The model I'm referring to is: "if it walks like software and quacks like software, it's software." Its writers and maintainers are AI. It has a commercial purpose. Its value comes from fulfilling its requirements.
There will be human handlers, including some who will occasionally have to dig through the dung and fix AI-idiosyncratic bugs. Fewer Ferrari designers, more Cuban 1956 Buick mechanics. It's an ugly approach, but the conjecture that, economically _or_ technically, there must be something fundamentally broken with it is very hand-wavy and dubious.
I agree that there will be less code-level innovation overall, just like artistic value production took a big hit when we went from portraits to photographs.
The requirements will have to come from somewhere, and they will have to be quite precise although probably higher-level than code written today. You're talking about just a new kind of software engineer. The kind of stuff described at https://martin.kleppmann.com/2025/12/08/ai-formal-verificati... (note the "the challenge will move to correctly defining the specification")
Unless what you have in mind is some sort of Moltbook add-on that the bots would write for themselves.
I'm talking software providing value to humans.
In this case, the $20k has been burned and produced zero value. Just look at the repo issues: looks like someone trying to get attention by spamming the issue tracker and opening hundreds of PRs. As an open source project, it’s a dead end.
So it doesn’t matter that this is “likely decrease in price over the next few years”? The value is zero, so even if superintelligence can produce this in an instant at zero cost in six months, the outcome is still worth zero.
You’re conflating production cost with value.
In terms of quality, to anyone using those coding agents, it should be clear by now that letting them run autonomously is a bad idea. That’s not going to change unless you believe LLMs will turn into something entirely different over time.
Note that what works with humans—social interaction creating innovation—doesn’t translate to LLM agents for a simple reason: they don’t have agency, shared goals, or accountability, so the social dynamics that generate innovation can’t form.