@davidgerard@circumstances.run @xgranade@wandering.shop @mttaggart@infosec.exchange @cwebber@social.coopIncidentally, as a bit of an aside since it touches on my own CS research a bit:
high output generation with review
seems to be load bearing in the push to widely deploy vibe coding or agentic coding or whatever they're calling it today. "It's OK to have LLMs produce code as long as there is thorough human review" is an argument I've seen trotted out countless times, but should not be given any credence.
I am here to tell you that this is a misapprehension that ignores the substantive difference between:
(a) Competent human beings producing X by, in part, avoiding producing Y
(b) Less-competent human beings with machine help producing Y, catching that Y is bad with a test or review, and lather-rinse-repeating until X is produced.
If you like, (a) is gradient ascent while (b) is trial-and-error (generate-and-test, or hillclimbing, to use the GOFAI jargon). Everyone who works with such algorithms knows that (a) is many orders of magnitude faster, more reliable, and more robust than (b) when a good gradient is available. Most of machine learning is based on this observation! When it comes to producing code, competent human software developers provide such a gradient (that's what we mean when we think of them as "competent").