> But no need to wait. At a high level, Gas City is the answer to all your problems. Ha! At least, for certain classes of problem, such as, “How can I bring AI into my company and pass an audit trail,”
The important audit at my company is conducted by the FDA.
I have a feeling when they ask what processes we followed to mitigate any user harm that could be caused by software changes that "I told an AI-mayor in the form of a cartoon fox what to do and he spit out a bunch of vibecode software written by AI-driven virtual cartoon characters" is not among the answers they want to hear.
Ehhh in my experience compliance auditors are 10 behind the cutting edge. I still see auditors that don't understand Kubernetes and so ask the same questions they would about on prem machines. They don't know the questions to ask to get to the real meat of the risks. This leads them to allow things through that probably deserve more scrutiny. I bet the same thing will happen with LLM tools like this. They'll just ask if you use PRs and wave you on through.
I did an induction at some ISO certified company some years back, reading their docs. A good 50% of them contained significant content that basically read:
> the thing must be in the place where it should be
With no further information e.g. what place, where, how, when, who facilitates that?
> the person who facilitates it, is the person who facilitates it.
Yea thanks. So their ISO accredited process was basically no process. Would have been way better with a talking fox.
So I feel like humans are capable of just as bad. I'd be interested in what answer the Fox could spit out and I kinda wonder where it might fit on the bell curve of all non Gas-Town "auditable" processes. I'm all for skepticism but I feel like it would be more tangible if we instead criticised the response instead of just conjuring it as "definitely awful" because it happens to be on top of a generated stack.
I mean: I don't want it to work, but maybe we're not as good as we think we are, or the stuff we rate as super important is actually way less important with a generated context. As much as I love good code, the thought that gnaws at the back of my head is the truism that some of the most profitable code in history has been some of the "worst" code (e.g. MySpace's janky code base ontop of ColdFusion or Twitter's "Fail Whale" era).
So I'm happy that someone is exploring this space in an open way. I'm just glad I'm not the one finding that out with my face first.
Which ISO certification matters, but the key thing people should be aware of is that the primary value of the certification to customers is that your processes are documented and that deviations are tracked, so that customers can check whether the processes makes sense before signing a contract. It's important not to expect the certification itself to guarantee quality.
> We're supposed to be engineers. Criticising a concept based on conjecture and insult is unbecoming of our culture.
The entire thing is nothing but conjecture. No real software has been produced by the concept to date, except more garbage software that takes hundreds of thousands of lines where a few thousand would do.
And to be clear, Beads and Gastown are unbecoming of our “culture” and any self respecting engineer would recoil in horror at the concept.
There are some good ideas in the tools. I hope our culture has room left for curiosity and exploration in that way. I also highly doubt these will catch on over one-shotting and Jira though. Here’s one quick thought from each:
Beads keeps the issue tracker state in git. This can only work if you don’t have a PR/Review-Gate to submitting patches (to file bugs/issues/etc) but I’ve found it unexpectedly helpful for personal projects. Helpful enough to entertain the idea in other contexts.
Gastown uses an AI Agent _as the orchestrator_, and to kick stalled agents, and, that’s such an obvious thing in hindsight I can’t believe I hadn’t thought of it. I have adopted this in a few other contexts now.
How is it conjecture when you just admitted you're aware of a repo with hundreds of thousands of lines of code.
Your argument belies a lazyness or skill issue. You abandon the possibility of proof to sling mud.
People have made a shit ton of economic value with shit code over the course of history of software and now that's accelerating with this sort of shite. I appreciate its ugly but i will not follow you by fashioning a duvet out of arrogance and throwing rocks people investigating the ugly.
What they're doing it at least an interesting spectacle and ill wait for the show to end before writing my review.
What it means is that it is easy to shit on other people's work. Much harder to give constructive criticism - especially on what looks like a throwaway account.
It’s not “other people’s work” because Steve didn’t do any work. He vibe coded hundreds of thousands of lines that don’t do what they’re supposed to with many thousands of lines of documentation that are inaccurate at best and aspirational at worst. He wrote some blog posts and got them picked up by vapid outlets that had nothing else to add to boost his exposure.
Case in point: no one talks about beads or gastown on HN because it’s crap that no one uses. Even *claw and that dumb fad get more mileage. meanwhile, CC vs Codex is an ever ongoing battle and Anthropic employees announce policy changes in “Tell HN” posts which stay on the front page for days.
