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> [Our product] essentially involves enabling reinsurance brokers to create risk programmes and then market them to underwriters, all within our online platform
by _bxg1 7y ago
> [Our product] essentially involves enabling reinsurance brokers to create risk programmes and then market them to underwriters, all within our online platform. A risk programme has a fairly complex life cycle, and we model and digitalise all of the steps that professionals in the industry would traditionally have done on paper, which is of course far less efficient and far more expensive.
Sounds like an ideal use-case: complex, well-defined rules and procedures that must be modeled in a fool-proof way. I think the issue for most people who dream about using Haskell at work is that their use-case doesn't have these kinds of needs, and so the tradeoffs (hiring difficulty, third-party API support, etc.) just don't make sense.
- nextos 7y agoYes, it does look like an ideal use case. I really really love Haskell, but I wonder if it's a rational decision to use it in comparison to an eager ML (OCaml, F# or SML). Much simpler languages. The amount of language extensions plus laziness make the learning curve of Haskell quite steep! Still, I love this. Keep up the good work. I think that during the 2020s we will see a lot of efforts to move software errors to compile time with fancier type systems (dependent, linear, etc). I'm betting on a slightly different approach than Haskell, which I think is too complex and will never fit all use cases. I think the best approach is to have a great language to quickly build DSLs and formal verification methods (ranging from lightweight like property-based testing or type systems to heavyweight like abstract interpretation or theorem proving). So, essentially Racket (Lisp) + lots of formal techniques in a nice package.
- wespiser_2018 7y agoin the 2020s, I hope we can get learn out to make complex type systems simple to use!