I wish there were a better bridge from spreadsheets to full-blown applications, though. I imagine some kind of tool where you have your prototype spreadsheet and click "Export to application", and a wizard walks you through naming your columns, which then get exported as named arrays/matrices in a declarative/functional dataflow language. You name your formulas, which become named functions. You mark some of the cells as inputs and others as outputs, which then kicks you over to a GUI wizard for laying out the end-user UI. Cells that aren't formulas, inputs, or outputs become named constants in your program. Maybe there's JSON REST, Protobuf gRPC, and Bloomberg market data API integration for inputs and outputs.

I've spent the past 10 years maintaining and improving a finance-centric lazily-evaluated dataflow language with integrated distributed NoSQL database for a Fortune 500 financial services company. My understanding is that most of our competitors use Excel where we use our language/database. Some of our competitors have hired away some of our developers to explicitly write more modern clones of our system. One competitor's clone uses Python with function decorators that inspect the function's AST and transform it into a reactive dataflow language, though I imagine it's very frustrating to write something that looks like Python with very non-Pythonic evaluation semantics. I think starting with something like Haskell or Prolog would be less jarring.

My wife does finance/accounting for another large multinational, and I see the appeal and power of both Excel and our system. I wish there were some easier way to migrate from spreadsheets to more scalable and maintainable systems. (And, I suppose, there's some utility in bidirectional migration.)