I work on software security at MITRE, including serving as amember of the OmniBOR Working Group, where I lead development of the Rustimplementation, and as the project manager for Hipcheck, a tool…
On January 1st, Steve Yegge published “Welcome to Gas Town,” an introduction to his new AI agent orchestration tool written in a loose and chaotic mode, and accompanied by AI-generated images depicting a fictional industrial city populated with weasels (yes, really).
Reactions were swift, mostly agog at the scale and hubris of such a (self-admittedly) wasteful and obscenely expensive system, and alternately confused or amazed at the amount of new, insular language tailor-made to describe it.
In the interest of making Gas Town intelligible (because, despite the prose, the idea of agent orchestration it describes will be important), I’d like to share a quick decoder for the many new terms Steve introduces. His article itself offers definitions, but those definitions reuse his insular terms, making by-hand decoding tedious. Here, I’ve done the work for you.
| Steve’s Term | Real-World Definition | Alternative Term |
|---|---|---|
| Town | Top-level folder containing your individual projects. The gt binary manages projects under this folder. | Workspace |
| Rig | A project. It’s a folder tracked by a unique Git repository within your workspace. | Project |
| Overseer | The user (you). You have an “inbox” to receive notifications from agents in your projects. | User |
| Mayor | The managing agent for a project. Usually you send this agent messages, and it coordinates the work of other agents in the project. | Manager Agent |
| Polecat | Worker agent, taking commands from the mayor, doing some work, submitting a Merge Request, and then stopping. | Worker Agent |
| Refinery | Merge agent, who coordinates and makes decisions about merge requests coming from Worker Agents. | Merge Agent |
| Witness | Fixer agent, that watches the worker agents and tries to fix any that are stuck. | Fixer Agent |
| Deacon | Maintenance agent, runs a consistent workflow in a loop, unlike “worker agents” who do arbitrary tasks and then die. | Maintenance Manager Agent |
| Dogs | Maintenance worker agents who do cleanup tasks, directed by the Maintenance Agent. | Maintenance Worker Agents |
| Boot the Dog | Maintenance Manager checker agent, just checks on the Maintenance Manager Agent periodically to see if it needs a reboot or anything else. | Maintenance Manager Checker Agent |
| Crew | Persistent Worker Agents, which you talk to directly (not through the Mayor), and which persist after their tasks are done, to be reused. These are per-Project. | Persistent Worker Agents. |
| Beads | System for tracking work history across the system. | Work Tracker |
| Rig Beads | Project-specific work, tracked in the Work Tracker. | Project Work |
| Town Beads | Whole-workspace work, tracked in the Work Tracker. | Workspace Work |
Even with these definitions and alternative terms, Gas Town is still a bit of a mess, with watchers-on-watchers at times (do we really need a Maintenance Manager Checker Agent?). That said, hopefully this decoder at least makes understanding what Gas Town is easier.
Read the original article
Comments
I’m very bought in to the idea that raw coding is now a solved problem with the current models and agentic harnesses. Let alone what’s coming in the near term.
That being said, I think we’re in a weird phase right now where people’s obvious mental health issues are appearing as “hyper productivity” due to the use of these tools to absolutely spam out code that isn’t necessarily broadly coherent but is locally impressive. I’m watching multiple people both publicly and privately clearly breaking down mentally because of the “power” AI is bestowing on them. Their wires are completely crossed when it comes to the value of outputs vs outcomes and they’re espousing generated nonsense as it’s thoughtful insight.
It’s an interesting thing to watch play out.
Mm.
I'd agree, the code "isn’t necessarily broadly coherent but is locally impressive".
However, I've seen some totally successful, even award-winning, human-written projects where I could say the same.
Ages back, I heard a woodworking analogy:
Now, I've never made anything more complex than furniture, so I don't know how well that fit the previous models let alone the current ones… but I've absolutely seen success coming out of bigger balls of mud than the balls of mud I got from letting Claude loose for a bit without oversight.LLM code is like MDF. Really useful for cheap furniture, massively cheaper than solid wood, but it would be a mistake to use it as a structural element in a house.Still, just because you can get success even with sloppy code, doesn't mean I think this is true everywhere. It's not like the award was for industrial equipment or anything, the closest I've come to life-critical code is helping to find and schedule video calls with GPs.
By theshrike79 2026-01-2011:52 "Without oversight" is the key here.
You need to define the problem space so that the agent knows what to do. Basically give it the tools to determine when it's "done" as defined by you.
By spmurrayzzz 2026-01-1916:433 reply This has also been an interesting social experiment in that we get to see what work people think is actually impressive vs trivial.
Folks who have spent years effectively snapping together other people’s APIs like LEGOs (and being well-compensated for it) are understandably blown away by the current state of AI. Compare that to someone writing embedded firmware for device microcontrollers, who would understandably be underwhelmed by the same.
The gap in reactions says more about the nature of the work than it does about the tools themselves.
By aaronblohowiak 2026-01-1917:361 reply >Compare that to someone writing embedded firmware for device microcontrollers, who would understandably be underwhelmed by the same.
