That's got its downsides. Majorly, I feel like it's restrictive. Exception handling, especially asynchronous exception handling, can really disallow recovery from errors. Sure, when you have a straight data stream and you simply want to stop processing at an error, there's no data for the next stage and it never runs. But that greatly limits recovery from errors. If your reaction to sqrt(-1) is to "crash", ending the business part of the program and hopping straight to printing or logging or whatever for the error, it can be very difficult to, say, enlarge the domain. You might have the need to simply give some use-case specific value for negative numbers, and you can pretty simply do that in code, but it'll result in some coupling you don't want as now you have to test for being outside that domain. For sqrt the domain is simple to define, but for a lot of real-world logic, it isn't nearly that simple. You can, in some languages, trap the error. Dataflow machines often are not designed for that though, especially when dealing with copious asynchronicity.

That's where explicit error types, such as Maybe come in. You get to write your happy path as if errors didn't exist, but function composition uses a different set of operators than you usually would. In cases where you do want to recover from an error, you handle both paths then and there, as part of the happy path, and possibly don't even allow for an error beyond that. Most importantly, to get any value which is not an abstract concept of "maybe value" out, you need to handle the existence of both paths gracefully. That can be very nice, and very useful.

That being said, now that you're using explicit error types, you can escape the "happy path"/"error" dichotomy. No longer is there necessarily just a "no value". There can be a "no value, but". Or a "value, but". You can have several errors stack up in a chain of things which could be done in parallel and then collated as a result. You can even entirely give up on the concept of errors, since that's only a very special case. You can use it to encode non-determinism: each unit takes in a single value and processes it to several possible and different values. Combining them with the monadic bind operator, each unit outputting a list of values has those values concatenated at the end to the list of all outputs, then the next function runs for each of those values the set of outputs of them are joined for the next stage and so on. This can be very, very useful for things like traversing graphs. You can, as Haskell programmers often do, use it to haul around a bit of "state" in a technically pure manner (purity is in certain cases very desirable). Perhaps the most infamous use of applicatives and monads in programming is the Haskell IO Monad, which encodes no real paths at all. IO simply is a virus which latches on to everything you do with it, and getting out of IO requires touching the outside world in an impure manner, which in Haskell can "only" be done while evaluating the expression called "main", meaning that the expression called "main" becomes your only point of contact to the outside world and the only way to "unwrap" IO values. Once again, that is for (obsessive) purity reasons. Alternative applicatives even allow for things as simple as an alternative applicative functor based on zipping instead of nondeterminism.

It's a surprisingly varied technique, going far beyond simple railroads, and offers a neat way to write "only" the happy path while staying pure (allowing simple equational static analysis and unit testing without the need for mocks to re-establish purity). It also offers you many other functorial tools which are all linked by a specific composition behaviour. Further, other applicatives provide extra tools when you just need a functor which represents a specific way to combine two values.

Using alternative methods, you often run out of ways to extend existing code, create something completely unreadable yet somehow isomorphic, or you create something readable and extensible, but due to the lack of purity inherent in some exceptional business logic, it becomes very hard to test without extensive mocking. Toeing the line between purity, readability and extensibility can be done in many ways, but functors and especially monads are among the S-tier when it comes to it. That being said, Haskell can get a bit goofy with it, by no means is purity an absolute value to be always chased. I kind of wish more """mainstream""" languages contained better monadic toolboxes for those times when you see an issue and you know you could solve it better than what you have to otherwise do if you only had the tools for it.