It's true that a larger team, formed well in advance, is also less efficient per person, but they still can achieve more overall than small teams (sometimes).
This is why architecture legibility keeps getting more important. Clean interfaces, small modules, good naming. Not because the human needs it (they already know the codebase) but because the agent has to reconstruct understanding from scratch every single time.
Brooks was right that the conceptual structure is the hard part. We just never had to make it this explicit before.
[0] https://steve-yegge.medium.com/welcome-to-gas-town-4f25ee16d...
[1] https://www.anthropic.com/engineering/building-c-compiler
From my own experience, the problem is that AI slows down a lot as the scale grows. It's very quick to add extra views to a frontend, but struggles a lot more in making wide reaching refactors. So it's very easy to start a project, but after a while your progress slows significantly.
But given I've developed 2 pretty functional full stack applications in the last 3 months, which I definitely wouldn't have done without AI assistance, I think it's a fair assumption that lots of other people are doing the same. So there is almost certainly a lot more software being produced than there was before.
As an analogy: imagine if someone was bragging about using Gen AI to pump out romantasy smut novels that were spicy enough to get off to. Would you think they’re capable of producing the next Grapes of Wrath?
We were not awash in novel software before AI (say last decade in 2019).
I can only assume what you're really trying to say is "AI bad".
Don't take me wrong, I like Waymo but 2035 is probably realistic for the cities in more developing countries.
Enterprise (+API) usage of LLMs has continued to grow exponentially.
Precisely 0 projects are making it out any faster or (IMO more importantly) better. We have a PR review bot clogging up our PRs with fucking useless comments, rewriting the PR descriptions in obnoxious ways, that basically everyone hates and is getting shut off soon. From an actual productivity POV, people are just using it for a quick demo or proof of concept here and there before actually building the proper thing manually as before. And we have all the latest and greatest techniques, all the AGENTS.mds and tool calling and MCP integrations and unlimited access to every model we care to have access to and all the other bullshit that OpenAI et al are trying to shove on people.
It's not for a lack of trying, plenty of people are trying to make any part of it work, even if it's just to handle the truly small stuff that would take 5 minutes of work but is just tedious and small enough to be annoying to pick up. It's just not happening, even with extremely simple tasks (that IMO would be better off with a dedicated, small deterministic script) we still need human overview because it often shits the bed regardless, so the effort required to review things is equal or often greater than just doing the damn ticket yourself.
My personal favorite failure is when the transcript bots just... Don't transcript random chunks of the conversation, which can often lead to more confusion than if we just didn't have anything transcribed. We've turned off the transcript and summarization bots, because we've found 9/10 times they're actively detrimental to our planning and lead us down bad paths.
Devs, even conservative ones, like it. I’ve built a lot of tooling in my life, but i never had the experience that devs reach out to me that fast because it is ‘broken’. (Expired token or a bug for huge MRs)
I can’t imagine the number being economically meaningful now.
And yet, from https://news.ycombinator.com/item?id=47048599
> One of the tips, especially when using Claude Code, is explictly ask to create a "tasks", and also use subagents. For example I want to validate and re-structure all my documentation - I would ask it to create a task to research state of my docs, then after create a task per specific detail, then create a task to re-validate quality after it has finished task.
Which sounds pretty much the same as how work is broken down and handed out to humans.