One datum for you: I recently asked Claude to make a jerk-limited and jerk-derivative-limited motion planner and to use the existing trapezoidal planner as reference for fuzzy-testing various moves (to ensure total pulses sent was correct) and it totally worked. Only a few rounds of guidance to get it to where I wanted to commit it.
By spmurrayzzz 2026-01-1918:221 reply My comment above I hope wasn't read to mean "LLMs are only good at web dev." Only that there are different capability magnitudes.
I often do experiments where I will clone one of our private repos, revert a commit, trash the .git path, and then see if any of the models/agents can re-apply the commit after N iterations. I record the pass@k score and compare between model generations over time.
In one of those recent experiments, I saw gpt-oss-120b add API support to swap tx and rx IQ for digital spectral inversion at higher frequencies on our wireless devices. This is for a proprietary IC running a quantenna radio, the SDK of which is very likely not in-distribution. It was moderately impressive to me in part because just writing the IQ swap registers had a negative effect on performance, but the model found that swapping the order of the IQ imbalance coefficients fixed the performance degradation.
I wouldn't say this was the same level of "impressive" as what the hype demands, but I remain an enthusiastic user of AI tooling due to somewhat regular moments like that. Especially when it involves open weight models of a low-to-moderate param count. My original point though is that those moments are far more common in web dev than they are elsewhere currently.
EDIT: Forgot to add that the model also did some work that the original commit did not. It removed code paths that were clobbering the rx IQ swap register and instead changed it to explicitly initialize during baseband init so it would come up correct on boot.
By aaronblohowiak 2026-01-1920:22 Ah yes the magic is more developed for commonly documented cases than niche stuff, 100% sorry I misinterpreted your post to mean that they are not useful for embedded rather than less capable for embedded. Also, your stuff is way more deep than anything I am doing (motion planning stuff is pretty well discussed online literature).
This is not true. You can see people who are much older and built a lot of the "internet scale" equally excited about it, e.g: freebsd OG developers, Steve himself (who wrote gas town) etc.
In fact, I would say I've seen more people who are "OG Coders" excited (and in their >50s) then mid generation
By spmurrayzzz 2026-01-1920:55 I think you're shadow-boxing with a point I never made. I never said experienced devs are not or can not be excited about current AI capabilities.
Lots of experienced devs who work in more difficult domains are excited about AI. In fact, I am one of them (see one of my responses in this thread about gpt-oss being able to work on proprietary RF firmware in my company [1]).
But that in no way suggests that there isn't a gap in what impresses or surprises engineers across any set of domains. Antirez is probably one of the better, more reasoned examples of this.
By phist_mcgee 2026-01-203:351 reply I think this says a lot about yourself and where your prejudices and preferences lie.
By spmurrayzzz 2026-01-2015:10 Preferences I think I get, but prejudices?
The OED defines prejudice as a "preconceived opinion that is not based on reason or actual experience."
My day to day work involves: full stack web dev, distributed systems, embedded systems, and machine learning. In addition to using AI tooling for dev tasks, we also use agents in production for various workflows and we also train/finetune models (some LLMs, but also other types of neural networks for anomaly detection, fault localization, time series forecasting, etc). I am basing my original commentary in this thread on all of that cumulative experience.
It has been my observation over the last almost 30 years of being a professional SWE that full stack web dev has been much easier and simpler than the other domains I work in. And even further, I find that models are much better at that domain on average than the other domains, measured by pass@k scores on private evals representing each domain. Anecdotal experience also tends to match the evals.
This tracks with all the other information we have pertaining to benchmark saturation, the "we need harder evals" crowd has been ringing this bell for the last 8-12 months. Models are getting very good at the less complex tasks.
I don't believe it will remain that way forever, but at present its far more common to see someone one shot a full stack web app from a single prompt than something like kernel driver for a NIC. One class of devs is seeing a massive performance jump, another class is not.
I don't see how that can be perceived as prejudice, it just may be an opinion you don't agree with or an observation that doesn't match your own experience (both of which are totally valid and understandable).
If you give every idiot a worldwide heard voice, you will hear every idiot from the whole world. If you give every idiot a tool to make programs, you will see a lot of programs made by idiots.
Steve Yegge is not an idiot or a bad programmer. Possibly just hypomanic at most. And a good, entertaining writer. https://en.wikipedia.org/wiki/Steve_Yegge
Gas Town is ridiculous and I had to uninstall Beads after seeing it only confuse my agents, but he's not completely insane or a moron. There may be some kernels of good ideas inside of Gas Town which could be extracted out into a better system.
By yetihehe 2026-01-1914:34 > Steve Yegge is not an idiot or a bad programmer.
I don't think he's an idiot, there are almost no actual idiots here on HN in my opinion and they don't write such articles or make systems like Steve Yegge. I'm only commenting about giving more tools to idiots. Even tools made by geniuses will give you idiotic results when used by actual idiots, but a lot of smart people want to lower barriers of entry so that idiots can use more tools. And there are a lot of idiots who were inactive just because they didn't have the tools. Famous quote from a famous Polish essayist/futurist Stanisław Lem: "I didn't know there are so many idiots in this world until I got internet".
