Writing Lisp is AI resistant and I'm sad

How does traditional human use the REPL impact AIs ability to use one language over the other?

> Most Python development resembles Go or C++

How do you know this? Or what source are you using to arrive at this conclusion?

Again, super curious, if outright copyright theft _isn't_ the answer, why can't AI write lisp, then?

Contrary to the blog author I don't really believe this.

> How does traditional human use the REPL impact AIs ability to use one language over the other?

I don't think it does very much other than it's not the normal workflow for people vibe coding. Lisp doesn't require you to develop with an interactive mindset, but it enables it and it's very enjoyable if nothing else. Vibe coding workflow is prompt -> plan / code generation / edits -> maybe create and run some tests or run program from start -> repeat (sometimes the AI is in a loop until it hits some threshold, or has subagents, or is off on its own for long periods, and other complications). The layer of interactivity is with the AI tool, not with the program itself. You can use this workflow with Lisp just fine. Sometimes an MCP tool might offer some amount of interactivity to the AI at least, e.g. I've never tried to use an AI to do Blender work but I imagine there's an MCP that lets it do stuff in the running instance without having to constantly relaunch Blender. Blender has a Python API so the AI with no eyes might even be decent at some things nevertheless.

Others than the blog author report using something like https://github.com/cl-ai-project/cl-mcp that lets the AI develop more bottom-up style with the REPL, perhaps even configurable to use a shared REPL with the human, where programs evolve bit by bit without restarting. I trust their report that it works though I don't really have a desire to try it. If an AI barfs a bunch of changes across several Lisp files and I want to try them out without restarting, I can just reload the system (which reloads the necessary files) on my own separately. I also don't think representation in the training data is that important at least to frontier models because they express ever more general intelligence which lets them do more with less. This is further suggested by them being decently good at things like TLA+ and Lean proofs, which don't exactly have a lot of data either.

> How do you know this?

I've at times been a Java developer, a C++ developer, a Python developer, a PHP developer, a Lisp developer, and others. I read about and observe how people develop their programs and how commercial tooling advertises itself. Hot reloading tooling technically exists in a lot of places and gets you some of the way towards what Lisp provides out of the box but it's not used by the majority and usually comes with a lot of asterisks for where it will fail. I'd say one of the biggest differences with a lot of Python code vs. other langs is the prevalence of jupyter notebooks, but that's more similar to literate programming styles than Lisp styles, and unlike Lisp or literate programming (though I'm sure there's at least one exception) jupyter notebooks are typically used for tiny few-hundred-lines stuff at most, not large projects.

As an example of what's out of the box in Lisp, compile is a function you can call at runtime, not a separate tool, inspect is another function you can call at runtime that lets you view and modify data, and the mouthful update-instance-for-redefined-class method is part of the standard, so you have optional custom control over class redefinitions modifying existing objects rather than just "invalidating" them and/or forcing them to keep using older copies of methods forever, or filling new fields with default values (though this is usually a fine default), or like default Java debug mode in eclipse/intellij saying "woops, we can't reload this change, you have to restart!". I like to advertise JRebel because it doesn't have as many limitations and goes very far indeed by working with the whole Java ecosystem. e.g. XML files that under normal development are used to configure and initialize objects at program start time, changes to which require a restart, are monitored by JRebel and when changed trigger reinitialization without having to restart anything. That's the Lisp way, though in Lisp you'd have to setup your own XML file watchers for something like that. (Djula is a Django-inspired example for web template files, it does reloading by just checking file modification times. One could use something fancier on Linux like inotifywait. Though some Lisp developers just write their HTML with s-expressions and so changes to a page are just recompiling a function like normal development rather than saving a separate mostly-html template file. Lisp gives you many options of how you prefer to develop and deploy changes to a website. I like to ship a binary.)