It pushes and crosses boundaries, it is a mixture of technology and art, it is provocative. It takes stochastic neural nets and mashes them together in bizarre ways to see if anything coherent comes out the other end.
And the reaction is a bunch of Very Serious Engineers who cross their arms and harumph at it for being Unprofessional and Not Serious and Not Ready For Production.
I often feel like our industry has lost its sense of whimsy and experimentation from the early days, when people tried weird things to see what would work and what wouldn't.
Maybe it's because we also have suits telling us we have to use neural nets everywhere for everything Or Else, and there's no sense of fun in that.
Maybe it's the natural consequence of large-scale professionalization, and stock option plans and RSUs and levels and sprints and PMs, that today's gray hoodie is just the updated gray suit of the past but with no less dryness of imagination.
So, Steve has the big scary "YOU WILL DIE" statements in there, but he also has this:
> I went ahead and built what’s next. First I predicted it, back in March, in Revenge of the Junior Developer. I predicted someone would lash the Claude Code camels together into chariots, and that is exactly what I’ve done with Gas Town. I’ve tamed them to where you can use 20–30 at once, productively, on a sustained basis.
"What's next"? Not an experiment. A prediction about how we'll work. The word "productively"? "Productively" is not just "a big fun experiment." "Productively" is what you say when you've got something people should use.
Even when he's giving the warnings, he says things like "If you have any doubt whatsoever, then you can’t use it" implying that it's ready for the right sort of person to use, or "Working effectively in Gas Town involves committing to vibe coding.", implying that working effectively with it is possible.
Every day, I go on Hacker News, and see the responses to a post where someone has an inconsistent message in their blog post like this.
If you say two different and contradictory things, and do not very explicitly resolve them, and say which one is the final answer, you will get blamed for both things you said, and you will not be entitled to complain about it, because you did it to yourself.
Gastown looks like a viable avenue for some app development. One of the most interesting things I've noticed about AI development is that it forces one to articulate desired and prohibited behaviors -- a spec becomes a true driving force.
Yegge's posts are always hyperbolic and he consistently presents interesting takes on the industry so I'm willing to cut him a buttload of slack.
I think ideas from it will probably partially inspire future, simpler systems.
And FOMO stories about missing out on Bitcoin when he knew about it, so he doesn't want you to miss out on this new opportunity to get "filthy rich" as an "investor" while you still can.
Note the word "future" not "present". People are making a prediction of where things will go, not saying that this thing is ready for production-grade code today.
- "what's next" does not mean "production quality" and is in no way mutually exclusive with "experimental". It means exactly what it says, which is that what comes next in the evolution of LLM-based coding is orchestration of numerous agents. It does not somehow mean that his orchestrator writes production-grade code and I have no idea why you would think it does mean that.
- "productively" also does not mean "production quality". It means getting things done, not getting things done at production-grade quality. Someone can be a productive tinkerer or they can be a productive engineer on enterprise software. Just because they have the word "product" in them does not make them the same word.
- "working effectively" is a phrase you snatched out of the context of this extremely clear paragraph which is saying the opposite of what you're pretending it is: "Working effectively in Gas Town involves committing to vibe coding. Work becomes fluid, an uncountable substance that you sling around freely, like slopping shiny fish into wooden barrels at the docks. Most work gets done; some work gets lost."
If he wanted to say that Gas Town wrote production grade code, he would have said that somewhere in his 8000-word post. But he did not. In fact, he said the opposite, many many many many many many times.
You're taking individual words out of context, using them to build a strawman representing a promise he never came close to making, and then attacking that strawman.
What possible motivation could you have for doing this? I have no idea.
> If you say two different and contradictory things...
He did not. Nothing in the blog post explicitly says or even remotely implies that this is production quality software. In addition, the post explicitly, unambiguously, and repeatedly screams at you that this is highly experimental, unreliable, spaghetti code, meant for writing spaghetti code.