By fegd85 2026-01-3016:29 Even if I looked past the overwrought, self-indulgent Mad Max LARP (and the poor judgment evidenced by the prioritization of world-building minutia while the basic architecture is imploding), the cost of finding those kernels in a monstrosity of this size negates any ROI. 189k lines in four weeks will inevitably surface interesting pattern combinations — that's not merit, that's sample size. You might as well search the Library of Babel; at least the patterns are guaranteed to exist there.
The other problem with that reasoning is that whatever patterns ARE interesting are more likely to be new to AI-assisted coding generally – meaning a cleaner system built for the same use case will surface them without the archaeological dig, just by virtue of its builder having the skill to design it (and crucially, being more interested in designing it than in creating AI drawings of polecats in steampunk-adjacent garb).
I'm also a bit curious about at which point you start considering someone an idiot when they keep making objectively idiotic moves – the whimsical Disneyfied presentation, the "please don't download this" false modesty while keeping the repo public, the inexplicable code growth all come from the same place. They're not separate quirks: they're the same inability to edit, the same need for immediate audience validation, the same substitution of volume and narrative for actual engineering discipline. Someone who thinks "Polecats" and "Guzzoline" are good names for production abstractions is not suddenly going to develop the editorial rigor to scrap a codebase and rebuild.
Which is why it's worth remembering that Yegge's one successful shipped project was Grok, an internal tool used by Google engineers, so Yegge seems to have bought his own hype, missing how much of that project's success was likely subsidized by its user base comprising people skilled enough to route around its limitations.
These days he seems to be building for developers in general, but critically might be missing that actual developers immediately clock the project's ineptitude + Yegge's immature, narcissistic prioritization and peace the fuck out. The end result of this is filtering for the self-described vibe-coder types, people already Dunning-Krugered enough to believe you can prompt your way into a complete system without knowing how to reason about that system in order to guide the AI.
Which, fittingly, is how you end up with users who can't even follow "please don't download this yet".
By sonnig 2026-01-1913:54 Well put. I can't help thinking of this every time I see the 854594th "agent coordination framework" in GitHub. They all look strangely similar, are obviously themselves vibe-coded, and make no real effort to present any type of evidence that they can help development in any way.
By petesergeant 2026-01-197:34 > where people’s obvious mental health issues
I think the kids would call this "getting one-shotted by AI"
By GrowingSideways 2026-01-1910:491 reply > raw coding is now a solved problem
Surely this was solved with fortran. What changed? I think most people just don't know what program they want.
You no longer have to be very specific about syntax. There's now an AI that can translate your idea into whatever language you want.
Previously, if you had an idea of what the program needed to do, you needed to learn a new language. This is so hard that we use language itself as a metaphor: It's hard to learn a new language, only a few people can translate from French to English, for example. Likewise, few people can translate English to Fortran.
Now, you can just think about your program in English, and so long as you actually know what you want, you can get a Fortran program.
The issue is now what it was originally for senior programmers: to decide what to make, not how to make it.
The hard part of software development is equivalent to the hard part of engineering:
Anyone can draw a sketch of what a house should look like. But designing a house that is safe, conforms to building regulations, and which wouldn't be uncomfortable to live in (for example, poor choice of heat insulation for the local climate) is the stuff people train on. Not the sketching part.
It's the same for software development. All we've done is replace FORTRAN / Javascript / whatever with a subset of a natural language. But we still need to thoroughly understand the problem and describe it to the LLM. Plus the way we format these markdown prompts, you're basically still programming. Albeit in a less strict syntax and the "compiler" is non-deterministic.
This is why I get so mythed by comments about AI replacing programmers. That's not what's happening. Programming is just shifting to a language that looks more like Jira tickets than source code. And the orgs that think they can replace developers with AI (and I don't for one second believe many of the technology leaders think this, but some smaller orgs likely do) are heading for a very unpleasant realisation soon.
I will caveat this by saying: there are far too many naff developers out there that genuinely aren't any better than an LLM. And maybe what we need is more regulation around software development, just like there is in proper engineering professions.
By throw310822 2026-01-208:17 > Anyone can draw a sketch of what a house should look like. But designing a house that is safe, conforms to building regulations, and which wouldn't be uncomfortable to live in...
And now we have AIs that can take your sketch on paper and add all these complex and technical things by themselves. That's the point.
> Programming is just shifting to a language that looks more like Jira tickets than source code.
Sure, but now I need to be fluent in prompt-lang and the underlying programming language if you want me to be confident in the output (and you probably do, right?)
No, you have to be fluent in the domain. That is ultimately where the program is acting. You can be confident it works if it passes domain level tests.
You save all the time that was wasted forcing the language into the shape you intended. A lot of trivial little things ate up time, until AI came along. The big things, well, you still need to understand them.
By majormajor 2026-01-1917:43 > You can be confident it works if it passes domain level tests.
