into the original agent that built out the code. Keep iterating like that.
My usual workflow:
Agent 1 - Build feature Agent 2 - Review these parts of the code, see if you find any code smells, bad architecture, scalability problems that will pop up, untestable code, or anything else falling outside of modern coding best practices Agent 1 - Here's the code review for your changes, please fix Agent 2 - Do another review Agent 1 - Here's the code review for your changes, please fix
Repeat until testable, maybe throw in a full codebase review instead of just the feature.
Agent 1 - Code looks good, start writing unit tests, go step by step, let's walk through everything, etc. etc. etc.
Then update your .md directive files to tell the agents how to test.
Voila, you have an llm agent loop that will write decent code and get features out the door.
I'm not trying to be rude here at all but are you manually verifying any of that? When I've had LLMs write unit tests they are quick to write pointless unit tests that seem impressive "2123/2123 tests passed!" but in reality it's testing mostly nothing of value. And that's when they aren't bypassing commit checks or just commenting out tests or saying "I fixed it all" while multiple tests are broken.
Maybe I need a stricter harness but I feel like I did try that and still didn't get good results.
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I haven’t used multi-agent set up yet but it’s intriguing.
Are you using Claude Code? How do you run the agents and make them speak?
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I worry about people who use this approach where they never look at the code. Vibe-coding IS possible but you have to spent a lot of time in plan mode and be very clear about architecture and the abstractions you want it to use.
I've written two seperate moderately-sized codebases using agentic techniques (oftentimes being very lazy and just blanket approving changes), and I don't encounter logic or off-by-one errors very often if at all. It seems quite good at the basic task of writing working code, but it sucks at architecture and you need occasional code review rounds to keep the codebase tidy and readable. My code reviews with the AI are like 50% DRY and separating concerns
In a recent Yegge interview, he mentions that he often throws away the entire codebase and starts from scratch rather than try to get LLMs to refactor their code for architecture.
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I don't get you guys that are getting such bad results.
Are you guys just trying to one shot stuff? Are you not using agents to iterate on things? Are you not putting agents against each other (have one code, one critique/test the code, and put them in a loop)?
I still look at the code that's produced, I'm not THAT far down the "vibe coding" path that I'm trusting everything being produced, but I get phenomenal results and I don't actually write any code any more.
So like, yeah, first pass the llm will create my feature and there's definitely some poorly written code or duplicate code or other code smells, but then I tell another agent to review and find all these problems. Then that review gets fed back in to the agent that created the feature. Wham, bam, clean code.
I'm not using gastown or ralph wiggum ($$$) but reading the docs, looking over how things work, I can see how it all comes together and should work. They've been built out to automatically do the review + iteration loop that I do.
My feeling has been that 'serious' software engineers aren't particularly suited to use these tools. Most don't have an interest in managing people or are attracted to the deterministic nature of computing. There's a whole psychology you have to learn when managing people, and a lot of those skills transfer to wrangling AI agents from my experience.
You can't be too prescriptive or verbose when interacting with them, you have to interact with them a bit to start understanding how they think and go from there to determine what information or context to provide. Same for understanding their programming styles, they will typically do what they're told but sometimes they go on a tangent.
You need to know how to communicate your expectations. Especially around testing and interaction with existing systems, performance standards, technology, the list goes on.
All our best performing devs/engineers are using the tools the most.
I think this is something a lot of people are telling themselves though, sure.
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I have some success but by the time I'm done I'm often not sure if I saved any time.
My (former) coworker who’s heavy into this stuff produced a lot of unmaintainable slop on his way out while singing agents praises to hire-ups. He also felt he was getting a lot of value and had no issues.
[flagged]
It lets 0.05X developers be 0.2X developers and 1X developers be 0.9-1.1X developers.
The problem is some 0.05X developers thought they were 0.5X and now they think they're 2X.
Nah, our best devs/engineers use the tools the most.
In my real life experience it's been the middling devs that always talk about "ai slop" and how the tools can't do their jobs.
