AI coding is mid(okay) yes, my main point is people use it and it's a good line of business right now for them. They expected bigger break throughs like gpt-2 to 3 to 4, and that's not happening so they have to lean on the other aspects of the business more.
The fact it is mid is why they are really needing all the other lines of business to work. AKA selling tokens to AI apps the specialize in other mid products, and limit the snakeoil AI products that are littering the market ruining AI's image of being the new catch all solution.
I was a big user of IntelliSense and more heavily, IntelliJ, for most of my career. It truly seemed like magic back then. I recall telling a colleague who preferred Emacs that it felt like having an editor that could read your mind, and would joke that my tab key was getting worn out.
Then I discovered LLMs.
If you think IntelliSense is comparable to what LLMs can do, you really, really need to try giving an AI higher-level problems to solve. Throwaway example I gave in a similar thread a few weeks ago: https://news.ycombinator.com/item?id=44892576
I think a big part of simonw's shtick is trying to get people to give LLMs a proper try, and TBH that's what I end up doing a lot too, including right now! The problem is a "proper try" takes dedicated effort, because it's not obvious where the AI will excel or fail for your specific context, and people legitimately don't have enough time for that.
But once you figure it out, it feels like when you first discovered IntelliSense, except you already know IntelliSense, so it's like... IntelliSense raised to the power of IntelliSense.
The things is that languages that need intellisense that much are language that made it too easy to construct complex systems. For lisp and C, you can get autocompletion for free, and indexing to offer docs preview and signature can be done quite easily as well. There's also an incentive to keep things short and small.
Then you have Java and C# where you need a whole IDE if you're writing more than 10 lines. Because using anything brings the whole jungle with it.
Hmm, I think all languages, regardless of verbosity, could be better with IntelliSense. I mean, if the IDE can reliably predict what you intend to type based on the context, regardless of the complexity of the application involved, why not have it?
Seems like languages like Java and C# that encourage more complexity just aim to provide richer context to mine. Simple example, given an incomplete line like "TypeA foo = bar.", the IDE can very easily figure out you want "bar.getBlah(baz)" because getBlah has a return type of "TypeA" and "baz" is the only variable available in the scope. But to have all that context at that point requires a whole bunch of setup beforehand, like a fine-grained types supported by a rich type system and function signatures and so on, which incentivizes verbosity that usually scales with the complexity of the app.
So yes, that's a lot of verbosity, but also a lot of context. To your point, I feel like the philosophy of languages like Java and C# is deliberately based on providing enough context for sophisticated tooling like IntelliSense and IntelliJ.
Unfortunately, the languages came before such sophisticated tooling existed, and when good tools did exist they were expensive, and even with those tools now being widely and freely availble, many people still don't use them. (Plus, in retrospect, the language designs themselves genuinely turned out to be more complex than ideal in some aspects.)
So the current reputation of these languages encouraging undue complexity is probably due to their philosophies being grounded in sound reasoning but based on predictions that didn't quite pan out as expected.
AI coding is mid(okay) yes, my main point is people use it and it's a good line of business right now for them. They expected bigger break throughs like gpt-2 to 3 to 4, and that's not happening so they have to lean on the other aspects of the business more.
The fact it is mid is why they are really needing all the other lines of business to work. AKA selling tokens to AI apps the specialize in other mid products, and limit the snakeoil AI products that are littering the market ruining AI's image of being the new catch all solution.
I was a big user of IntelliSense and more heavily, IntelliJ, for most of my career. It truly seemed like magic back then. I recall telling a colleague who preferred Emacs that it felt like having an editor that could read your mind, and would joke that my tab key was getting worn out.
Then I discovered LLMs.
If you think IntelliSense is comparable to what LLMs can do, you really, really need to try giving an AI higher-level problems to solve. Throwaway example I gave in a similar thread a few weeks ago: https://news.ycombinator.com/item?id=44892576
I think a big part of simonw's shtick is trying to get people to give LLMs a proper try, and TBH that's what I end up doing a lot too, including right now! The problem is a "proper try" takes dedicated effort, because it's not obvious where the AI will excel or fail for your specific context, and people legitimately don't have enough time for that.
But once you figure it out, it feels like when you first discovered IntelliSense, except you already know IntelliSense, so it's like... IntelliSense raised to the power of IntelliSense.
The things is that languages that need intellisense that much are language that made it too easy to construct complex systems. For lisp and C, you can get autocompletion for free, and indexing to offer docs preview and signature can be done quite easily as well. There's also an incentive to keep things short and small.
Then you have Java and C# where you need a whole IDE if you're writing more than 10 lines. Because using anything brings the whole jungle with it.
Hmm, I think all languages, regardless of verbosity, could be better with IntelliSense. I mean, if the IDE can reliably predict what you intend to type based on the context, regardless of the complexity of the application involved, why not have it?
Seems like languages like Java and C# that encourage more complexity just aim to provide richer context to mine. Simple example, given an incomplete line like "TypeA foo = bar.", the IDE can very easily figure out you want "bar.getBlah(baz)" because getBlah has a return type of "TypeA" and "baz" is the only variable available in the scope. But to have all that context at that point requires a whole bunch of setup beforehand, like a fine-grained types supported by a rich type system and function signatures and so on, which incentivizes verbosity that usually scales with the complexity of the app.
So yes, that's a lot of verbosity, but also a lot of context. To your point, I feel like the philosophy of languages like Java and C# is deliberately based on providing enough context for sophisticated tooling like IntelliSense and IntelliJ.
Unfortunately, the languages came before such sophisticated tooling existed, and when good tools did exist they were expensive, and even with those tools now being widely and freely availble, many people still don't use them. (Plus, in retrospect, the language designs themselves genuinely turned out to be more complex than ideal in some aspects.)
So the current reputation of these languages encouraging undue complexity is probably due to their philosophies being grounded in sound reasoning but based on predictions that didn't quite pan out as expected.
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