This is generally true for things you run locally on your machine IF your domain isn't super heavy on external dependencies or data dependencies that cause edge cases and cause explosions in test cases. But again, easier to inspect/be sure of those things locally for single-player utilities.
Generally much less true for anything that touches the internet and deals with money and/or long-term persistent storage of other people's data. If you aren't fluent in that world you'll run software built on old versions of third party code with iterations to make further changes that have to be increasingly broad in scope against a set of test cases that is almost certainly not as creative as a real attacker.
Personally I would love to see stuff move back to local user machines vs the Google-et-al-owned online world. But I don't think "cheap freeware" was the missing ingredient that prevented the corporate consolidation. And so people/companies who want to play in that massively-online world (where the money is) are still going to have to know the broader technical domain of operating online services safely and securely, which touches deep into the code.
So I, personally, don't have to be confident in one-off or utility scripts for manual tasks or ops that I write, because I can be confident in the domain of their behavior since I'm intimately familiar with the surrounding systems. Saves me a TON of time. Time I can devote to the important-to-get-correct code. But what about the next generation? Not familiar with the surrounding systems, so not even aware of what the domains they need to know (or not know) in depth are? (Maybe they'll pay us a bunch of money to help clean up a mess, which is a classic post-just-build-shit-fast successful startup story.)
By hnlmorg 2026-01-1915:40 I think the GP is correct.
You can get some of the way writing prompts with very little effort. But you almost always hit problems after a while. And once you do, it feels almost impossible to recover without restarting from a new context. And that can sometimes be a painful step.
But with learning to write effective prompts will get you a lot further, a lot quicker and with less friction.
So there’s definitely an element of learning a “prompt-lang” to effective use of LLMs.
By GrowingSideways 2026-01-1921:06 > Sure, but now I need to be fluent in prompt-lang and the underlying programming language if you want me to be confident in the output (and you probably do, right?)
Using a formal language makes the problem space unambiguous. That is just as much a benefit as it is a barrier to entry. Once you learn this formal language, the ability to read code and see the surface area of the problem is absolutely empowering. Using english to express this is an exercise in frustration (or, occasionally, genius—but genius is not necessary with the formal language).
Programs are not poetry!
By GrowingSideways 2026-01-1914:31 Again, I don't think most people are prepared to articulate what behavior they want. Fortran (and any other formal language) used to force this, but now you just kind of jerk off on the keyboard or into the microphone and expect mind-reading.
Reactionarily? Sure. Maybe AI has some role to play there. Maybe you can ask the chatbot to modify settings.
I am no fan of chatbots. But i do have empathy for the people responsible for them when their users start complaining that programs don't do what they want, despite the chatbots delivering precisely the code demanded.
By hahahahhaah 2026-01-197:21 Yeah I am definitely trying to stay off hype and just use the damn tool
There is a lot of research on how words/language influences what we think, and even what we can observe, like the Sapir-Whorf hypothesis. If in a langauge there is one word for 2 different colors, speakers of it are unable to see the difference between the colors.
I have a suspicion that extensive use of LLMs can result in damage to your brain. That's why we are seeing so many mental health issues surfacing up, and we are getting a bunch of blog posts about "an agentic coding psychosis".
It could be that llms go from bicycles for the brain to smoking for the brain, once we figure out the long term effects of it.
> If in a langauge there is one word for 2 different colors, speakers of it are unable to see the difference between the colors.
That is quite untrue. It is true that people may be slightly slower or less accurate in distinguishing colors that are within a labeled category than those that cross a category boundary, but that's far from saying they can't perceive the difference at all. The latter would imply that, for instance, English speakers cannot distinguish shades of blue or green.
The point I was trying to make is that the way our brain works is deeply connected to language and words, including how fast and how accurate you perceive colors [0][1]. And interacting with an LLM could have unexpected side effects on it, because we were never before exposed to "statistically generated language" in such amounts.
[0]: https://youtu.be/RKK7wGAYP6k?si=GK6VPP0yoFoGyOn3 [1]: https://youtu.be/I64RtGofPW8?si=v1FNU06rb5mMYRKj&t=889
> If in a langauge there is one word for 2 different colors, speakers of it are unable to see the difference between the colors.
Perhaps you mean to say that speakers are unable to name the difference between the colours?
I can easily see differences between (for example) different shades of red. But I can't name them other than "shade of red".
I do happen to subscribe to the Sapir-Whorf hypothesis, in the sense that I think the language you think in constrains your thoughts - but I don't think it is strong enough to prevent you from being able to see different colours.
No, if you show them two colors and ask them if they are different, they will tell you no.
EDIT: I have been searching for the source of where I saw this, but can't find it now :(
EDIT2: I found a talk touching in the topic with a study: https://youtu.be/I64RtGofPW8?si=v1FNU06rb5mMYRKj&t=889
By JumpCrisscross 2026-01-199:061 reply > if you show them two colors and ask them if they are different, they will tell you no
The experiments I've seen seem to interrogate what the culture means by colour (versus shade, et cetera) more than what the person is seeing.