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Where is the "super upvote button" when you need it?
YES! I have been playing with vibe coding tools since they came out. "Playing" because only on rare occasions have I created something that is good enough to commit/keep/use. I keep playing with them because, well I have a subscription, but also so I don't fall into the fuddy-duddy camp of "all AI is bad" and can legitimately speak on the value, or lack thereof, of these tools.
Claude Code is super cool, no doubt, and with _highly targeted_ and _well planned_ tasks it can produce valuable output. Period. But, every attempt at full-vibe-coding I've done has gotten hung up at some point and I have to step in an manually fix this. My experience is often:
1. First Prompt: Oh wow, this is amazing, this is the future
2. Second Prompt: Ok, let me just add/tweak a few things
10. 10th prompt: Ugh, everytime I fix one thing, something else breaks
I'm not sure at all what I'm doing "wrong". Flogging the agents along doesn't not work well for me or maybe I am just having trouble letting go of the control and I'm not flogging enough?
But the bottom line is I am generally shocked that something like Gas Town was able to be vibe-coded. Maybe it's a case of the LLM overstating what it's accomplished (typical) and if you look under the hood it's doing 1% of what it says it is but I really don't know. Clearly it's doing something, but then I sit over here trying to build a simple agent with some MCPs hooked up to it using a LLM agent framework and it's falling over after a few iterations.
So I’m probably in a similar spot - I mostly prompt-and-check, unless it’s a throwaway script or something, and even then I give it a quick glance.
One thing that stands out in your steps and that I’ve noticed myself- yeah, by prompt 10, it starts to suck. If it ever hits “compaction” then that’s beyond the point of return.
I still find myself slipping into this trap sometimes because I’m just in the flow of getting good results (until it nosedives), but the better strategy is to do a small unit of work per session. It keeps the context small and that keeps the model smarter.
“Ralph” is one way to do this. (decent intro here: https://www.aihero.dev/getting-started-with-ralph)
Another way is “Write out what we did to PROGRESS.md” - then start new session - then “Read @PROGRESS.md and do X”
Just playing around with ways to split up the work into smaller tasks basically, and crucially, not doing all of those small tasks in one long chat.
I will check out Ralph (thank you for that link!).
> Another way is “Write out what we did to PROGRESS.md” - then start new session - then “Read @PROGRESS.md and do X”
I agree on small context and if I hit "compacting" I've normally gone too far. I'm a huge fan of `/clear`-ing regularly or `/compact <Here is what you should remember for the next task we will work on>` and I've also tried "TODO.md"-style tracking.
I'm conflicted on TODO.md-style tracking because in practice I've had an agent work through everyone on the list, confidently telling me steps are done, only to find that's not the case when I check its work. Either a TODO.md that I created or one I had the agent create both suffer from this. Also, getting it update the TODO.md has been frustrating, even when I add it to CLAUDE.md "Make sure to mark tasks as complete in the TODO.md as you finish them" or adding the same message to the end of all my prompts, it won't always update it.
I've been interested in trying out beads to see if works better than a markdown TODO file but I haven't played with that yet.
But overall I agree with you, smaller chunks are key to success.
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I’ve definitely hit that same pattern in the early iterations, but for me it hasn’t really been a blocker. I’ve found the iteration loop itself isn’t that bad as long as you treat it like normal software work. I still test, review, and check what it actually did each time, but that’s expected anyway. What’s surprised me is how quickly things can scale once the overall architecture is thought through. I’ve built out working pieces in a couple of weeks using Claude Code, and a lot of that time was just deciding on the architecture up front and then letting it help fill in the details. It’s not hands-off, but used deliberately, it’s been quite effective https://robos.rnsu.net
I agree that it can be very useful when used like that but I'm referring to fully vibe-coding, the "I've never looked at the code"-people. CC is a great tool when you use plan carefully, review its work, etc but people are building things they say they've never read the code for and that just hasn't been my experience, it always falls over on it's own if I'm not in the code reviewing/tweaking.
