AI coding agents are removing programming language barriers

Cursor and Claude Code were the asskicking I needed to finally get on the typescript bandwagon.

Strong typing drastically reduces hallucinations and wtf bugs that slip through code review.

So it’ll probably be the strongly typed languages that receive the proportionally greatest boost in popularity from LLM-assisted coding.

It’s good at matching patterns. If you can frame your problem so that it fits an existing pattern, good for you. It can show you good idiomatic code in small snippets. The more unusual and involved your problem is, the less useful it is. It cannot reason about the abstract moving parts in a way the human brain can.

From what I can tell, LLMs tend to hallucinate more with minor languages than with popular ones. I'm saying this as a Scala dev. I suspect most discussions about the LLM usefulness depend on the language they use. Maybe it's useful for JS devs.

I'm not sure, I have a custom config format that combines a CSV schema with processing instructions that I use for bank CSVs and Claude was able to generate a perfect one for a new bank only based on one config plus CSV and the new bank's CSV.

I'm optimistic that most new programming languages will only need a few "real" programmers to write a small amount of example code for the AI training to get started.

I’m having a good time with claude and Elm. The correctness seems to help a lot. I mean it still goes wonky some times, but I assume that’s the case with everyone.

More people who are not traditionally programmers are now writing code with AI assistance (great!) but this crowd seems unlikely to pick up Clojure, Haskell, OCaml etc... so I agree this is a development in favor of mainstream languages.

Ehhhh, a year ago I'd have agreed with you — LLMs were noticeably worse with Elixir than with bigger langs.

But I'm not noticing that anymore, at least with Elixir. The gap has closed; Claude 4 and Gemini 2.5 both write it excellently.

Otoh, if you wanted to create an entirely new programming language in 2025, you might be shit outta luck.

Recently I wrote a significant amount of zig first time in my life thanks to Claude Code. Is zig a mainstream language yet?

Wish I could go back to a time when I believed stuff like this

I used a LSP MCP tool for a LLM and was so far a bit underwhelmed. The problem is that LSP is designed for human consumption and LLMs have different constraints.

LLMs don't use the LSP exploratory to learn the API, you just give it to it as a context or MCP tool. LLMs are really good at pattern matching and wont make type errors as long as the type structure and constructs are simple.

If they are not simple it is not said that the LLM can solve and the user understand it.

I wish but the opposite seems to be coming - Haskell will have less support from coding AIs than mainstream languages.

I think people, who care about FP, should think about what is appealing about coding in natural language and is missing from programming in strongly typed FP languages such as Haskell and Lean. (After all, what attracted me to Haskell compared to Python was that the typechecking is relatively cheap thanks to type inference.)

I believe that natural language in coding has allure because it can express the outcome in fuzzy manner. I can "handwave" certain parts and the machine fills them out. I further believe, to make this work well with formal languages, we will need to use some kind of fuzzy logic, in which we specify the programs. (I particularly favor certain strong logics based on MTL but that aside.) Unfortunately, this line of research seems to have been pretty much abandoned in AI in favor of NNs.

> can be formally verified using well known algos

Is there any large formally verified project written in Haskell? The most well known ones are C (seL4 microkernel) and Coq+OCaml (CompCert verified C compiler).

We might see wider adoption of dependently typed languages like Agda. But limited corpus might become the limiting factor, I’m not sure how knowledge transfers as the languages get more different.

My experience is that each question I ask or point I make produces an answer that validates my thinking. After two or three iterations in a row in this style I end up distrusting everything.

I'm addition, I frequently tell it to ask clarifying questions. Those often reveal gaps in understanding or just plain misunderstanding that you can then bip in the bud before it has generated a million tokens.

I think this is more of a criticism of bash than of Gemini.

Also, I out-of-hand reject any criticism of an AI that specifies only the brand ("ChatGPT") and not the specific model version, settings, etc...

So, for example, Gemini 2.5 Pro (Jan 2025) with temperature 0.15 prompted with: "Write a short, idiomatic bash script that takes a file containing a list of directory names, changes to each one, runs a command, and then returns to the original working directory."

Spits out this:

    #!/bin/bash

    # A script to run a command in a list of directories.

    # Exit if the wrong number of arguments are provided.
    if [[ $# -lt 2 ]]; then
      echo "Usage: $0 <file_with_dirs> <command> [args...]" >&2
      exit 1
    fi

    DIR_FILE="$1"
    shift # The rest of the arguments ("$@") are now the command.

    # Ensure the directory list file exists and is readable.
    if [[ ! -r "$DIR_FILE" ]]; then
      echo "Error: Cannot read file '$DIR_FILE'" >&2
      exit 1
    fi

    # Read the file line by line.
    while IFS= read -r dir; do
      # Skip empty lines or non-existent directories.
      if [[ -n "$dir" && -d "$dir" ]]; then
        echo "==> Entering '$dir'..."
        # Run command in a subshell to keep the 'cd' local.
        # '&&' ensures the command only runs if 'cd' succeeds.
        (cd "$dir" && "$@")
        echo "<== Finished with '$dir'."
      else
        echo "--> Skipping invalid directory: '$dir'" >&2
      fi
    done < "$DIR_FILE"

    echo "All done."

Something that I found amusing, and again, is a criticism of bash instead of the AI, is that this fails to process the last line if it isn't terminated with a \n character.

PS: This is almost a one-liner in PowerShell, and works with or without the final terminator character:

    Push-Location
    Get-Content dirs.txt | cd -PassThru | Foreach-Object { echo "Hello from: $pwd" }
    Pop-Location

    pushd;gc dirs.txt|%{cd $_;"Hello from: $pwd"};popd