If you show me sky blue and Navy blue and ask me if they're the same colour, I'll say yes. If you ask someone in a different context if Russian violet and Midnight blue are the same colour, I could see them saying yes, too. That doesn't mean they literally can't see the difference. Just that their ontology maps the words blue and violet to sets of colours differently.
If you asked me if a fire engine and a ripe strawberry are the same color I would say yes. Obviously, they are both red. If you held them next to each other I would still be able to tell you they are obviously different shades of red. But in my head they are both mapped to the red "embedding". I imagine that's the exact same thing that happens to blue and green in cultures that don't have a word for green.
If on the other hand you work with colors a lot you develop a finer mapping. If your first instinct when asked for the name of that wall over there is to say it's sage instead of green, then you would never say that a strawberry and a fire engine have the same color. You might even question the validity of the question, since fire engines have all kinds of different colors (neon red being a trend lately)
By JumpCrisscross 2026-01-199:561 reply > in my head they are both mapped to the red "embedding"
Sure. That's the point. These studies are a study of language per se. Not how language influences perception to a meanigful degree. Sapir-Whorf is a cool hypothesis. But it isn't true for humans.
(Out of curiosity, what is "embedding" doing that "word" does not?)
Word would imply that this only happens when I translate my thoughts to a chosen human language (or articulate thoughts in a language). I chose embedding because I think this happens much earlier in the pipeline: the information of the exact shade is discarded before the scene is committed to memory and before most conscious reasoning. I see this as something happening at the interface of the vision system, not the speech center.
Which is kind of Sapir-Whorf, just not the extreme version of "we literally can't see or reason about the difference", more "differences we don't care about get lost in processing". Which you can kind of conceptualize as the brain choosing a different encoding, or embedding space (even though obviously such a thing does not exist in the literal sense in our brains)
Edit: in a way, I would claim Sapir-Whorf is mistaking correlation for causation: it's not that the words we know are the reason for how we can think, it's that what differences we care about cause both the ways we think and the words we use
By JumpCrisscross 2026-01-1913:07 > the information of the exact shade is discarded before the scene is committed to memory and before most conscious reasoning
I'm curious if we have any evidence for this. A lot of visual processing happens in the retina. To my knowledge, the retina has no awareness of words. I'd also assume that the visual cortex comes before anything to do with language, though that's just an assumption.
> it's not that the words we know are the reason for how we can think, it's that what differences we care about cause both the ways we think and the words we use
This is fair. Though for something like colour, a far-older system in our brains than language, I'd be sceptical of the latter controlling the former.
By pverheggen 2026-01-199:131 reply You're probably thinking of the Himba tribe color experiment - which as it turns out, was mostly fabricated by a BBC documentary:
By bkolobara 2026-01-199:27 Yes, I think this was it! Thanks for sharing the link. I had no idea that part was fabricated.
By cthalupa 2026-01-199:08 The ability for us to look at a gradient of color and differentiate between shades even without distinct names for them seems to disprove this on its face.
Unless the question is literally the equivalent of someone showing you a swatch of crimson and a swatch of scarlet and being asked if both are red, in which case, well yeah sure.
By skywhopper 2026-01-1912:361 reply But the color thing is self-evidently untrue. It’s not even hard to talk about. Unless you yourself are colorblind I think that would be obvious?
Sort of, at least some degree of relativism exists though how much is debated. Would you ever talk about sea having the same color as wine? But that's exactly what Homer called it.
https://en.wikipedia.org/wiki/Wine-dark_sea
https://en.wikipedia.org/wiki/Linguistic_relativity_and_the_...
By cthalupa 2026-01-1920:04 This is still quite clearly something different than being unable to see the different colors, though.
Their mental model, sure. The way they convey it to others, sure.
But you can easily distinguish between two colors side by side that are even closer in appearance than wine and the sea, even if you only know one name for them. We can differentiate between colors before we even know the words for them when we're young, too.
The idea of gas town is simultaneously appealing and appalling to me. The waste and lack of control is wild, but at the same time there's at least a nugget of fascinating, useful work in there. In a world where compute is cheap and abundant and the models are a notch smarter, I think it's the start of a useful framework for what the future of augmented work might look like.
I have no interest in using gas town as it is (for a plethora of reasons, not the least of which being that I'm uninterested in spending the money), but I've been fascinated with the idea of slowing it down and having it run with a low concurrency. If you've got a couple A100s, what does it look like if you keep them busy with two agents working concurrently (with 20+ agents total)? What does it mean to have the town focus the scope of work to a series of non-overlapping changesets instead of a continuous stream of work?
If you don't plan to have it YOLO stuff in realtime and you can handle the models being dumber than Claude, I think you can have it do some really practical, useful things that are markedly better than the tools we have today.
I put it in a VM and had it build a really simple todo app for me the other day. It wasted so many tokens that I can't help but agree with you right now. And I could certainly have done the same thing with beads and opus in approximately the same amount of time.