> 10. 10th prompt: Ugh, everytime I fix one thing, something else breaks
Maybe that is the time to start making changes by hand. I think this dream of humans never ever writing any more code might be too far and unnecessary.
> How do these industry figures claim they see no part of a 225K+ line of code and promise that it works?
The only promise is that you will get your face ripped off.
“WARNING DANGER CAUTION - GET THE F** OUT - YOU WILL DIE […] Gas Town is an industrialized coding factory manned by superintelligent robot chimps, and when they feel like it, they can wreck your shit in an instant. They will wreck the other chimps, the workstations, the customers. They’ll rip your face off if you aren’t already an experienced chimp-wrangler.”
Yeah, I'm at that stage 6 or 7. I'm using multiple agents across multiple terminal windows. I'm not even coding any more, literally I haven't written code in like 2-4 months now beyond changing a config value or something.
But I still haven't actually used Gastown. It looks cool. I think it probably works, at least somewhat. I get it. But it's just not what I need right now. It's bleeding edge and experimental.
The main thing holding me back from even tinkering with it is the cost. Otherwise I'd probably play with it a little, but it's not something I'd expect to use and ship production code right now. And I ship a ton of production code with claude.
There is an incentive for dishonesty about what AI can and cannot do.
People from OpenAI was saying that GPT2 had achieved AGI. There is a very clear incentive for that statement to be made by people who are not using AI for anything productive.
Even as increasingly bombastic claims are made, it is obvious that the best AI cannot one-shot everything if you are an actual user. And the worst ones: was using Gemini yesterday and it wouldn't stop outputting emojis, was using Grok and it refused to give me a code snippet because it claimed its system prompt forbade this...what can you say?
I don't understand why anyone would want to work on a codebase they didn't understand either. What happens when something goes wrong?
Again though, there is massive financial incentive to make these claims, and some other people will fall along with that because it is good for their career, etc. I have seen this in my own company where senior people are shoehorning this stuff in that they clearly do not actually use or understand (to be clear, this is engineering not management...these are people who definitely should understand but do not).
Great tool, but the 100% vibecoding without looking at the code, for something that you are actually expecting others to use, is a bad idea. Feels more like performance art than actual work. I like jokes, I like coding, room for both but don't confuse the two.
> I don't understand why anyone would want to work on a codebase they didn't understand either. What happens when something goes wrong?
It's your coworker's problem. The one who actually understands the big picture and how the system fits into it. They'll deal with it.
No one is promising anything. It's just a giant experiment and the author explicitly tells you not to use it. I appreciate those that try new things, even it it's possibly akin to throwing s** at a wall and seeing what sticks.
Maybe it changes how we code or maybe it doesn't. Vibe coding has definitely helped me write throwaway tools that were useful.
After listening to Yegge's interview, I'm not sure this is accurate: https://www.youtube.com/watch?v=zuJyJP517Uw
For example, he makes a comment to the effect that anyone using an IDE to look at code in 2026 is a "bad engineer."
Hyperbole is very common.
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> It's just a giant experiment and the author explicitly tells you not to use it.
No, he threw up a hyperbolic warning and then dove deep into how this is the future of all coding in the rest of his talks/writing.
It’s as good a warning as someone saying “I’m not {X} but {something blatantly showing I am X}”
Reminds me of Matt Levine on https://www.lesswrong.com/posts/WACraar4p3o6oF2wD/sam-altman...
Who's promising it works?
It's an experiment to discover what the limits are. Maybe the experiment fails because it's scoped beyond the limits of LLMs. Maybe we learn something by how far it gets exactly. Maybe it changes as LLMs get better, or maybe it's a flawed approach to pushing the limits of these.
I'm sympathetic to this view, but I also wonder if this is the same thing that assembly language programmers said about compilers. What do you mean that you never look at the machine code? What if the compiler does something inefficient?
Not even remotely close.
Compilers are deterministic. People who write them test that they will produce correct results. You can expect the same code to compile to the same assembly.