The blog post could not possibly have been more clear.
> ...because you did it to yourself.
No, you're doing this to his words.
Don't believe me? Copy-paste his post into any LLM and ask it whether the post is contradictory or whether it's ambiguous whether this is production grade software or not. Literally no objective reader of this would come to the tortured conclusions that you have.
If I can be a bit bold and observe that this tic is also a very old rhetorical trick you see in our industry. Call it Schrodinger's Modest Proposal if you will.
In it someone writes something provocative, but casts it as both a joke and deadly serious at various points. Depending on how the audience reacts they can then double down on it being all-in-good-jest or yes-absolutely-totally. People who enjoy the author will explain the nonsensical tension as "nuance".
You see it in rationalist writing all the time. It's a tiresome rhetorical "trick" that doesn't fool anyone any more.
Our industry is held back in so many ways by engineers clinging to black-and-white thinking.
Sometimes there isn’t a “final” answer, and sometimes there is no “right” answer. Sometimes two conflicting ideas can be “true” and “correct” simultaneously.
It would do us a world of good to get comfortable with that.
The final answer can be "each of these positions has merit, and I don't know which is right." It can be "I don't understand what's going on here." It can be "I've raised some questions."
The final answer is not "the final answer that ends the discussion." Rather, it is the final statement about your current position. It can be revised in the future. It does not have to be definitive.
The problem comes when the same article says two contradictory things and does not even try to reconcile them, or try to give a careful reader an accurate picture.
And I think that the sustained argument over how to read that article shows that Yegge did a bad job of writing to make a clear point, albeit a good job of creatring hype.
Ok, I can accept that, it's a choice.
> Things said there may not reflect his actual thoughts on the subject(s) at hand.
Nope, you don't get to have it both ways. LLMs are just tools, there is always a human behind them and that human is responsible for what they let the LLM do/say/post/etc.
We have seen the hell that comes from playing the "They said that but they don't mean it" or "It's just a joke" (re: Trump), I'm not a fan of whitewashing with LLMs.
This is not an anti or pro Gas Town comment, just a comment on giving people a pass because they used an LLM.
The same approach actually applies to Trump and other liars. You can't take anything they say as truth or serious intent on its own; they're not engaging in good faith. You can remove yourself one step and attempt to analyze why they say what they do, and from there get at what to take seriously and what to disregard.
In Steve's case, my interpretation is that he's extremely bullish on AI and sees his setup or something similar as the inevitable future, but he sprinkles in silly warnings to lampshade criticism. That's how the two messages of "this isn't serious" and "this is the future or software development" co-exist. The first is largely just a cover and an admission this his particular project is a mess. Note that this interpretation assumes that the contents of the blog post in question were largely written by him, even if LLM assistance was used.
I agree with you on Steve's case, and I have no ill will towards him. Mostly it was just me trying to "stomp" on giving him a pass, but, as you point out, that may not have been what the original commenter meant.
I suppose that has little to do with the technical merits of the work, but it's such a bad look, and it makes everyone boosting this stuff seem exactly as dysregulated/unwise as they've appeared to many engineers for a while.
I met Sean Goedecke for lunch a few weeks ago, who uses LLMs a bunch, and is clearly a serious adult, but half the folks being shoved in front of everyone are behaving totally manic and people are cheering them on. Absolutely blows my mind to watch.
https://pivot-to-ai.com/2026/01/22/steve-yegges-gas-town-vib...
> $GAS is not equity and does not give you any ownership interest in Gas Town or my work. This post is for informational purposes only and is not a solicitation or recommendation to buy, sell, or hold any token. Crypto markets are volatile and speculative — do not risk money you can’t afford to lose.
...
> Note: The next few sections are about online gambling in all its forms, where “investing” is the buy-and-hold long-form “acceptable” form of gambling because it’s tied to world GDP growth. Cryptocurrencies are subject to wild swings and spikes, and the currency tied to Gas Town is on a wild swing up. But it’s still gambling, and this stuff is only for people who are into that… which is not me, and should probably not be you either.