However, the gas town one was almost completely hands off. I think my only interventions were due to how beta it was, so I had to help it work around its own bugs to keep from doing stupid things.
Other than that, it implemented exactly what I asked for in a workable fashion with effectively one prompt. It would have taken several prompts and course corrections to get the same result without it.
Other than the riskyness (it runs in dangerous permissions mode) and incredible cost inefficiency, I'd certainly use it.
By safety1st 2026-01-196:01 If gas town can actually do stuff well at any price it'll have a radical impact on how society is organized, because there are people out there who have practically unlimited money (billions of dollars of their own to spend, plus they can get the government to print more dollars for them if necessary; you probably already know who a few of these people are).
I've only started using coding agents recently and I think they go a long way to explain why different people get different mileage from "AI." My experience with Opencode using its default model, vs. Github Copilot using its default model, is night and day. One is amazing, the other is pretty crappy. That's a product of both the software/interface and the model itself I'd suspect.
Where I think this goes in the medium term is we will absolutely spin up our own teams of agents, probably not conforming to the silly anthropomorphized "town" model with mayors and polecats and so on, but they'll be specialized to particular purposes and respond to specific events within a software architecture or a project or even a business model. Currently the sky's the limit in my mind for all the possible applications of this, and a lot of it can be done with existing and fairly cheap models too, so the bottleneck is, surprise surprise... developer time! The industry won't disappear but it will increasingly revolve around orchestrating these teams of models, and software will continue to eat the world.
I guess tokens get cheaper all the time, and we can fix the risk via sufficient sand boxing. (I mean the risk to your computer.)
By Avicebron 2026-01-195:10 I've been running my own version of what Gas Town seems to be in a couple of proxmox hosts for a while now, it's fine.
By condiment 2026-01-195:27 If software engineers can agree on anything, it's that LLM experiences are wildly inconsistent. People have similar inconsistencies. We have different experiences, intellects, educations, priorities, motivations, value systems. And in software specifically (and institutions generally) we create methodologies and processes that diminish our inconsistencies and leverage our strengths.
Gas town is a demonstration of a methodology for getting a consistent result from inconsistent agents. The case in point is that Yegge claims to have solved the MAKER problem (tower of Hanoi) via prompting alone. With the right structure, quantity has a quality all its own.
By hahahahhaah 2026-01-197:23 I feel like each of these things is going to be bitter lessoned by a model who you can just say "yeah get a bunch of agents together and clone twitter, get em to put requirements together first, ya know, measure once and all that. promise em a beer when done".
I'd help build Gas City and Gas State, and Gas Country if that would mean we actually would solve the things AI promised to solve. All sickness, famine, wealth ...
The problem is, we're just fidgeting yolo-fizzbuzz ad nauseam.
The return on investment at the moment is probably one of the worst in the history of human investments.
AI does improve over time, still today, but we're going to run out of planet before we get there...
By ViscountPenguin 2026-01-193:572 reply As of yet, the AI models doing important work are still pretty specialized. I'd be happy to pitch in to run something like an open source version of alpha-fold, but I'm not aware of any such projects.
I have trouble seeing LLMs making meaningful progress on those frontiers without reaching ASI, but I'd be happy to be wrong.
By Terr_ 2026-01-198:59 I think part of the problem/difference is that all "important work" needs to be auditable and understood by humans. We need to be able to fix bugs, and not just roll the dice and hoping that a lack of symptoms means everything is cured.
By camgunz 2026-01-1922:16 Even alphafold generated a bunch of slop,like impossible proteins and such.
That doesn't make any sense.
Yegge named it Gas Town as in "refinery" because the main job for the human at this stage is reviewing the generated code and merging. "
The whole point of the project is to be in control. Yegge even says the programmers who can read/review a lot of code fast are the new 10x (paraphrasing).
By colin_jack 2026-01-1915:421 reply "I’ve never seen the code, and I never care to, which might give you pause"
https://steve-yegge.medium.com/welcome-to-gas-town-4f25ee16d...
By colin_jack 2026-01-1917:16 Yeah and its not a big focus of the posts which is interesting. I'd have thought he'd spend a lot more time talking about the workflow he's using, the specs/feature definitions he's writing, and so on.
By soulofmischief 2026-01-193:593 reply The Wright brothers are idiots, if it were me I'd have made a supersonic jet from the get go and not waste my time mucking around with prototypes.
The prototype phase meant data centers are now measured in MW instead of TFLOPS.
At a time where we were desperate to reduce emissions, data centers now consume around 20% of the energy consumed by the entire aviation sector, with consumption is rising at 15% YoY.
Never mind the water required to cool them, or the energy and resources required to build them, the capital allocation, and the opportunity cost of not allocating all of that to something else.
And this is, your words, the prototype phase.
By neoromantique 2026-01-1915:26 Emissions and Energy consumed do not necessarily have to be linked up.
We have plenty of ways to make clean energy, it is only matter of incentives.
As long as burning coal is simply cheaper, business will burn coal.
