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Earlier quoted context omitted.
It probably could though. Or at least to the extent that declarative languages ever really work for real world problems. But iif you perfected it then it would also be the thing that actually kills software development. Because if I told you your whole job is now writing tests, you’d find another job.
Not that long ago that was a literal job for some software engineers. Whole departments of them.
But the only people who write code as bad as QA folks do are the DevOps people.
The paradox of SDETs is: QA makes less than dev, no matter what flavor. If you're good at poking holes in developer logic, and you can code yourself, there's a 40-60% raise for you if you can switch into security consulting, which takes the same foundational skills and some reading.
So there are at least two brain drains for "good coder in test", and we aren't even the most lucrative one.
I remember the Thinkgeek PC EZ-Bake Oven that fit into a 5.25" bay in your PC - fitting for 2004! https://hoaxes.org/af_database/permalink/pc_ez-bake_oven
And my favourite: Microsoft's Alpine Legend for Xbox 360 in 2009 that caused a stir because so many people actually wanted that game to be real. https://www.youtube.com/watch?v=ZUBQknWUEYU
The best part of April Fools jokes are that they capture the spirit of the time. I remember the Thinkgeek PC EZ-Bake Oven that fit into a 5.25" bay in your PC - fitting for 2004! https://hoaxes.org/af_database/permalink/pc_ez-bake_oven And my favourite: Microsoft's Alpine Legend for Xbox 360 in 2009 that caused a stir because so many people actually wanted that game to be real. https://www.youtube.com/watch?v=ZUBQknW…
To put things into perspective: DeepMind was founded in 2010, bought by goog in 2014, the year of this "prank". 11 years later and ... here we are. Also, a look at how our expectations / goalposts are moving. In 2010, one of the first "presentations" given at Deepmind by Hassabis, had a few slides on AGI (from the movie/documentary "The Thinking Game"): Quote from Shane Legg: "Our mission was to build an AGI - an art…
Consider that LLM->TTS example's human equivalent: when you're talking, you naturally emphasize certain words, and part of that is knowing not just what you want to say but why you want to say it. If you had a machine learning model where the speech module had insight into why the language model picked the words it has, and also vision so it knows who it's talking to to pick the right tone, and also the motor system had access to that too for gesturing, etc. then at that point you'd have a single AI that was indeed generally solving a large variety of tasks. We have a little bit of that for some domains but as it stands most of what we have are lots of specific models that we've got talking to each other and falling a little short of human level when the interface between them is incomplete.
Earlier quoted context omitted.
We're beyond that, now we can vibecode both the tests and the implementation.
It's always been possible to vibe code, it's just really fast now! I've done slipshod work full of bugs and security problems and thrown it over the fence hoping it will stand up long enough to be someone else's problems like 20 years ago!
They knew the future in 2014 and somehow wasted 10 years
Coding tests (if done correctly) is basically defining the behaviour of a black box API using running code. So it is easy to imagine an AI generating the black box from the tests/behaviour spec.