If you actually follow the links you posted, you will see that he didn't create a meme coin and didn't rug pull it. Someone else made the coin and set it up so he got transfer fees.
Does Yegge really think that building production software this way is a good idea?
Let's assume that managing context well is a problem and that this kind of orchestration solves it. But I see another problem with agents:
When designing a system or a component we have ideas that form invariants. Sometimes the invariant is big, like a certain grand architecture, and sometimes it's small, like the selection of a data structure. Eventually, though, you want to add a feature that clashes with that invariant. At that point there are usually three choices:
* Don't add the feature. The invariant is a useful simplifying principle and it's more important than the feature; it will pay dividends in other ways.
* Add the feature inelegantly or inefficiently on top of the invariant. Hey, not every feature has to be elegant or efficient.
* Go back and change the invariant. You've just learnt something new that you hadn't considered and puts things in a new light, and it turns out there's a better approach.
Often, only one of these is right. Usually, one of these is very, very wrong, and with bad consequences.
But picking among them isn't a matter of context. It's a matter of judgment and the models - not the harnesses - get this judgment wrong far too often (they go with what they know - the "average" of their training - or they just don't get it). So often, in fact, that mistakes quickly accumulate and compound, and after a few bad decisions like this the codebase is unsalvageable. Today's models are just not good enough (yet) to create a complete sustainable product on their own. You just can't trust them to make wise decisions. Study after study and experiement after experiment show this.
Now, perhaps we make better judgment calls because we have context that the agent doesn't. But we can't really dump everything we know, from facts to lessons, and that pertains to every abstraction layer of the software, into documents. Even if we could, today's models couldn't handle them. So even if it is a matter of context, it is not something that can be solved with better context management. Having an audit trail is nice, but not if it's a trail of one bad decision after another.
I think a lot of it comes down to the training objective, which is to fulfill the user’s request.
They have knowledge about how programs can be structured in ways that improve overall maintainability, but little room to exercise that knowledge over the course of fulfilling the user’s request to add X feature.
They can make changes which lead to an improvement to the code base itself (without adding features); they just need to be asked explicitly to do so.
I’d argue the training objective should be tweaked. Before implementing, stop to consider the absolutely best way to approach it - potentially making other refactors to accommodate the feature first.
Serious question - there's a lot of fluff talking about Gas Town, but has Gas Town shipping something in public that can be evaluated without all of this surrounding hype and blogposting?
At this point it should be clear that Gas Town has done something we can evaluate the value of.
>At this point it should be clear that Gas Town has done something we can evaluate the value of.
I see this sentiment often, repeated a couple times in here, but I don't understand why on earth that would be the case. Gas Town was released a little over three months ago. It's an ongoing open-source experiment at the bleeding edge of vendor-agnostic multi-agent orchestration.
I was using gastown for fire-and-forget prototyping of larger projects. It was flaky and scorches tokens but it was able to get larger prototypes done than I could with a single instance of my daily river (claude) alone.
> Having spent six weeks or so using Gas Town across multiple simultaneous projects, I believe I can describe the shift concretely. The bottleneck migrates from coding speed to the rate at which you can generate ideas, write specifications, and validate outputs. You are no longer limited by how fast you can build. You are limited by how fast you can think.
Interesting:
> Kubernetes asks “Is it running?” Gas Town asks “Is it done?” Kubernetes optimizes for uptime. Gas Town optimizes for completion.
I’m not sure I find the testimony of a Bain & Company AI consultant (https://www.bain.com/our-team/eric-koziol/) to be compelling for anything outside of generating fees.
This sounds like every LLM workflow, which is 'you tell the LLM what you want'.
The real distinction is of scale - whether you want a REST endpoint or a fully functional word processor.
But real, actual, complex software is at least half spec (either explicit, or implicitly captured by its code), the question is, can LLMs specify software to the same degree with Gas Town, that you get something functioning?
You provided a quote from someone who seems to be an AI-boosting influencer who claimed to use it, but where's the output in the form of code we can look at, or in the form of an app someone can use today?
I'm not an AI-denier. I use LLMs and agentic coding. They increase my productivity.
...but there is still a very real problem with people claiming that some new way of using AI is earth shattering, and changes everything based on vague anecdotes that don't involve a tangible released output that they can point to.