In the next post he said he wasn't going to shill it any more, and then the price collapsed and people sent him death threats on Twitter. It probably would have collapsed anyway. Perhaps there was supposedly some implicit bargain that he shouldn't take the money if he wasn't going to shill? Well, there's certainly no rule saying you have to do that.
I think he's not very much to blame for taking the money from degenerate gamblers, and the cryptocurrency idiots are mostly to blame for their own mistakes.
Personally I got about 3 paragraphs into what seemed like a twelve-page fevered dream and filed it under "not for me yet".
What I don't like is people me-tooing gastown as some breakthrough in orchestration. I also don't like how people are doing the same thing for ralph.
In truth, what I hate is people dogpiling thoughtlessly on things, and only caring about what social media has told them to care about. This tendency makes me get warm tingles at the thought of the end of the world. Agent smith was right about humanity.
But that's often enough to loop over and over again and eventually finish a task
https://pivot-to-ai.com/2026/01/22/steve-yegges-gas-town-vib...
When he decided to monetize the eyeballs on the project instead of anything related to the engineering. Which, of course, Steve isn't smart enough to understand (in his own words) and he recommends you not buy but he still makes a tidy profit from it.
Its a memecoin now... that has a software project attached to it. Anything related to engineering died the day he failed to disavow the crypto BS and instead starting shrilling it.
What happened to engineers not calling out BS as BS.
https://steve-yegge.medium.com/bags-and-the-creator-economy-...
It makes it difficult to believe that gas town is actually producing anything of value.
I also lol at his bitching about how the bank didn’t let him do the transactions instantly as he describes himself how much of a scam this seems and how the worst thing is his bank account being drained, like banks don’t have a self interest in protecting their clientele from such scams.
The first thing I thought as I read his post and saw the images of the weasels was that he should make a game of it. Maybe name it Bitborn.
[Medium post]: https://steve-yegge.medium.com/welcome-to-gas-town-4f25ee16d...
[HN Discussion]: https://news.ycombinator.com/item?id=46458936
Fear over what it means if it works.
A couple of days ago I was sitting in a meeting of 10-15 devs, discussing our AI agents. People were raising issues and brainstorming ways around the problems with AI. How to make the AI better.
Our devs were occupied doing AI things, not accounting/banking things.
If the time savings were as promised, we should have been 3 devs (with the remaining devs replaced by 7-10 AI agents) discussing accounting/banking.
If Gas Town succeeds, it will just be the next toy we play with instead of doing our jobs.
This is only partly tongue in cheek :P
Its like the ultimate RTS, plus you get paid.
Remember the days when people experimented with and talked about things that werent LLMs?
I used to go to a lot of industry events and I really enjoyed hearing about the diversity of different things people worked on both as a hobby and at work.
Now it's all LLMs all the time and it's so goddamn tedious.
I go to tech meetups regularly. The speed at which any conversation end up on the topic of AI is extremely grating to me. No more discussions about interesting problems and creative solutions that people come up with. It's all just AI, agentic, vibe code.
At what point are we going to see the loss of practical skills if people keep on relying on LLMs for all their thinking?
And then you give in and ask what they're building with AI, that activation energy finally available to build the side project they wouldn't have built otherwise.
"Oh, I'm building a custom agentic harness!"
...
I can't even say that's definitely a losing bet-- it could very well happen-- but boy does it seem risky to go all-in on it.
On the other, if a large portion of the industry goes all in, and it _doesn’t_ pay off and craters them, maybe the overhyping will move onto something else and we can go back to having an interesting, actually-nice-to-be-in-industry!
And maybe he’s even right. But the reaction is to the flavour of chip on the shoulder delivery mixed into an otherwise fun piece.
