I've honed a relatively decent flow that requires interaction from me for important parts (mostly) while making its own decisions at the not-important parts (mostly). This results in being able to send the agent off on an hours-long dev cycle and have relatively decent results after that need a few minor fixes. I think this is the best style for the current generation of AI
Welcome to the Wasteland: A Thousand Gas Towns
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Re: Welcome to the Wasteland: A Thousand Gas Towns
#92It's saddening to see folks here on HN direct so much contempt towards this. I have no intention of messing with Gas Town or Wasteland, but I think it's cool that folks like Steve with lots of money and time are using it to build stuff they find cool and interesting. I doubt these projects are the future of AI agent orchestration, but I do think they're probably going to help us collectively learn better how to work…
I see a lot of folks lamenting how Yegge has ignited a fire under leadership for egoless, factory worker style engineers. I don't think many would care much otherwise, but his post here is lamenting AI is not enough of a factory worker yet. On a site mostly populated by folks who put most of their lives into becoming skilled professionals, hearing "we think your work should be the kind of work we send to the cheapest…
What impact did he have?
Re: Welcome to the Wasteland: A Thousand Gas Towns
#93I really want to host a vibe coding competition and see what can actually be made with these systems. Like if we’re doing insane token spends, it better be in service of creating amazing stuff. Can we make an entirely new programming language? Can we make an OS?
The question is the degree to which they can produce original things.
Re: Welcome to the Wasteland: A Thousand Gas Towns
#94There are two bottlenecks in software. First is understanding what to build. Second is getting the details right. The best software is both the right software, and high quality. It’s bloody hard to do! So, we do requirements gathering, and try to get the details right (TDD, continuous delivery etc).. it’s surprising to see Gas Town do none of this and optimistically hope agents will converge on good software by just…
I think Gastown is truly special, but I wanted something more focused on learning as I think that's the real bottleneck. So I built AgenC to make it trivial to roll learnings back into your Claude.
Re: Welcome to the Wasteland: A Thousand Gas Towns
#95I really want to host a vibe coding competition and see what can actually be made with these systems. Like if we’re doing insane token spends, it better be in service of creating amazing stuff. Can we make an entirely new programming language? Can we make an OS?
Source: been watching both these guys closely, as I've been building my own agent factory focused on security + learning: https://github.com/mieubrisse/agenc
Re: Welcome to the Wasteland: A Thousand Gas Towns
#96Re: Welcome to the Wasteland: A Thousand Gas Towns
#97Re: Welcome to the Wasteland: A Thousand Gas Towns
#98It's saddening to see folks here on HN direct so much contempt towards this. I have no intention of messing with Gas Town or Wasteland, but I think it's cool that folks like Steve with lots of money and time are using it to build stuff they find cool and interesting. I doubt these projects are the future of AI agent orchestration, but I do think they're probably going to help us collectively learn better how to work…
If you can point to single product he has made through his "vibe-coding" that isn't for "vibe-coding," I think they would all relent.
Re: Welcome to the Wasteland: A Thousand Gas Towns
#99With LLM-based tools that inherently rely so much on the semantics of language, I wonder if there will be differences in code generated for the "wanted board" in the "Wasteland", compared to the "task list" in the "public square" or the "wish list" in the "Utopia".
Re: Welcome to the Wasteland: A Thousand Gas Towns
#100Earlier quoted context omitted.
Regardless of whether this particular project goes anywhere, it's at least very interesting that Yegge has discovered a way to make multi-agent setups work better. Giving them discrete personas ("you are a senior database engineer with 30 years of experience") and narrower scopes makes them much more effective. This was surprising to me but makes a lot of sense in retrospect.
The part that always struck me as weird about this stuff is that all of these "agents" with their "personas" are the same baseline LLMs with the same training ultimately, just told to basically pretend they're different. How far can that really get you? I'm not actually a database engineer with 30 years of experience. If somebody demanded that I pretend to be one, I guess I'd give it a shot, but I would expect any ac…
Why aren't the labs training models to pick a mantra appropriate to the task and do this themselves? "Huh, a database question. I am going to pretend I'm a database expert with lots of experience. OK, here we go!"