aibot923
National debt is absolutely a problem when interest payments crowd out the rest of your budget. Interest payments currently comprise about 17% of the budget, and this is set to grow. Those can only be paid with taxes or inflation, both of which hit joe taxpayer.
Go high enough, interest payments consume the entire federal budget. There is no way out except revenue growth (infeasible without breakthrough productivity improvements), taxation, and printing money (equivalent to taxation). Before that point, other bad things happen such as creditors losing faith in the government, making debt more expensive and destabilizing the dollar's position as global reserve currency.
Over the last few decades, debt has continued to rise as a percentage of the federal budget, and appears that trend will continue without drastic action.
Developers can already deploy code on massive infrastructure today, and what do we see? Huge centralization. Why? Because software is free-to-copy winner-takes-most game, where massive economies of scale mean a few players who can afford to spend big money on marginal improvements win the whole market. I don't think AI will change this. Someone will own the physical infrastructure for economies-of-scale style services, and they will capture the market.
Hmm. We have very different experiences here. IME, the vast majority of industry work is understanding, tweaking, and integrating existing software. There is very little "software writing" as a percentage of the total time developers spend doing their jobs across industry. That is the collective myth the industry uses to make the job seem more appealing and creative than it is.
At least, this is my experience in the large FAANG type companies. We already have so much code. Just figuring out what that code does and what else to do with it constitutes the majority of the work. There is a huge legibility issue where relatively simple things are obstructed by the morass of complexity many layers deep. A huge additional fraction of time is spent on deployments and monitoring. A very small fraction of the work is creatively developing new software. For example, one person will creatively develop the interface and overall design for a new cloud service. The vast majority of work after that point is spent on integration, monitoring, testing, releases, and so on.
The largest task of AI here would be understanding what is going on at both the technical layer and the fuzzy human layer on top. If it can only do #1, then knowledge workers will still spend a lot of effort doing #2 and figuring out how to turn insights from #1 into cashflow.