Yeah if this can truly just autonomously make great software, then where is all the new SaaS that is able to undercut incumbents by charging 10-20% of what they are charging?
you can always fire it up yourself and see what its all about. in my experience it generates a lot of code very quickly, that code is probably only ever supposed to be LLM maintained, not by people.
I don't think the op meant Gas Town itself (if they did, my bad), but what has Yegge done with Gas Town? By now it should have released some amazing thing if Gas Town increases productivity so much.
What has Yegge done with Gas Town? Well for one, he has posted a bunch of blog content about it which has generated chatter like this and increased his geek mindshare.
Just because he's operating in the realm of smart nerds doesn't mean he is immune to the value-inverting effects of social media.
If the post does not have any use-cases proving value then perhaps this is something yet to be validated, i.e. the burden on the users, not the creators.
Beads is cool, but I tried to use it, and the backend didn't really make sense. I have to run an sql database in the background? How does it sync with Git? (I didn't see any files/objects committed to the repo) Plus, Dolt ended up using a constant 3-30kB/s of i/o in the background, while nothing was actually going on. That and Beads has a lot of features I'm not gonna use. All of this was just too complicated for my tiny brain.
So I slapped together my own Beads implementation (https://codeberg.org/mutablecc/dingles) over a day or two. Probably has bugs, and I'm sure race conditions if you tried to use with Gas Town, and likely does not scale. But it has the minimum functionality needed to create and track issues and sync them (locally and remotely, either via normal merge, or a dedicated ticket branch). No SQL, no extra features, just JSONL and Git. Threw a whole large software project at it, and the AI took to it like a duck to water, used it to make epics for the whole project, methodically worked through them all, dependencies first, across multiple context sessions. The paradigm of making tools the AI wants to use is clearly a winner.
I loved Beads, but kept running into issues because it is so git heavy. One: not every system and project I work on uses git. Two: Sometimes I'd switch branches, and that would screw up Beads state entirely. Three: And this is at least last I used it, there's no safety net, Claude would close a Bead, without validating anything.
I wound up building my own with Claude, I made it SQLite first, syncs to GitHub, can pull down from GitHub, and I added "Gates" to stopgap Claude or whatever agent from marking things complete if they've not been: compiled, unit tests run, or simple human testing / confirmation. The Gates concept improved my experience with Claude, all too often it says it finished something, when in fact it did not. Every task must have a gate, and gates must pass before you can close a task. Gates can be reused across tasks, so if "Run unit tests" is one gate, you can reuse it for every task, when it passes, it passes for that one task <-> gate combination.
Anyway, I'm happy for Beads, Gas Town not so much my wheelhouse on the other hand.
Gas Town has always struck me as more of a performance art piece than a tool that was actually meant to be used, even among the recent hyped AI projects. If you’re using it for real, what are you using it for?
Gas Town really feels not just vibe coded but also vibe designed.
I looked into it, to see whether multi agent setups really made a difference, the entire design philosophy feels like it was « let’s add one more layer of agent and surely this time it will work » about 10 times in a row.
So now you have agents of type mayor, polecats, witnesses, deacons, dogs etc plus a slew of
Unneeded constructs with incomprehensible names.
In one of the blog post for gas town I remember reading something by the author along the lines of « it’s super inefficient, but because you burn so many tokens, you still get what you want at the end! » clearly this is also the design philosophy behind this project, just (get your ai to) throw more random abstractions and more agent types until you feel like it kinda works, don’t bother asking yourself if they actually contribute anything.
This gave me the very clear feeling that most of the complexity of gas town is absolutely not needed and probably detrimental.
Ended up building my own thing that is 10x simpler, just a simple main agent you talk to, that can dispatch subagents, they all communicate, wake each other up and keep track of work through a simple CLI. No « refinery » or « wasteland » or « molecule » or « convoys » or « deacons » or …
Nice timing. I was just noting that beads in an old repo, just ... worked. Updates worked, I didn't have super weird errors to track down... I was like "nice!" Beads bumping to 1.0 is great. I haven't used gas town in a month or so, but a stable gas town sounds very valuable.
I think Yegge's instincts that making a programmable / editable coordination layer (he calls this gas city) is a great idea. Gas town early days was definitely a wild experience in terms of needing to watch carefully lest your system be destroyed, and then I put that energy into OpenClaw - I'll probably spin up Gas City and see what it can do soon though. Very cool.