There's no art (or engineering) in this and the only provocative thing about it is that Yegge apparently decided to turn it into a crypto scam. I like the intersection of engineering and art but I prefer if it includes both actual engineering and art, 100 rabbits (100r.co) is a good example of it, not a blog post with 15 AI generated images in it that advocates some unholy combination of gambling, vibe coding and cryptocurrency crap.
Just for fun!
https://steve-yegge.medium.com/bags-and-the-creator-economy-...
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?
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?...)
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.
Maybe I need a stricter harness but I feel like I did try that and still didn't get good results.
I'll keep testing it but that just hasn't been my experience, I sincerely hope that changes because an agent that runs unit test [0] and can write them would be very powerful.
[0] This is a pain point for me. The number of times I've watching Claude run "git commit --no-verify"... I've told it in CLAUDE.md to never bypass commit checks, I've told it in the prompt, I've added it 10 more times in different places in CLAUDE.md but still, the agent will always reach for that if it can't fix something in 1-3 iterations. And yes, I've told it "If you can't get the checks to pass then ask me before bypassing the checks".
It doesn't matter how many guardrails I put up and how good they are if the agent will lazily bypass them at the drop of a hat. I'm not sure how other people are dealing with this (maybe with agents managing agents and checking their work? A la Gas Town?).
When I work on issues I create a new branch off of master, let the llm go to town on it, then I manually commit and push to remote for an MR/PR. If there are any errors on the commit hooks I just feed the errors back into the agent.
For the llm a lot of linting and build/test tools go into simple scripts that the llm can run and get shorthand info out of. Some tools, if you have the llm run them, they're going to ingest a lot from the output (like a big stacktrace or something). I want to keep context clean so I have the llm create the tool to use for build/test/linting and I tell it to create it so the outputs will keep its context clean, then I have it document it in the .md file.
When working with the LLM I have to start out pretty explicit about using the tooling. As we work through things it will start to automatically run the tooling. Sometimes it will want to do something else, I just nudge it back to use the tooling (or I'll ask it why or if there are benefits to the other way and if there are we'll rebuild the tooling to use the other way).
Finally, if the LLM is really having trouble, I kill the session and start a new one. It used to feel bad to do that. I'd feel like I'm losing a lot of info that's in context. But now, I feel like it's not so bad... but I'm not sure if that's because the llms are better or if my workflow has adapted.
Now, let me backup a little bit. I mentioned that I don't have the llm use git. That's the control I maintain. And with that my workflow is: llm builds feature->llm runs linters/tests->I e2e test whatever I'm building by deploying to a dev/staging/local env->once verified I commit. Now I will continue that context window/session until I feel like the llm starts fucking up. Then I kill the session and start a new one. I rarely compact, but it does happen and I generally don't fret about it too much.
I try to keep my units of work small and I feel like it does the best when I do. But then I often find myself surprised at how much it can do from a single prompt, so idk. I do understand some of the skepticism because a lot of this stuff sounds "hand-wavy". I'm hoping we all start to hone in on some general more concrete patterns but with it being so non-deterministic I'm not sure if we will. It feels like everyone is using it differently and people are having successes and failures across different things. People where I work LOVE MCPs but I can't stand them. When I use them it always feels like I have to remind the llm that it has an MCP, then it feels like the MCP takes too much context window and sometimes the llm still trips over how to use it.
I’m trying to redesign my setup to use hooks now instead because poor adherence to rules files across all the agentic CLIs is exhausting to workaround.
(and no, Opus 4.5 didn’t magically solve this problem to preemptively respond to that reply)
I wonder if some people are putting in too much into their markdown files of what NOT to do.
I hate people saying the llms are just better auto-correct, but in some ways they're right. I think putting in too much "don't do this" is leading the llm down the path to do "this" because you mentioned it at all. The LLM is probabilistically generating it's response based on what you've said and what's in the markdown files, the fact you put some of that stuff in there at all probably increases the probability those things will show up.