With LLMs two people giving the exact same prompts can get wildly different results. That is not a tool you can use to blindly ship production code. Imagine if your compiler randomly threw in a syscall to delete your hard drive, or decide to pass credentials in plain text. LLMs can and will do those things.
Even ignoring determinism, with traditional source code you have a durable, human-readable blueprint of what the software is meant to do that other humans can understand and tweak. There's no analogy in the case of "don't read the code" LLM usage. No artifacts exist that humans can read or verify to understand what the software is supposed to be doing.
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Not only that but compiler optimizations are generally based on rigorous mathematical proofs, so that even without testing them you can be pretty sure it will generate equivalent assembly. From the little I know of LLM's, I'm pretty sure no one has figured out what mathematical principles LLM's are generating code from so you cant be sure its going to right aside from testing it.
I write JS, and I have never directly observed the IRs or assembly code that my code becomes. Yet I certainly assume that the compiler author has looked at the compiled output in the process of writing a compiler!
For me the difference is prognosis. Gas Town has no ratchet of quality: its fate was written on the wall since the day Steve decided he didn't want to know what the code says: it will grow to a moderate but unimpressive size before it collapses under its own weight. Even if someone tried to prop it up with stable infra, Steve would surely vibe the stable infra out of existence since he does not care about that
or he will find a way to get the AI to create harnesses so it becomes stable. The lack of imagination and willingness to experiment in the HN crowd is AMAZING me and worrying me at the same time. Never thought a group of engineers would be the most conservative and close minded people I could discuss with.
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The big difference is that compilation is deterministic: compile the same program twice and it'll generate the same output twice. It also doesn't involve any "creativity": a compiler is mostly translating a high-level concept into its predefined lower-level components. I don't know exactly what my code compiles to, but I can be pretty certain what the general idea of the assembly is going to be.
With LLMs all bets are off. Is your code going to import leftpad, call leftpad-as-a-service, write its own leftpad implementation, decide that padding isn't needed after all, use a close-enough rightpad instead? Who knows! It's just rolling dice, so have fun finding out!
> The big difference is that compilation is deterministic: compile the same program twice and it'll generate the same output twice.
That's barely true now. Nix comes close, but builds are only bit-for-bit identical if you set a bunch of extra flags that aren't set by default. The most obvious instability is CPU dispatch order (aka modern single computer systems are themselves distributed, racy systems) changes the generated code ever so slightly.
We don't actually care, because if one compiled version of the code uses r8 for a variable but a different compilation uses r9 for that variable, it doesn't matter because we just assume the resulting binary works the same either way. R8 vs r9 are implementation details that don't matter to humans. See where I'm going with this? If the LLM non-deterministically calls the variable fileName one day, and file_name the next time it's given the same prompt, yeah language syntax purists are going to suffer an aneurysm because one of those is clearly "wrong" for the language in use, but it's really more of an implementation detail at this point. Obviously you can't mix them, the generated code has to be consistent in which one it's using, but if compilers get to chose r8 one day and r9 the next, and we're fine with it, why is having the exact variable name that important, as long as it's being used correctly?
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The compiler is deterministic and the translation does not lose semantics. The meaning of your code is an exact reflection of what is produced.
We can tell you weren't around for the advent of compilers. To be fair, neither was I since the UNIX c compiler came out in '68 and was by far not the first compiler. Modern comilers you can make that claim about, but early compilers weren't.
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No, it is not what assembly programmers said about compilers, because you can still look at the compiled assembly, and if the compiler makes a mistake, you can observe it and work around it with inline assembly or, if the source is available, improve the compiler. That is not the same as saying "never look at the code".
I feel like this argument would make a lot more sense if LLMs had anywhere near the same level of determinism as a compiler.
>but I also wonder if this is the same thing that assembly language programmers said about compilers
But as a programmer writing C code, you're still building out the software by hand. You're having to read and write a slightly higher level encoding of the software.
With vibe coding, you don't even deal with encodings. You just prompt and move on.