I'm pretty excited about agentic coding myself, but this does appear to be an extended ai-psychosis (i'm not super comfortable with this phrase, but it is becoming pretty recognisable).
I think he's boxed himself in by continually layering more complexity on his approach, rather than stepping back and questioning the fundamentals or the overall direction.
All of the steps Gas Town or Gas City etc are taking are towards reducing human oversight and control. This is profoundly misguided! In a world of infinite cheap software it is precisely this human decision making and control that matters.
> There will be nothing like it. You are going to want to use Gas City.
No. I do not want to talk to the mayor of my software factory, as its cartoonish minions build an infinite mountain of slop. Unreviewable, both in terms of code and the finished product.
Instead, I want to precisely capture human ideas, have those ideas questioned, challenged, improved, and then I want to bring those ideas to life, keeping the human in the loop whenever they want. Neither Beads, Gas Town, nor Gas City or anything like them are required for that.
For "hacker" news, this group is reacting like its "labor" news. I get it - this will have an impact on the current ways of building software getting deprecated.
But this is genuinely cutting-edge, new paradigm of building software. Something that will iron it's kinks out, and potentially be the way of developing software in the new Era. That's worth some curious and exploratory discussion, rather than more comments about not being the "true way of software development".
(Sorry, was put off by the crab-pulling down discussion.)
My experience is that Agentic Coding can legitimately get you mostly-working software. You do, however, still need to spend a few days groking, validating, and usually nudging/whacking it to conform to the shape you intended vs what the agent inferred.
It is pretty magical to go from brainstorming an idea in the evening, having ChatGPT Pro spit out a long list of beads to implement it, leaving it running over night in a totally empty repo and waking up to a mostly-implemented project.
I tried Beads and it kept breaking in such frustratingly random ways that I just added a Linear MCP server and called it a day. That's really all you need.
I searched on google about the cost of running Gas Town. The Gemini AI response claimed Gas town costs $100 / hour and can spit out 4000 lines of code per hour, so Gas Town costs 2.5 cents per line of code.
I tried tracking down where those numbers came from and the sources were a bit sketchy. Can anybody who has used Gas Town confirm those numbers, or report their personal numbers?
i've experimented quite a lot with multi agent setups and orchestrations.
In the end, it didn't feel worth it mostly because of high token overhead (inter agent communications, agents re reading same code, etc...) and synchronization / cooperation issues (who should do what).
What actually works for me and provides good results: multi step workflows with clearly defined steps and strong guidance for the agent.
Also I chuckled at the AI-generated "The Overseer is Alnays Right | Vacation Approved" poster in the background of the split image where the mayor is reading so you can supervise. This has strong Boondocks Catcher Freeman vibes. I want to hear the polecats/badgers' version.
I don't know if Gastown will work out. But it is quite a bold take. I am interested to see how it plays out. I suspect they will eventually roll back some of the stringent "no code reading" approach in favor of observability as the community grows.
> I’ve been saying since last year that by the end of 2026, people will be mostly programming by talking to a face. There’s absolutely NO reason to type with the Mayor. You should be able to chat with them like a person. You’ll have a cartoon fox there onscreen, in costume, building and managing your production software, and showing you pretty status updates whenever you ask for one. This is the end state for IDEs.
This is a desirable end state for highly social but perhaps slightly sociopathic extroverts who want to spend all day talking even though they aren't talking to a person.
For anyone else, it's hard to imagine considering that a desirable way to spend eight hours a day.
I cannot really get behind Gas Town or any other “agent swarm” setup. They always seem to waste an incredible amount of tokens on passing the buck around as half-finished specs, and even with a healthy amount of tokens pre-allocated they burn money faster than setting my wallet on fire…
I feel Gastown is an attempt at answering: what if i push the multi-agent paradigm to its chaotic end?
But I think the point that Yegge doesn't address and that I had to discover for myself is: getting many agents working in parallel doing different things -- while cool and exciting (in an anthromorphic way) -- might not actually be solving the right problem. The bottleneck in development isn't workflow orchestration (what Gastown does) -- it's actually problem decomposition.
And Beads doesn't actually handle the decomposed problem well. I thought it did. But all it is is a task-graph system. Each bead is task, and agents can just pick up tasks to work on. That looks a lot like an SDE picking up a JIRA ticket right? But the problem is embedding just enough context in the task that the agent can do it right. But often it doesn't, so the agent has to guess missing context. And it often produces plausible code that is wrong.