By soulofmischief 2026-01-1912:16 The computing power in a crappy cheap modern phone used to fill up a warehouse and cost a ton of energy, relatively. Moore's law might not remain steadfast, but if history is any indication, we'll find a way to make the technology more efficient.
So, yes, prototypes often use more energy than the final product. That doesn't mean we shouldn't sustainable build datacenters, but that's conflating issues.
By jpfromlondon 2026-01-199:311 reply the Wright brothers sold me a subscription to a supersonic jet and I've got a bundle of matchsticks and some canvas.
By soulofmischief 2026-01-1912:131 reply On the other hand, flight is ubiquitous and has changed everything.
Flight changed everything when it comes to warfare. But as far as individuals are concerned, the average human on the planet will take a handful of flights in their lifetime, at best, and nearly all flights that are taken are for recreation which is ultimately fungible with other forms of recreation that don't involve taking flights, and of the flights that aren't for recreation most could be replaced by things like video calls, and the vast and overwhelming majority of the goods that make up the lifeblood of the global economy are still shipped by ship, not shipped by air.
Which is to say, the commercial aviation industry could permanently collapse tomorrow and it would have only a marginal impact on most people's lives, who would just replace planes with train, car, or boat travel. The lesson here is that even if normal people experience some tangential beneficial effects from LLMs, their most enduring legacy will likely be to entrench authority and cement the existing power structures.
By soulofmischief 2026-01-1919:45 It's silly to say that the ability to fly has not changed society. Or that it won't continue to change society, if we manage to become space-faring before ruining our home planet.
The phrase, "The average human on the planet will take a handful of flights in their lifetime" is doing a lot of work. What are those flights to? How meaningful/important were the experiences? What cultural knowledge was exchanged? What about crucial components that enable industries we depend on? For example, a nuclear plant might constantly be ordering parts that are flown in overnight.
In general you're really minimizing the importance of aviation without really providing anything to back up your claims.
We were promised supersonic jets today or very soon though and our economies have been held hostage waiting for that promise.
We are perpetually just months away from software jobs being obsolete.
AGI was achieved internally at OpenAI a year ago.
Multiple companies have already re-hired staff they had fired and replaced with AI.
etc.
By soulofmischief 2026-01-196:481 reply Your problem is thinking that hype artists, professionals and skeptics are all the same voice with the same opinion. Because of that, you can't recognize when sentiment is changing among the more skeptical.
You are responding to some voices in your head, not to the context of the conversation.
You're also presuming too much about what I'm thinking and being dead wrong about that.
By soulofmischief 2026-01-1912:121 reply I am responding to what you wrote:
> We are perpetually just months away from software jobs being obsolete.
only hype artists are saying this. and you're using it as a way to negate the argument of more skeptical people.
Functional illiteracy and lack of any capacity to hold any context longer than two sentences has long been a plague on HN. Now that we've outsourced our entire thinking process to "@grok is this true", it has now claimed almost the entirety of human race.
soulofmischief: complains that AI-skeptics would say the Wright brothers were idiots because they didn't imediately implement a supersonic jet
ares623: we were promised supersonic jets today or very soon (translation: AI hype and scam artists have already promised a lot now)
eru: The passive voice is doing a lot of work in your sentence. (Translation: he questions the validity of ares623's statement)
me: Here are just three examples of hype and scam promising the equivalent of super jet today, with some companies already being burned by these promises.
soulofmischief: some incoherent rambling
By soulofmischief 2026-01-1920:001 reply Apply your own "functional literacy". I made a clarification that those outside of an industry have to separate the opinions of professionals and hype artists.
The irony of your comment would be salient, if it didn't feel like I was speaking with a child. This conversation is over, there's no reason to continue speaking with you as long you maintain this obnoxious attitude coupled with bad reading comprehension.
It's a hillarious attempt to save face.
"Separate opinions of professionals" etc.
Here's Ryan Dahl, cofounder of Deno, creator of Node.js tweeting today:
--- start quote ---
This has been said a thousand times before, but allow me to add my own voice: the era of humans writing code is over. Disturbing for those of us who identify as SWEs, but no less true. That's not to say SWEs don't have work to do, but writing syntax directly is not it.
https://x.com/rough__sea/status/2013280952370573666
--- end quote ---
Professional enough for you?
They have everything to gain by saying those things. It doesn’t even need to be true. All the benefits arrive at the point of tweeting.
If it turns out to be not true then they don’t lose anything.
So we are in a state where people can just say things all the time. Worse, they _have_ to say. To them, Not saying anything is just as bad as being directly against the hype. Zero accountability.
By meowface 2026-01-2015:58 What does he have to gain? This is Deno: https://deno.com
By soulofmischief 2026-01-2121:41 Yes, my point is that industry professionals are re-calibrating based on the last year of agentic coding advancements, and that this is different from hype men on YouTube from 1-2 years ago claiming that they don't have to write code anymore.
Congratulations, now you're starting to understand! :)
By meowface 2026-01-2015:58 What is incorrect or bad about his statement?
Your posts here remind me of Trumpists citing random Twitter leftists as Democratic party leaders.
