161–170 of 223 posts
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It’s discouraged to pass around structs of functions to replicate type classes in Gleam. Instead the preference is to not type class style patterns in your projects, favouring a concrete style instead.
Does that mean pass every needed function as a parameter? Or just don’t write generic functionality?
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> I fear LLMs have frozen programming language advancement and adoption for anything past 2021. Why would that be the case? Many models have knowledge cutoffs in this calendar year. Furthermore I’ve found that LLMs are generally pretty good at picking up new (or just obscure) languages as long as you have a few examples. As wide and varied as programming languages are, syntactically and ideologically they can only be…
There's a flywheel where programmers choose languages that LLMs already understand, but LLMs can only learn languages that programmers write a sufficient amount of code in. Because LLMs make it that much faster to develop software, any potential advantage you may get from adopting a very niche language is overshadowed by the fact that you can't use it with an LLM. This makes it that much harder for your new language…
i wrote my own language, LLMs have been able to work with it at a good level for over a year. I don't do anything special to enable that - just front load some key examples of the syntax before giving the task. I don't need to explain concepts like iteration.
Also llm's can work with languages with unconventional paradigms - kdb comes up fairly often in my world (array language but also written right to left).
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You can generate those conversions, most people do. But also, you shouldn’t think of it as writing the same type twice! If you couple your external API and your internal data model you are greatly restricting your domain modelling cability. Even in languages where JSON serialisation works with reflection I would recommend having a distinct definition for the internal and external structure so you can have the optimal…
>You can generate those conversions, most people do. Hi, what do people use to generate them, I found gserde (edit: and glerd-json)
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Yes, my point is that it's not a good experience.
I would be very interested in hearing about your experience writing Gleam and the problems you have! We regularly collect feedback and haven’t got problems reported here, so your feedback saying otherwise would be a useful data point.
Thank you for Gleam btw, I do really like the rest of the language.
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> Because LLMs make it that much faster to develop software I feel as though "facts" such as this are presented to me all the time on HN, but in my every day job I encounter devs creating piles of slop that even the most die-hard AI enthusiasts in my office can't stand and have started to push against. I know, I know "they just don't know how to use LLMs the right way!!!", but all of the better engineers I know, the…
This last week: * One developer tried to refactor a bunch of graph ql with an LLM and ended up checking in a bunch of completely broken code. Thankfully there were api tests. * One developer has an LLM making his PRs. He slurped up my unfinished branch, PRed it, and merged (!) it. One can only guess that the approved was also using an LLM. When I asked him why he did it, he was completely baffled and assured me he wo…
So the LLM was not told how to run the tests? Without that they cannot know if what they did works, and they are a bit like humans, they try something and then they need to check if that does the right thing. Without a test cycle you definitely don’t get a lot out of LLMs.
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There's a flywheel where programmers choose languages that LLMs already understand, but LLMs can only learn languages that programmers write a sufficient amount of code in. Because LLMs make it that much faster to develop software, any potential advantage you may get from adopting a very niche language is overshadowed by the fact that you can't use it with an LLM. This makes it that much harder for your new language…
> but LLMs can only learn languages that programmers write a sufficient amount of code in i wrote my own language, LLMs have been able to work with it at a good level for over a year. I don't do anything special to enable that - just front load some key examples of the syntax before giving the task. I don't need to explain concepts like iteration. Also llm's can work with languages with unconventional paradigms - kdb…
One thing im wondering with the LLM age we seem to be entering: is there value in picking up a language like this if theres not going to be a corpus of training data for an LLM to learn from? Id like to invest the time to learn Gleam, but I treat a language as a tool, or a means to an end. I feel like more and more I'm reaching for the tool to get the job done most easily, which are languages that LLMs seem to gel wi…
it seems semi intuitive to me that a typesafe, functional programming language with referential transparency would be ideal if you could decompose a program to small components and code those.
once you have a referentially transparent function with input/out tests you can spin on that forever until its solved and then be sure that it works.
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There are (some) guards available though? You could rewrite your example as: case x { n if x ... n if x > 10 -> ... n if x ... } Guards are a bit limited in that they cannot contain function calls, but that's a problem of the BEAM and not something Gleam could control.
Ah right, I remember now. > Guards are a bit limited in that they cannot contain function calls, I feel like that's not a small sacrifice. > but that's a problem of the BEAM and not something Gleam could control. Could Gleam desugar to a case expression like I wrote above?
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There's a flywheel where programmers choose languages that LLMs already understand, but LLMs can only learn languages that programmers write a sufficient amount of code in. Because LLMs make it that much faster to develop software, any potential advantage you may get from adopting a very niche language is overshadowed by the fact that you can't use it with an LLM. This makes it that much harder for your new language…
> Because LLMs make it that much faster to develop software I feel as though "facts" such as this are presented to me all the time on HN, but in my every day job I encounter devs creating piles of slop that even the most die-hard AI enthusiasts in my office can't stand and have started to push against. I know, I know "they just don't know how to use LLMs the right way!!!", but all of the better engineers I know, the…
I once toured a dairy farm that had been a pioneer test site for Lasix. Like all good hippies, everyone I knew shunned additives. This farmer claimed that Lasix wasn't a cheat because it only worked on really healthy cows. Best practices, and then add Lasix.
I nearly dropped out of Harvard's mathematics PhD program. Sticking around and finishing a thesis was the hardest thing I've ever done. It didn't take smarts. It took being the kind of person who doesn't die on a mountain.
There's a legendary Philadelphia cook who does pop-up meals, and keeps talking about the restaurant he plans to open. Professional chefs roll their eyes; being a good cook is a small part of the enterprise of engineering a successful restaurant.
(These are three stool legs. Neurodivergents have an advantage using AI. A stool is more stable when its legs are further apart. AI is an association engine. Humans find my sense of analogy tedious, but spreading out analogies defines more accurate planes in AI's association space. One doesn't simply "tell AI what to do".)
Learning how to use AI effectively was the hardest thing I've done recently, many brutal months of experiment, test projects with a dozen languages. One maintains several levels of planning, as if a corporate CTO. One tears apart all code in many iterations of code review. Just as a genius manager makes best use of flawed human talent, one learns to make best use of flawed AI talent.
My guess is that programmers who write bad code with AI were already writing bad code before AI.
Best practices, and then add AI.
Ruined by ligatures. Use them in your own private coding time, not when trying to communicate with others. It obfuscates rather than clarifies.