Devolving a goal into the smaller slices is really where a lot of difficulty lies. You might say, oh, "I can just tell Claude to write Epics/Stories/Tasks, and it'll figure it out". Right? But without something grounding it like a spec, Claude doesn't do a good job. It won't know exactly how much context to provide to each independent agent.
What I have found useful is spec-driven development, especially of the opinionated variety that Kiro IDE offers. Kiro IDE is a middling Cursor, but an excellent spec generator -- in fact one of the best. It generates 3 specs at 3 levels of abstraction. It generates a Requirements doc in EARS/INCOSE (used at Rolls Royce and Boeing for reducing spec ambiguity), and then generate a Design doc (commonly done at FAANG), and... then generates a Task list, which cross-references the sections of the requirements/design.
This kind of spec hugely limits the degrees of freedom. The Requirements part of the spec actually captures intent, which is key. The Design part mocks interfaces, embeds glossaries, and also embeds PBTs (property-based tests using Hypothesis -- maybe eventually Hegel?) as gating mechanisms to check invariants. The Task list is what Beads is supposed to do -- but Beads can't do a good job because it doesn't have the other two specs.
I've deployed 4 products now using Kiro spec-driven dev (+ Simon Willison's tip "do red/green tdd") and they're running in prod and so far so good. They're pressure-tested using real data.
Spec-driven development isn't perfect but I feel its aim is the correct one -- to capture intentions, to reduce the degrees of freedom, and to constrain agents toward correctness. I tried using Claude Code's /plan mode but it's nowhere as rigorous, and there's still spec drift in the generated code. It doesn't pin down the problem sufficiently.
Gastown/Beads are solutions for workflow orchestration problem (which is exciting for tech bros), but at its core, it's not the most important problem. Problem decomposition is.
Otherwise you're just solving the wrong problem, fast.
I'm a long-time Steve Yegge fan but a major Gas Town hater (now Gas City too, I guess). It's doubling down on all the wrong metaphors.
I also simply detest how Gas Town is modeled fundamentally on an extractive and destructive metaphor, the 19th century factory. I want to live in a verdant software garden, not a dystopian industrialist hellscape.
In my view the StrongDM guys are on the right long-term path.
164 comments
> But no need to wait. At a high level, Gas City is the answer to all your problems. Ha! At least, for certain classes of problem, such as, “How can I bring AI into my company and pass an audit trail,”
The important audit at my company is conducted by the FDA.
I have a feeling when they ask what processes we followed to mitigate any user harm that could be caused by software changes that "I told an AI-mayor in the form of a cartoon fox what to do and he spit out a bunch of vibecode software written by AI-driven virtual cartoon characters" is not among the answers they want to hear.
And those cartoon foxes didn't even do anything! I guess these ones do?
Don't put it past the masses. These are crazy times.
https://poignant.guide/book/chapter-3.html
> the thing must be in the place where it should be
With no further information e.g. what place, where, how, when, who facilitates that?
> the person who facilitates it, is the person who facilitates it.
Yea thanks. So their ISO accredited process was basically no process. Would have been way better with a talking fox.
So I feel like humans are capable of just as bad. I'd be interested in what answer the Fox could spit out and I kinda wonder where it might fit on the bell curve of all non Gas-Town "auditable" processes. I'm all for skepticism but I feel like it would be more tangible if we instead criticised the response instead of just conjuring it as "definitely awful" because it happens to be on top of a generated stack.
I mean: I don't want it to work, but maybe we're not as good as we think we are, or the stuff we rate as super important is actually way less important with a generated context. As much as I love good code, the thought that gnaws at the back of my head is the truism that some of the most profitable code in history has been some of the "worst" code (e.g. MySpace's janky code base ontop of ColdFusion or Twitter's "Fail Whale" era).
So I'm happy that someone is exploring this space in an open way. I'm just glad I'm not the one finding that out with my face first.
The sanatorium from American Horror Story Asylum comes to mind.
Dominique, nique, nique…
Where do I even begin to mock that except at the source? That’s just absolute insanity.
What does that even mean? Am I supposed to point Claude at garbage code bases? All it will find is garbage.
> My point is that just calling him names has no substance, but mocking his source specifically does.
He is the source. He wrote this stuff under his own volition.
The entire thing is nothing but conjecture. No real software has been produced by the concept to date, except more garbage software that takes hundreds of thousands of lines where a few thousand would do.