I've wondered if people who write detailed specs, are overly detailed, are in a regulated industry, or even work with offshore teams have success more quickly simply they start with that behavior. Maybe they have a tendency to dwell before moving on which may be slightly more iterative than someone who vibecodes straight through.
I wonder if assembly programmers felt this way about the reliability of the electical components which their code relies upon...
I wonder if electrical engineers felt this way about the reliability of the silicon crystal lattice their circuits rely upon…
This analogy has always been bad any time someone has used it. Compilers directly transform via known algorithms.
Vibecoding is literally just random probabilistic mapping between unknown inputs and outputs on an unknown domain.
Feels like saying because I don't know how my engine works that my car could've just been vibe-engineered. People have put 1000s of hours into making certain tools work up to a give standard and spec reviewed by many many people.
"I don't know how something works" != "This wasn't thoughtfully designed"
Why do people compare these things.
Do you understand at a molecular level how cooking works? Or do you just do some rote actions according to instructions? How do you know if your cooking worked properly without understanding chemistry? Without looking at its components under a microscope?
Simple: you follow the directions, eat the food, and if it tastes good, it worked.
If cooks don't understand physics, chemistry, biology, etc, how do all the cooks in the world ensure they don't get people sick? They follow a set of practices and guidelines developed to ensure the food comes out okay. At scale, businesses develop even more practices (pasteurization, sanitization, refrigeration, etc) to ensure more food safety. None of the people involved understand it at a base level. There are no scientists directly involved in building the machines or day-to-day operations. Yet the entire world's food supply works just fine.
It's all just abstractions. You don't need to see the code for the code to work.
That's a terrible analogy lol.
1. Chefs do learn the chemistry, at least enough to know why their techniques work.
2. Food scientist is a real job
3. The supply chain absolutely does have scientists involved in day to day operations lol.
A better analogy is just shoving the entire contents of the fridge into a pot, plastic containers and all, and assuming it'll be fine.
> Chefs do learn the chemistry, at least enough to know why their techniques work
Cooks are idiots (most are either illegal immigrants with no formal education, or substance-abusing degenerates who failed at everything else) who repeat what they're told. They think ridiculous things, like that searing a stake "seals in the juices", or that adding oil to pasta water "prevents sticking", that alcohol completely "cooks off", that salt "makes water boil faster", etc. They are the auto mechanics of food. A few may be formally educated but the vast majority are not. They're just doing what they were shown to do.
> A better analogy is just shoving the entire contents of the fridge into a pot, plastic containers and all, and assuming it'll be fine.
That would never result in a good meal. On the other hand, vibe coding is curently churning out not just working software, but working businesses. You're sleeping on the real effect this is having. And it's getting better every 6 months.
Back to the topic: most programmers actually suck at programming. Their code is full of bugs, and occasionally the code paths run into those bugs and make them noticeable, but they are always there. AI does the same thing, just faster, and it's getting better at it. If you still write code by hand in a few years you will be considered a dinosaur.
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It's unintuitive, but having an llm verification loop like a code reviewer works impeccably well, you can even create dedicated agents to check for specific problem areas like poor error handling.
This isn't about anthropomorphism, it's context engineering. By breaking things into more agents, you get more focused context windows.
I believe gas town has some review process built in, but my comment is more to address the idea that it's all slop.
As an aside, Opus 4.5 is the first model I used that most of the time doesn't produce much slop, in case you haven't tried it. Still produces some slop, but not much human required for building things (it's mostly higher level and architectural things they need guidance on).
> it's mostly higher level and architectural things they need guidance on
Any examples you can share?
Mostly, it's not the model that is lacking but the visibility it has. Often the top level business context for a problem is out of reach, spread across slack, email, internal knowledge and meetings.
Once I digest some of this and give it to Claude, it's mostly smooth sailing but then the context window becomes the problem. Compactions during implementation remove a lot of important info. There should really be a Claude monitoring top level context and passing work to agents. I'm currently figuring out how to orchastrate that nicely with Claude Code MD files.
