Amazing stuff for sure. Looking at the example on page 59, though, I certainly see a description that contains sufficient information to implement against. I read this, and then I jump back into the tech spec that I'm writing to find:
(1) The product specification and use cases are so poorly defined that I need to anticipate the use cases, design a system that is general enough to accommodate them, and implement it in a way that is easily changeable to accommodate the future departures from my assumptions.
(2) As I do this, I need to consider the existing systems that I'm building on top of to ensure there is no regression when this feature rolls out
(3) I consider the other teams that are doing similar work and make judgement calls about whether to write independent systems that do one thing each, or to collaborate on a general-enough system with multiple team ownership.
(4) The tech that I use to implement this must be within the narrow slice of company-sanctioned tech.
(5) I weigh constant tradeoffs on speed to market, maintainability and ownership.
I'm sure there's more, but this stuff is _hard_. If autonomous driving for white collar work is coming, as put forth by comments here, I'd like to see indications that the actual hard part of the job is in jeopardy of being executed effectively.
Maybe I don't want to believe it, so I can't see it. I'll grant that. But I truly do not see it.
I'm mostly with you for the immediate future. So even if cars driving themselves to our offices to write code for 8 hours is in the cards I'd be curious to hear more tactical informed guesses. What would an intermediate stage look like?
Would the demand for junior developers evaporate if more experiences people can 10x daily LoC productivity? Or the other way around? Would languages with higher level abstractions (e.g. comparable to Scala if not Haskell) win or something like JS dominate?
I debated where in the whole thread, if anywhere, to comment that it is unfair to call it a dog. It is unfair to dogs, and misleading to any human trying to form useful abstractions about it. It lacks any of the dog's general intelligence and social skill which are integral to how we humans think about the sophistication of a dog and understand its adaptability and utility. To me, it is about as accurate as characterizing a mannequin as a monkey with mediocre fashion skills.
But, your post makes me realize that a job could be threatened by an AI just superficially emulating a worker, because its existence might exploit the social vulnerabilities of the workplace, in spite of having no general intelligence nor exploitative social skills of its own.
(1) The product specification and use cases are so poorly defined that I need to anticipate the use cases, design a system that is general enough to accommodate them, and implement it in a way that is easily changeable to accommodate the future departures from my assumptions.
(2) As I do this, I need to consider the existing systems that I'm building on top of to ensure there is no regression when this feature rolls out
(3) I consider the other teams that are doing similar work and make judgement calls about whether to write independent systems that do one thing each, or to collaborate on a general-enough system with multiple team ownership.
(4) The tech that I use to implement this must be within the narrow slice of company-sanctioned tech.
(5) I weigh constant tradeoffs on speed to market, maintainability and ownership.
I'm sure there's more, but this stuff is _hard_. If autonomous driving for white collar work is coming, as put forth by comments here, I'd like to see indications that the actual hard part of the job is in jeopardy of being executed effectively.
Maybe I don't want to believe it, so I can't see it. I'll grant that. But I truly do not see it.