The functional paradigm is a bit uncomfortable at first, but it does make problem solving feel... different. I personally find OOP to be the most intuitive for large scale systems design, but that's just me.

Most models do not perform particularly well in Clojure, but OpenAI models fully utilize the power of the language. Subjectively, it kind of seems to match the personality. Data at https://gertlabs.com/rankings?provider=openai

> I personally find OOP to be the most intuitive for large scale systems design, but that's just me.

The beauty of Clojure shines through when you want to change something that cuts through a large part of a large project. If you are using mutable data, you may end up with many bugs from various pieces of code mutating objects inconsistently. With Clojure, if someone hands you data, you can't possibly break some distant piece of code by updating an object: it's just not possible because you only ever make fast, updated copies. The more complicated your codrbase gets, the more this benefit is realized.

I actually kind of think of it as an easier mechanism with similar outcomes to Rust's borrow checker. Only one piece of code ever owns the data so things end up much safer. However it is way easier to use IMHO because you just know that zero people own anything and everyone can read everything.

It also makes converting some code to be multi-threaded extremely easily and with some constraints guaranteeably correct.

Lots of dovetailing features neatly put together for both clarity and less bugs and more usable cores which are probably sitting idle.

Raw models aren't as effective with clojure as they are with typescript or python, but clojure has a superpower that most other languages don't have: the REPL! Specifically nREPL and the ecosystem around it.

An LLM is only as good as its feedback loop. If your LLM can actually test the code it writes, it's going to be much more effective. Static types are a form of feedback (if it can use the LSP), unit/integration tests are another.

Clojure has an exceptionally good repl. LLMs can eval any piece of any function. They can test out functions they aren't familiar with. They can fetch data, try out different arguments, try different approaches before committing to one. They can query a database (read-only connection, of course), look at the result, fetch data from an API, and stitch it all together. It can even hook into your running program and debug it from the inside out!!

It makes it so much more effective at using libraries or paradigms that it isn't trained on. In my experience, hooking an LLM up to the clojure repl lets it write WAY more complex stuff. I'm talking like 10x more complex programs with zero errors, cause it can literally try it out every little piece before putting it together. It's like watching a human programming. But like, really fast.

Sorry I get a little ranty when clojure + LLMs come up, because I don't think most people realize what they're missing out on. It's crazy stuff. It's also easy peasy if you use vscode. There's an extension called calva-backseat-driver that just hooks it all up for you. Gives copilot access to the repl, and I think it exposes an mcp if you want to give claude access too.

> I personally find OOP to be the most intuitive for large scale systems design, but that's just me.

Once you're more comfortable with it and want to try a typed functional programming language, I highly recommend checking OCaml (or SML, if you're into old school tech) and see how the Module Functors are applied, most software will look extremely over-engineered after you write a few functors. It's the feature I miss the most when coding in F# or Gleam, for instance.

Thanks for the link!

What would you say is missing from Clojure for large-scale OOP design? As I understand, Clojure gives you OOP a la carte. Objects (via maps/records/structs), polymorphic dispatch (via multimethods/protocols/case), types (via Malli/TypedClojure), inheritance (via derived, isa?, etc), some encapsulation (via defn-/^:private)...

Not sure if I'm reading this right, but the "success rate" table for OpenAI models shows Clojure near the bottom. And if I switch provider to Anthropic, success rate for most languages, including Clojure, goes up dramatically.

Rich Hickey's: Are We There Yet may be interesting to any one here: https://www.youtube.com/watch?v=ScEPu1cs4l0

I found this to be one of the more interesting talks I've watched.

Like you (I think) - I love functional languages.

But there's a problem I can't really figure out how to articulate where they reach a level where they stop "just working" imo. Maybe it's just me being too dumb.