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3 days ago
1
Lifelong AI skeptic now turned LLM proponent here. I'm almost in the Adrian Cockroft/Joe Magerramov camp: for me today's LLMs are by far the most productivity-increasing tool for software development since the compiler. Yes I'm so old that I remember making software without a compiler. Reinforcing my non-koolaid-consuming cred: I've been using LLM tools to write programs I'd never have time to write, find bugs I'd have taken much longer to track down myself, understand the design of large complex codebases I'd have previously left as mystery-meat. The new tools are helping me work through the seemingly endless pile of stuff that always needed to be done but never got done.
Although the media narrative and previous HN discussions focus on developer layoffs supposedly due to AI adoption, I'm wondering about the inverse perspective. Since LLM tools improve software developer productivity significantly, why haven't we seen much better software? Why haven't we seen startups making new useful applications? Is there something about the wider business context that precludes improved productivity being applied to increase capacity and/or improve quality? After all when Walmart discovered how to optimize retail they didn't use that capability to make one super-efficient store. They built stores everywhere. Are we somehow stuck in some crappyness equilibrium where there's no overall benefit to improving software. Was that always the case but we never realized because by chance we had just enough developers to get by?