This has not happened to me since Sonnet 4.5. Opus 4.5 is especially robust when it comes to writing tests. I use it daily in multiple projects and verify the test code.
Are you using Claude Code? How do you run the agents and make them speak?
I messed around with separate "agents" in the same context window for a while. I even went as far as playing with strands agents. Having multiple agents was a crapshoot.
Sometimes they'd work great, but sometimes they start working on the same files at the same time, argue with each other, etc. I'd always get multiple agents working, at least how I assumed they should work, by telling the llm explicitly what agents to create and what work to pass off to what agents. And it did a pretty poor job of that. I tried having orchestration agents, but at a certain point the orchestration agent would just takeover and do everything. So I'm not big on having multiple agents (in theory it sounds great, especially since they are supposed to each have their own context window). When I attempted doing this kind of stuff with strands agents it honestly felt like I was trying to recreate claude, so I just stick with plain cli llm tools for now.
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
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.”
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.
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.
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.
I think this is something a lot of people are telling themselves though, sure.
What about git stats?
I can tell you the guys that are consistently pushing code AND having the biggest impact are using LLM tools.
The problem is some 0.05X developers thought they were 0.5X and now they think they're 2X.
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.
- those who have embraced AI and learned to use it well
- those who have embraced AI but treat it as a silver bullet
- those who reject AI
First group is by far the most productive and adds the most value to the team.
If anything the silver bullet people are mostly managers and C levels... some of which don't even use the tools themselves.
Of the devs that rejected it at first, the ones with the same sentiment I'm seeing online in threads like these, we forced one to give it a try. He now treats totters between using it well and treating it as a silver bullet. I still hear him incredulous about the things claude does at meetings, "I had to do <thing> and I thought I'd let claude get a crack at it... did it in one shot"
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.
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.
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.
> 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.
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.
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.
Maybe it changes how we code or maybe it doesn't. Vibe coding has definitely helped me write throwaway tools that were useful.
For example, he makes a comment to the effect that anyone using an IDE to look at code in 2026 is a "bad engineer."
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}”
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.
What I mean is an artifact that is the starting point for generating the software. Compiled binaries can be completely thrown away whenever because you know you have a blueprint (the source code) that can reliably reproduce it.
Documentation & requirements _could_ work this way if they served as input to the LLMs that would then go and create the source code from scratch. I don't think many people are using LLMs this way, but I think this is an interesting idea. Maybe soon we'll have a new generation of "LLM-facing programming languages" that are even higher level software blueprints that will be fed to LLMs to generate code.
TDD is also a potential answer here? You can imagine a world where humans just write test suites and LLMs fill out the code to get it to pass. I'm curious if people are using LLMs this way, but from what I can tell a lot of people use them for writing their tests as well.
> And it's not like you can't go read the code if you want to understand how it works
In-theory sure, but this is true of assembly in-theory as well. But the assembly of most modern software is de-facto unreadable, and LLM-generated source code will start going that way too the more people become okay with not reading it. (But again, the difference is that we're not necessarily replacing it with some higher-level blueprint that humans manage, we're just relying on the LLMs to be able to manage it completely)
> I truly do not understand why so many people are hung up on this "I need to understand every single line of code in my program" bs I keep reading here, do you also disassemble every library you use and understand it? no, you just use it because it's faster that way.
I think at the end of the day this is just an empirical question: are LLMs good enough to manage complex software "on their own", without a human necessarily being able to inspect, validate, or help debug it? If the answer is yes, maybe this is fine, but based on my experiences with LLMs so far I am not convinced that this is going to be true any time soon.
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
There's a saying that you don't want optimists building bridges.
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.
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!
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?
I certainly don’t use all compilers everywhere, but I don’t think determinism in compilation is especially rare.
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.
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).
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.
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.
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.
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).
Any examples you can share?
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.
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.