And to be clear, Beads and Gastown are unbecoming of our “culture” and any self respecting engineer would recoil in horror at the concept.
Beads keeps the issue tracker state in git. This can only work if you don’t have a PR/Review-Gate to submitting patches (to file bugs/issues/etc) but I’ve found it unexpectedly helpful for personal projects. Helpful enough to entertain the idea in other contexts.
Gastown uses an AI Agent _as the orchestrator_, and to kick stalled agents, and, that’s such an obvious thing in hindsight I can’t believe I hadn’t thought of it. I have adopted this in a few other contexts now.
Your argument belies a lazyness or skill issue. You abandon the possibility of proof to sling mud.
People have made a shit ton of economic value with shit code over the course of history of software and now that's accelerating with this sort of shite. I appreciate its ugly but i will not follow you by fashioning a duvet out of arrogance and throwing rocks people investigating the ugly.
What they're doing it at least an interesting spectacle and ill wait for the show to end before writing my review.
Case in point: no one talks about beads or gastown on HN because it’s crap that no one uses. Even *claw and that dumb fad get more mileage. meanwhile, CC vs Codex is an ever ongoing battle and Anthropic employees announce policy changes in “Tell HN” posts which stay on the front page for days.
If that is a foreign concept, I hope to god that you have excellent health insurance.
> The important audit at my company is conducted by [Trump's second term] FDA.
Could work
Let's assume that managing context well is a problem and that this kind of orchestration solves it. But I see another problem with agents:
When designing a system or a component we have ideas that form invariants. Sometimes the invariant is big, like a certain grand architecture, and sometimes it's small, like the selection of a data structure. Eventually, though, you want to add a feature that clashes with that invariant. At that point there are usually three choices:
* Don't add the feature. The invariant is a useful simplifying principle and it's more important than the feature; it will pay dividends in other ways.
* Add the feature inelegantly or inefficiently on top of the invariant. Hey, not every feature has to be elegant or efficient.
* Go back and change the invariant. You've just learnt something new that you hadn't considered and puts things in a new light, and it turns out there's a better approach.
Often, only one of these is right. Usually, one of these is very, very wrong, and with bad consequences.
But picking among them isn't a matter of context. It's a matter of judgment and the models - not the harnesses - get this judgment wrong far too often (they go with what they know - the "average" of their training - or they just don't get it). So often, in fact, that mistakes quickly accumulate and compound, and after a few bad decisions like this the codebase is unsalvageable. Today's models are just not good enough (yet) to create a complete sustainable product on their own. You just can't trust them to make wise decisions. Study after study and experiement after experiment show this.
Now, perhaps we make better judgment calls because we have context that the agent doesn't. But we can't really dump everything we know, from facts to lessons, and that pertains to every abstraction layer of the software, into documents. Even if we could, today's models couldn't handle them. So even if it is a matter of context, it is not something that can be solved with better context management. Having an audit trail is nice, but not if it's a trail of one bad decision after another.
They have knowledge about how programs can be structured in ways that improve overall maintainability, but little room to exercise that knowledge over the course of fulfilling the user’s request to add X feature.
They can make changes which lead to an improvement to the code base itself (without adding features); they just need to be asked explicitly to do so.
I’d argue the training objective should be tweaked. Before implementing, stop to consider the absolutely best way to approach it - potentially making other refactors to accommodate the feature first.
Hang in there, there will be a lot of slop to fix in contract work...
At this point it should be clear that Gas Town has done something we can evaluate the value of.
> has Gas Town shipping something in public that can be evaluated without all of this surrounding hype and blogposting?
No.
>At this point it should be clear that Gas Town has done something we can evaluate the value of.
I see this sentiment often, repeated a couple times in here, but I don't understand why on earth that would be the case. Gas Town was released a little over three months ago. It's an ongoing open-source experiment at the bleeding edge of vendor-agnostic multi-agent orchestration.
I was using gastown for fire-and-forget prototyping of larger projects. It was flaky and scorches tokens but it was able to get larger prototypes done than I could with a single instance of my daily river (claude) alone.
> Gas Town was released a little over three months ago
Should be plenty of time for a 100x zero-shot vibe god.
> Having spent six weeks or so using Gas Town across multiple simultaneous projects, I believe I can describe the shift concretely. The bottleneck migrates from coding speed to the rate at which you can generate ideas, write specifications, and validate outputs. You are no longer limited by how fast you can build. You are limited by how fast you can think.
