Fascinating reading the section about why the 1980s AI industry stumbled. The Moore’s law reasoning is that the early AI machines used custom processors which were commoditized. This time around we really are using general purpose compute though. Maybe there’s an analogy to open weight models but it’s a stretch.
Also the section on hype is informative, but I really see (ofc writing this from peak hype) a difference this time around. I fund $1000 in Claude Code Opus 4 for my top developers over the course of this month, and I really do expect to get >$1000 worth of more work output. Probably scales to $1000/dev before we hit diminishing returns.
Would be fun to write a 2029 version of this, with the assumption that we see a similar crash as happened in ~87 but in ~27. What would some possible stumbling reasons be this time around?
> I fund $1000 in Claude Code Opus 4 for my top developers over the course of this month, and I really do expect to get >$1000 worth of more work output. Probably scales to $1000/dev before we hit diminishing returns.
Two unknowns: the true non-VC-subsidized cost and the effects of increasing code output and maintenance of the code asymptotically. There are also second order effects of pipelines of senior engineers drying up and costing a lot. Chances are if widespread longterm adoption, we’ll see 90% of costs going to fixing 10% or 1% of problems that are expensive and difficult to avoid with LLMs and expensive to hire humans for. Theres always a new equilibrium.
On the former a recent post here “LLMs are cheap” I think, laid out a pretty compelling argument that API inference costs are in the right ballpark.
Regarding increasing maintenance, i’m finding that Claude code is just as good for working on CI/CD and unit testing as it is for new implementation. In fact, maintenance is more well defined and possibly being accelerated more than new features.
The point about pipeline of senior developers is a good one. I suppose depends on how elastic the demand side is. Will the demand for software go up asymptomatically as the cost drops? I think it will.
Also the section on hype is informative, but I really see (ofc writing this from peak hype) a difference this time around. I fund $1000 in Claude Code Opus 4 for my top developers over the course of this month, and I really do expect to get >$1000 worth of more work output. Probably scales to $1000/dev before we hit diminishing returns.
Would be fun to write a 2029 version of this, with the assumption that we see a similar crash as happened in ~87 but in ~27. What would some possible stumbling reasons be this time around?