It might. It probably won't though. I don't see any code in it that deletes files. And, unlike BloatedShittyCommercialApp (and its cousin, BloatedDoEverythingOpenSourceApp), the code is going to be relatively small and if I do have doubts I can easily check to see what it's doing. I can build it quickly. I can patch it quickly. I don't have to file a bug to someone and beg him to look at it. I don't have to worry that the next release is going to break stuff I want and add stuff I don't want.
I recently moved my home theater PC from Kodi to a tiny bespoke vibed video player app, that basically just wraps libVLC with a minimal Android GUI. It's like 3000 lines of code total. I can practically keep the entire app in my head. If I need to fix something, it's 5 minutes in my dev terminal and then adb install. Ever tried to find and fix a bug in Kodi? The goddamn thing takes forever to even build, let alone debug. And that's even open source. I don't even have a remote chance of getting a bug fixed in professionally-built proprietary software.
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).
I think azan_ is demonstrating that shipping products 'suitable for the needs of many' is going to have to compete with 'slopping software for the needs of one'.
There is a small subset of the population who is now enabled to make proof-of-concepts with less effort than before. This is no way diminishes the need for delivering performant, secure, interoperable software at scale to serve humanity's needs.
I'm going on a tangent here but what's with this constant deprecation of mothers to make a point? There are many people here whose mothers can develop software.
I think the thing you're missing is that the tool doesn't need to be marketed because someone else could ask their LLM to make them a similar tool but fitting their use case.
It doesn't matter if the tool "needs" to be marketed. There is a market of paying customers. If other people are paying $200/month, both your and their lives would be improved significantly by you offering a $100/month replacement software. For all the talk about LLMs replacing the need for packaged software, people are still paying for packaged software, and while they are, you could be making large amounts of money while saving them money. If you're altruistic, you could even release it as FOSS and save a lot of people $200/mo. Unless, of course, your vibe-coded app isn't actually remotely capable of replacing the software in question.
I built a clinical pharmacist "pocket calculator" kinda app for a specific function. It was like $.60 in claude credits I think. Built with flutter + dart. It's a simple tool suite and I've only built out one of the tools so far.
Now to be fair, that $.60 session was just the coding. I did some brainstorming in chatgpt and generated good markdown files (claude.md, gemini.md, agents.md) before I started.
Is it _just_ speech-to-text, or god-forbid are you giving it scans and having it write reports for you too?
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.
Honestly I don't get the hostility. Yegge is running an experiment. I don't think it will work, but it will be interesting and informative to watch.
To be clear, I think LLMs are useful technology. But the degree of increasing insanity surrounding it is putting people off for obvious reasons.
Not really new. Back in the day companies used to outsource their stuff to the lowest bidder agencies in proverbial Elbonia, never looked at the code, and then panickedly hired another agency when the things visibly were not what was ordered. Case studies are abound on TheDailyWTF for the last two decades.
Doing the same with agents will give you the same disastrous results for comparably the same money, just faster. Oh and you can't sue them, really.
Maybe it's better, who knows.
But you don’t pay them any money and don’t enter into contractual relationship with them either. Thus you can’t sue them. Well, you can try, of course, but.
You could sue an Elbonian company, though, for contract breach. LLMs are like usual Elbonian quality with two middlemen but quicker, and you only have yourself to blame when they inevitably produce a disaster.
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
Ralph loops are also stupid because they don't make use of kv cache properly.
---
https://github.com/steveyegge/gastown/issues/503
Problem:
Every gt command runs bd version to verify the minimum beads version requirement. Under high concurrency (17+ agent sessions), this check times out and blocks gt commands from running.
Impact:
With 17+ concurrent sessions each running gt commands:
- Each gt command spawns bd version
- Each bd version spawns 5-7 git processes
- This creates 85-120+ git processes competing for resources
- The 2-second timeout in gt is exceeded
- gt commands fail with "bd version check timed out"
This is a cost/resources thing. If it's more effective and the resources are available, it's completely fine.