Interesting:
> Kubernetes asks “Is it running?” Gas Town asks “Is it done?” Kubernetes optimizes for uptime. Gas Town optimizes for completion.
https://embracingenigmas.substack.com/p/exploring-gas-town
edit: was "is your imagination". Changed to fully match https://genius.com/Zombo-zombocom-lyrics
The real distinction is of scale - whether you want a REST endpoint or a fully functional word processor.
But real, actual, complex software is at least half spec (either explicit, or implicitly captured by its code), the question is, can LLMs specify software to the same degree with Gas Town, that you get something functioning?
You provided a quote from someone who seems to be an AI-boosting influencer who claimed to use it, but where's the output in the form of code we can look at, or in the form of an app someone can use today?
I'm not an AI-denier. I use LLMs and agentic coding. They increase my productivity.
...but there is still a very real problem with people claiming that some new way of using AI is earth shattering, and changes everything based on vague anecdotes that don't involve a tangible released output that they can point to.
>
Kubernetes asks “Is it running?” Gas Town asks “Is it done?” Kubernetes optimizes for uptime. Gas Town optimizes for completion.Sounds like the typical AI post slop.
Just because he's operating in the realm of smart nerds doesn't mean he is immune to the value-inverting effects of social media.
>
you can always fire it up yourself and see what its all aboutI imagine it doesn't run very cheaply.
>
that code is probably only ever supposed to be LLM maintained, not by people.But LLMs are trying to mimic people. So if confusion is the human response, what's to stop the llm from acting confused?
>Gas Town shipping something in public that can be evaluated without all of this surrounding hype and blogposting?
I am very confident in saying that most individuals successfully using multiple agents have done so by building their own harness.
So I slapped together my own Beads implementation (https://codeberg.org/mutablecc/dingles) over a day or two. Probably has bugs, and I'm sure race conditions if you tried to use with Gas Town, and likely does not scale. But it has the minimum functionality needed to create and track issues and sync them (locally and remotely, either via normal merge, or a dedicated ticket branch). No SQL, no extra features, just JSONL and Git. Threw a whole large software project at it, and the AI took to it like a duck to water, used it to make epics for the whole project, methodically worked through them all, dependencies first, across multiple context sessions. The paradigm of making tools the AI wants to use is clearly a winner.
I wound up building my own with Claude, I made it SQLite first, syncs to GitHub, can pull down from GitHub, and I added "Gates" to stopgap Claude or whatever agent from marking things complete if they've not been: compiled, unit tests run, or simple human testing / confirmation. The Gates concept improved my experience with Claude, all too often it says it finished something, when in fact it did not. Every task must have a gate, and gates must pass before you can close a task. Gates can be reused across tasks, so if "Run unit tests" is one gate, you can reuse it for every task, when it passes, it passes for that one task <-> gate combination.
Anyway, I'm happy for Beads, Gas Town not so much my wheelhouse on the other hand.
So now you have agents of type mayor, polecats, witnesses, deacons, dogs etc plus a slew of Unneeded constructs with incomprehensible names.
In one of the blog post for gas town I remember reading something by the author along the lines of « it’s super inefficient, but because you burn so many tokens, you still get what you want at the end! » clearly this is also the design philosophy behind this project, just (get your ai to) throw more random abstractions and more agent types until you feel like it kinda works, don’t bother asking yourself if they actually contribute anything.
This gave me the very clear feeling that most of the complexity of gas town is absolutely not needed and probably detrimental.
Ended up building my own thing that is 10x simpler, just a simple main agent you talk to, that can dispatch subagents, they all communicate, wake each other up and keep track of work through a simple CLI. No « refinery » or « wasteland » or « molecule » or « convoys » or « deacons » or …
I think Yegge's instincts that making a programmable / editable coordination layer (he calls this gas city) is a great idea. Gas town early days was definitely a wild experience in terms of needing to watch carefully lest your system be destroyed, and then I put that energy into OpenClaw - I'll probably spin up Gas City and see what it can do soon though. Very cool.
I think he's boxed himself in by continually layering more complexity on his approach, rather than stepping back and questioning the fundamentals or the overall direction.
All of the steps Gas Town or Gas City etc are taking are towards reducing human oversight and control. This is profoundly misguided! In a world of infinite cheap software it is precisely this human decision making and control that matters.