With respect to architecture, it generally makes sound decisions but I want to tweak it, often trading off simplicity vs. security and scale. These decisions seem very subtle and likely include some personal preferences I haven't written anywhere.
In my experience, it really depends on what you're building _and_ how you prompt the LLM.
For some things, LLMs are great. For others, they're absolute dog shit.
It's still early days. Anyone who claims to know what they're talking about either doesn't or what they're saying will be out of date in a month's time (including me).
The secret is that it doesn't work. None of these people have built real software that anyone outside their bubble uses. They are not replacing anyone, they are just off in their own corner building sand castles.
Just because they're one-off tools that only one person uses doesn't mean it's not "real software". I'm actually pretty excited about the fact that it's now feasible for me to replace all my BloatedShittyCommercialApps that I only use 5% of with vibe-coded bespoke tools that only do the important 5%, just for me to use. If that makes it a "sand castle" to you, fine, but this is real software and I'm seeing real benefit here.
> I'm actually pretty excited about the fact that it's now feasible for me to replace all my BloatedShittyCommercialApps that I only use 5% of with vibe-coded bespoke tools that only do the important 5%, just for me to use.
Aren't you worried that they'll work fine for 3 weeks then delete all your data when you hold them slightly different? Vibe coded software seems to have a similar problem to "Undefined Behaviour", in that just because it works sometimes doesn't mean that it will always work. And there's no limit on what it might do when it doesn't work (the proverbial "nasal demons") - it might well wipe your entire harddrive, not just corrupt it's own data.
You can of course mitigate this by manually reviewing the software, but then you lose at least some of the productivity benefit.
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The whole "real software" thing is a type of elitism that has existed in our field for a long time, and AI is the new battleground on which it is wielded.
> The secret is that it doesn't work.
I have 100% vibecoded software that I now use instead of commercial implementation that cost me almost 200 usd a month (tool for radiology dictation and report generation).
Wait, so you're a radiologist and you're using software you vibecoded to generate radiology reports for real patients? Is that, like, allowed?
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And yet I notice you haven't mentioned publishing it and undercutting the market. You could make a lot of money out-competing the existing option if what you produced was production-grade software. I'm guessing the actual case is that you only needed a small subset of the functionality of the paid software, and the LLM stitched together a rough unpolished proof-of-concept that handled your exact specific use case. Which is still great for you! But it's not the future of coding. The world still needs real engineers to make real software that is suitable for the needs of many, and this doesn't replace that.
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Vibe-coded radiology reports, finally the 21st century will get its own Therac-25 incident.
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My partner is a radiologist and I'd love to hear more about what you built. The engineer in me is also curious how much this cost in credits?
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How much costs you renting vibecoding tools?
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Using mystery vibe coded software in a tightly regulated, consequence-heavy environment, that’s so reassuring! /s
Is it _just_ speech-to-text, or god-forbid are you giving it scans and having it write reports for you too?
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no that's not true. I rarely now write a SINGLE line of code both at work or at home. Even simple config switches, I ask codex/gemini to do it.
You always have to review overall diff though and go back to agent with broader corrections to do.
> You always have to review overall diff though and go back to agent with broader corrections to do.
This thread is about vibe coding _without_ looking at the code.
Of course it works. I haven't looked at code for my internal development in months.
I don't know why people keep repeating this but it's wrong. It works.
It is fine to have criticisms of this, I have many, but saying that Yegge hasn't built real software is just not true.
Yegge obviously built real software in the past. He has not built real software wherein he never looked at the code, as he is now promoting.
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> saying that Yegge hasn't built real software is just not true
I mean... I feel like it's somewhat telling that his wikipedia page spends half its words on his abrasive communication style, and the only thing approximating a product mentioned is a (lost) Rails-on-Javascript port, and 25 years spent developing a MUD on the side.
Certainly one doesn't get to stay a staff-level engineer at Google without writing code - but in terms of real, shipping software, Yegge's resume is a bit light for his tenure in BigTech
OP defines herself as a mediocre engineer. She's trying to sell you Slop Town, not engineering principles.