So true! Not to mention the garbled text and inconsistent visuals across the diagrams———an insult to the reader's intelligence. How do people tolerate this visual embodiment of slurred speech?
Which is unfortunate as it would have been really helpful to have actually legible architecture diagrams, given the prose was so difficult for me to untangle due to the manic “fun” irreverent style (and it’s fine to write with a distinctive voice to make it more interesting, but still … confusing).
Plus the dozens of new unique names and connections introduced every few paragraphs to try to keep in my head…
I first asked Gemini 3 Pro to condense it to a boring technical overview and it produced a single page outline and Mermaid diagrams that were nearly as unintelligible as the original post so even AI has issues digesting it apparently…
> A more conservative, easier to consider, debate is: how close should the code be in agentic software development tools? How easy should it be to access? How often do we expect developers to edit it by hand?
> Framing this debate as an either/or – either you look at code or don’t, either you edit code by hand or you exclusively direct agents, either you’re the anti-AI-purist or the agentic-maxxer – is unhelpful.
> The right distance isn’t about what kind of person you are or what you believe about AI capabilities in the current moment. How far away you step from the syntax shifts based on what you’re building, who you’re building with, and what happens when things go wrong.
This quote sums it all up for me. It's a crazy project that moves the conversation forward, which is the main value I see in it.
It very well could be a logjam breaker for those who are fortunate enough to get out more than they put into it... but it's very much a gamble, and the odds are against you.
It's the same chasm that all the AI vendors are exploiting: the gap between people who have some idea what is going on and the vast mass of people who don't but are addicted to excitement or fear of the future.
Yegge is being fake-playful about it but if you have read any of his other writing, this tracks. None of it is to be taken very seriously because he values provocation and mischief a little too highly, but bits of it have some ideas worth thinking about.
Basically simulate a software engineering team using GitHub but everyone is an agent. From tech lead to coders to QA testers.
I believe agentic coding could eventually be a paradigm shift, if and only if the agents become self-conscious of design decisions and their implications on the system and its surrounding systems as a whole.
If that doesn’t happen, the entire workflow devolves into specifying system states and behavior in natural language, which is something humans are exceedingly bad at.
Coincidently, that is why we have invented programming languages: to be able to express program state and behavior unambiguously.
I’m not bullish on a future where I have to write specifications on all explicit and implicit corner and edge cases just to have an agent make software design choices which don’t feel batshit insane to humans.
We already have software corporations which produce that kind of code simply because the people doing the specifying don’t know the system or the domain it operates in, and the people doing the implementing of those specifications don’t necessarily know any of that either.
As soon as the results actually matter, the maxim becomes "if it works, but it's stupid, it doesn't work".
So apparently the medical field is not above this logic.
> “It will be like kubernetes, but for agents,” I said.
> “It will have to have multiple levels of agents supervising other agents,” I said.
> “It will have a Merge Queue,” I said.
> “It will orchestrate workflows,” I said.
> “It will have plugins and quality gates,” I said.
More “agile for agents” than “Kubernetes for agents”.
Yes, but you didn't https://www.signedoriginalprints.com/cdn/shop/products/wegot...
While the agents can generate, they can't exercise that judgement, they can't see nuances and they can't really walk their actions back in a "that's not quite what I meant" sense.
Exercising judgement is where design actually happens, it is iterative, in response to something concrete. The bottleneck isn't just thinking ahead, it's the judgment call when you see the result, its the walking back, as well as thinking forward.
Anyways we'll likely always settle on simpler/boring - but the game analogies are fun in the time being. A lot of opportunity to enhance UX around design, planning, and review.
> 3 days
still seems slow! I’m saying what happens in 2028 when your entire project is 5-10 minutes of total agent runtime - time actually spent writing code and implementing your plan? Trying to parallelize 10m of work with a “town” of agents seems like unnecessary complexity.