> There will be nothing like it. You are going to want to use Gas City.
No. I do not want to talk to the mayor of my software factory, as its cartoonish minions build an infinite mountain of slop. Unreviewable, both in terms of code and the finished product.
Instead, I want to precisely capture human ideas, have those ideas questioned, challenged, improved, and then I want to bring those ideas to life, keeping the human in the loop whenever they want. Neither Beads, Gas Town, nor Gas City or anything like them are required for that.
Seems like I'm back to obscurity.
:)
But this is genuinely cutting-edge, new paradigm of building software. Something that will iron it's kinks out, and potentially be the way of developing software in the new Era. That's worth some curious and exploratory discussion, rather than more comments about not being the "true way of software development".
(Sorry, was put off by the crab-pulling down discussion.)
It is pretty magical to go from brainstorming an idea in the evening, having ChatGPT Pro spit out a long list of beads to implement it, leaving it running over night in a totally empty repo and waking up to a mostly-implemented project.
I tried tracking down where those numbers came from and the sources were a bit sketchy. Can anybody who has used Gas Town confirm those numbers, or report their personal numbers?
In the end, it didn't feel worth it mostly because of high token overhead (inter agent communications, agents re reading same code, etc...) and synchronization / cooperation issues (who should do what).
What actually works for me and provides good results: multi step workflows with clearly defined steps and strong guidance for the agent.
This is a desirable end state for highly social but perhaps slightly sociopathic extroverts who want to spend all day talking even though they aren't talking to a person.
For anyone else, it's hard to imagine considering that a desirable way to spend eight hours a day.
I think we need to take a hard line with AI stuff like this, and put the onus on the creator to prove these ideas have merit.
But I think the point that Yegge doesn't address and that I had to discover for myself is: getting many agents working in parallel doing different things -- while cool and exciting (in an anthromorphic way) -- might not actually be solving the right problem. The bottleneck in development isn't workflow orchestration (what Gastown does) -- it's actually problem decomposition.
And Beads doesn't actually handle the decomposed problem well. I thought it did. But all it is is a task-graph system. Each bead is task, and agents can just pick up tasks to work on. That looks a lot like an SDE picking up a JIRA ticket right? But the problem is embedding just enough context in the task that the agent can do it right. But often it doesn't, so the agent has to guess missing context. And it often produces plausible code that is wrong.
Devolving a goal into the smaller slices is really where a lot of difficulty lies. You might say, oh, "I can just tell Claude to write Epics/Stories/Tasks, and it'll figure it out". Right? But without something grounding it like a spec, Claude doesn't do a good job. It won't know exactly how much context to provide to each independent agent.
What I have found useful is spec-driven development, especially of the opinionated variety that Kiro IDE offers. Kiro IDE is a middling Cursor, but an excellent spec generator -- in fact one of the best. It generates 3 specs at 3 levels of abstraction. It generates a Requirements doc in EARS/INCOSE (used at Rolls Royce and Boeing for reducing spec ambiguity), and then generate a Design doc (commonly done at FAANG), and... then generates a Task list, which cross-references the sections of the requirements/design.
This kind of spec hugely limits the degrees of freedom. The Requirements part of the spec actually captures intent, which is key. The Design part mocks interfaces, embeds glossaries, and also embeds PBTs (property-based tests using Hypothesis -- maybe eventually Hegel?) as gating mechanisms to check invariants. The Task list is what Beads is supposed to do -- but Beads can't do a good job because it doesn't have the other two specs.
I've deployed 4 products now using Kiro spec-driven dev (+ Simon Willison's tip "do red/green tdd") and they're running in prod and so far so good. They're pressure-tested using real data.
Spec-driven development isn't perfect but I feel its aim is the correct one -- to capture intentions, to reduce the degrees of freedom, and to constrain agents toward correctness. I tried using Claude Code's /plan mode but it's nowhere as rigorous, and there's still spec drift in the generated code. It doesn't pin down the problem sufficiently.
Gastown/Beads are solutions for workflow orchestration problem (which is exciting for tech bros), but at its core, it's not the most important problem. Problem decomposition is.
Otherwise you're just solving the wrong problem, fast.
I also simply detest how Gas Town is modeled fundamentally on an extractive and destructive metaphor, the 19th century factory. I want to live in a verdant software garden, not a dystopian industrialist hellscape.
In my view the StrongDM guys are on the right long-term path.