Sue SmithFeb 1

"The specification language gets more precise over time, because natural language is ambiguous and different models interpret the same prompt differently. You add more structure. You define exact function signatures. You specify return types. You nail down error handling behavior with enough precision that two different models should produce interchangeable output. The specification starts looking less like English prose and more like a programming language."

https://nesbitt.io/2026/01/30/will-ai-make-package-managers-redundant.html

Will AI Make Package Managers Redundant?

Following the prompt registry idea to its logical conclusion.

Andrew Nesbitt
Show threadSue SmithFeb 1
This is obviously a thought experiment but I can genuinely see a lot of these spec driven projects going this way, at some point you're trying to do something that would have been easier just using an existing high level programming language.
Show threadSue SmithFeb 1
Which might be an indictment of how badly we've taught these programming languages tbh lol.
Show threadSue SmithFeb 1
Honestly I think there is a lot to this, when I see some of the guides to using LLMs for folk without coding skills I think I could more easily just teach them to code. The mystification of coding is also a huge part of the appeal of this stuff for lots of people.
Show threadCybermatron

@sue There is a similar issue to this on the output side, where we are now seeing guidance on how to “tidy up” substandard GenAI output, which – if done well and applied consistently – takes significantly longer than creating the output yourself, once you have learned the necessary research and writing skills.

One of the things I’m telling my students to try to dissuade them from using GenAI for their assignments, is that “the math just isn’t mathing” and likely never will.

Feb 1 at 1:48pmWeb