One thing I wonder: if you took the union of everyone’s vision for future of coding (in this community), what percentage of the current application space in programming would it cover? For me, my view of coding is heavily influenced by the applications I’ve personally worked on, which like many of you, is web UI + enterprise CRUD apps + compilers + games + functional programming. Subsequently a lot of the focus is on better databases, better UIs, better compiler toolchains, or more generally better “abstractions”, whatever that means. However I haven’t seen a strong presence in this community from e.g. hardware, cloud computing and data processing, data science, hard sciences (bio, physics, chem, …), supercomputing, simulation, security and privacy, blockchain/crypto, machine learning and AI, robotics, and so on. I partly mention those apps because in academia (at least Stanford), those are the problem spaces that academics are placing their bets on as the future of coding computer science. Of course, there’s a completely separate question of how much of the future is engineering vs. research, how much academia values engineering, etc. but I at least wanted to raise the initial question.

I come pretty definitely from the data science “world” / way of thinking. A lot of what computing is about is data transformation, operations, representation etc I feel. Whether it’s building applications, understanding systems, visualization, etc .. data is central. “Data science” also overlaps with / is a superset of supercomputing, simulation, and ML / AI.

Oh yeah, to be clear, I’m sure that there are several individuals who have direct or overlapping interest with what I mentioned. I’m referring more to my impression of the overall narrative of the community (as the sum of the things I see discussed).

It is very interesting you ask this question. In my "vision" of future of programming, I wonder how we can find some tools/languages which helps abstract very diverse kinds of programming artifacts : data, algorithms, persistence, infrastructures, scientific models, hardware, network connections, etc. I imagine that it would be greet to have a plateform that helps one design her own working abstractions for her problems at hand.

from my perspective, the important part is not necessarily what angle to approach the problem, but more defining what the problem really is and addressing it from a low level. Why is programming hard? What’s the reason that most people aren’t cracking open VS Code the way they might comfortably put together an Excel calculation?

I think, there is low , to no consensuses to what "the future" pf programming looks like, even and especially in this small group. Trying to frame something common could be an interesting exercise.

oh yeah for sure, but that's the fun bit - exploring everyone's perspective on where we're going!