Lol. "random leftists"
First two come directly from OpenAI, Anthropic and others
Last one is literally made rounds even on HN e.g. Klarna bringing back their support staff after they tried to replace them with AI.
Last one is irrelevant. Of course some companies are miscalculating.
OpenAI never claimed they had achieved AGI internally. Sam was very obviously joking, and despite the joke being so obvious he even clarified hours later.
>In a post to the Reddit forum r/singularity, Mr Altman wrote “AGI has been achieved internally”, referring to artificial general intelligence – AI systems that match or exceed human intelligence.
>Mr Altman then edited his original post to add: “Obviously this is just memeing, y’all have no chill, when AGI is achieved it will not be announced with a Reddit comment.”
Dario has not said "we are months away from software jobs being obsolete". He said:
>"I think we will be there in three to six months, where AI is writing 90% of the code. And then, in 12 months, we may be in a world where AI is writing essentially all of the code"
He's maybe off by some months, but not at all a bad prediction.
Arguing with AI skeptics reminds me of debating other very zealous ideologues. It's such a strange thing to me.
Like, just use the stuff. It's right there. It's mostly the people using the stuff vs. the people who refuse to use it because they feel it'll make them ideologically impure, or they used it once two years ago when it was way worse and haven't touched it since.
By soulofmischief 2026-01-2122:22 The insecurity is mind-boggling. So many engineers afraid to touch this stuff for one reason or another.
I pride myself in being an extremely capable engineer who can solve any problem when given the right time and resources.
But now, random unskilled people can do in an afternoon what it might have taken me a week or more to do before. Of course, I know their work might be filled with major security issues, or terrible architectural decisions and hidden tech debt that will eventually grind development to a complete halt.
I can be negative and point out these issues, or I can adopt these tools myself, and have the skilled hand required to keep things on rails. Now what I can do in a week cannot be matched by an unskilled engineer in an afternoon, because we have the same velocity multipliers.
I remember being such a purist in my youth that I didn't even want autocomplete or intellisense, because I feared it would affect my recall or stunt my growth. How far we have come. How I code has changed completely in the last year.
I code 8-20 hours a day, all day. I actively work on several projects at once, flipping between contexts to check results, review code, iterate on design/implementation, hand off new units of work to various agents. It is not a perfect process, I am constantly screaming and pulling my hair out over how stupid and forgetful and stubborn these tools can be sometimes. My output has still dramatically increased, and I have plenty extra time to ensure the quality of the code is secure and good enough.
I've given up on expecting perfection from code I didn't write myself; but what else is new? Any skilled individual who has managed engineers before knows you have to get over this quickly and accept that code from other engineers will not match your standards 100%.
Your role is to develop and enforce guidelines and processes which ensure that any code which hits production has been thoroughly reviewed, made secure and performant. There might be some stupid inline metacomments from the LLM that slip through, but if your processes are tight enough, you can produce much more code with correct interfaces, even if the insides aren't perfect. Even then, targeted refactors are more painless than ever.
Engineers who only know how to code, and at a relatively mediocre level, which I imagine is the majority of engineers now in the field who got into it because of the money, are probably feeling the heat and worried that they won't be employable. I do not share that fear, provided that anyone at all is employable.
When running a business, you'll still need to split the workload, especially as keeping pace with competition becomes an increasingly brutal exercise. The money is still in the industry, and people with money will still find ways to use it to develop an edge.
By meowface 2026-01-1913:01 The AI bubble will pop any month now.
See? I can do this too.
By soulofmischief 2026-01-194:141 reply The first recorded supersonic flight was in 1947.
By windward 2026-01-1910:05 Supersonic passenger planes failed commercially.
Are you saying that people can't work out what to code using these? Or that code is not a worthy subject to use AI for? 'cause I got news for you... 1. Improving coding improved reasoning in the models. Having a verifiable answer that is not a single thing is a good training test. 2. Software has been used for fairly serious things. We used to have skyscrapers of people doing manual math. Now we have campuses of people doing manual code. You might argue that nobody would trust AI to write code when it matters. History tells us that if that is ever true, it will pass. 3. We are not going to run out of planet. It just feels to folks that there is not enough planet for their dreams and we get population panic, energy panic etc. There is a huge fusion reactor conveniently holding us in it's gravity well and spewing out many orders of magnitude more energy than we can currently use. Chill.
I think at Gas Country levels we will need better networking systems. Maybe that backbone Nvidia just built....
By krupan 2026-01-1915:19 Replacing human computers with electronic computers is nothing like what LLMs do or how they work. The electronic computer is straight up automation. Same input in gives you the same input out every time. Electronic computers are actually pretty simple. They just do simple mathematical operations like add, subtract, multiply, and divide. What makes them so powerful is that they can do billions of those simple operations a second.
LLMs are not simple deterministic machines that automate rote tasks like computers or compilers. People, please stop believing and repeating that they are the next level of abstraction and automation. They aren't.
By toephu2 2026-01-195:18 AI can't even find a cure for the common cold.