I mean, we use coding agents all the time these days (on auto pilot) and there is absolutely nothing of this sorts. Coding with AI looks a lot like coding without AI. The same old process apply.
I mean "I feel like I'm taking crazy pills".
Hah, tell that to Docker, or React (the ecosystem, not the library), or any of the other terrible technologies that have better thought-out alternatives, but we're stuck with them being the de facto standard because they were first.
In claude I have a code-reviewer agent, and I remind cc often to run the code reviewer before closing any bead. It works surprisingly well.
I used to monitor context and start afresh when it reached ~80%, but I stopped doing that. Compacting is not as disruptive as it used to be, and with beads agents don't lose track.
I spent some time trying to measure the productivity change due to beads, analysing cc and codex logs and linking them to deltas and commits in git [1]. But I did not fully believe the result (5x increase when using beads, there has to be some hidden variable) and I moved on to other things.
Part of the complexity is that these days I often work on two or three projects at the same time, so attribution is difficult.
[1] Analysis code is at https://github.com/juanre/agent-taylor
I haven't seen anything to suggest that Yegge is proposing it as a serious tool for serious work, so why all the hate?
Debt doesnt come due immediately, its accrued and may allow for the purchase of things that were once too expensive, but eventually the bill comes due.
Ive started referring to vibe-coding as "Credit Cards" for developers. Allowing them to accrue massive amounts of technical debt that were previously out of reach. This can provide some competent developers with incredible improvments to their work. But for the people who accrue more Technical Debt than they have the ability to pay off, it can sink their project and cost our organization alot in lost investment of both time and money.
I see Gas Town and tools like as debt schemes where someone applies for more credit cards to pay the payments on prior cards they've maxed out, compounding the issue with the vague goal of "eventually it pays off." So color me skeptical.
Not sure if this analogy holds up to all things, but its been helping my organization navigate the application of agents, since it allows us to allocate spend depending on the seniority of each developer. Thus ive been feeling like an underwriter having to figure out if a developer requesting more credits or budget for agentic code can be trusted to pay off the debt they will accrue.
aaaaand right on cue: https://github.com/anthropics/claude-code/commit/e431f5b4964... https://www.threads.com/@boris_cherny/post/DT15_k2juQH/at-th...
There's this implied trust we all have in the AI companies that the models are either not sufficiently powerful to form a working takeover plan or that they're sufficiently aligned to not try. And maybe they genuinely try but my experience is that in the real world, nothing is certain. If it's not impossible, it will happen given enough time.
If the safety margin for preventing takeover is "we're 99.99999999 percent sure per 1M tokens", how long before it happens? I made up these numbers but any guess what they are really?
Because we're giving the models so much unsupervised compute...
I hope you might be somewhat relieved to consider that this is not so in an absolute sense. There are plenty of technological might-have-beens that didn't happen, and still haven't, and probably will never—due to various economic and social dynamics.
The counterfactual—all that's possible happens—ie almost tautological.
We should try and look at these mechanisms from an economic standpoint, and ask "do they really have the information-processing density to take significant long-term independent action?"
Of course, "significant" is my weasel word.
> we're giving the models so much unsupervised compute...
Didn't you read the article? It's wasted! It's kipple!
Can we please stop with the backhanded compliments and judgement? This is cutting edge technology in a brand new field of computing using experimental methods. Please give the guy a break. At least he's trying to advance the state of the art, unlike all the people that copy everyone else.
The problem is that as an outsider it really looks like someone is trying to herd a bunch of monkeys into writing Shakespeare, or trying to advance impressionist art by pretending a baby's first crayon scratches are equivalent to a Pollock.
I bet he's having a lot of fun playing around with "cutting-edge technology", but it's missing any kind of scientific rigor or analysis, so the results are going to be completely useless to anyone wanting to genuinely advance the use of LLMs for programming.
