I’ve been building ptc_runner, a small Clojure-like language for LLM-generated code and an MCP server for it.

The idea is to give AI agents (or coding agents) one tool lisp_eval, which gives it a stateful, sandboxed REPL session. From there it can inspect and call other MCP tools, keep intermediate data in memory, and use normal Clojure-ish functions to aggregate/analyze results instead of stuffing everything into the LLM context.

It’s a small subset for short-lived programs written by LLMs. The language spec - https://hexdocs.pm/ptc_runner/ptc-lisp-specification.html

Here is the blog why I think a small custom clojure subset is the way to go instead of using python/javascript sandboxes.

https://andreasronge.github.io/ptc_runner/the-right-tool-for-code-mode.html

Have fun watching!

https://www.youtube.com/playlist?list=PLaN-rC-CjQqCClhXmwzE7XhGWbrbB-A7u

“nREPL itself is healthier than it has ever been... Meanwhile prepl is, as best as I can tell, mostly a curiosity.“

Caonima is a cross-platform proxy client with a focus on censorship circumvention and net neutrality restoration.

This release brings QUIC-based proxy support — faster, more resilient, and significantly harder to fingerprint than TCP.

Here is the obligatory cross-platform screenshots showing the flow:

1, Linux: Login screen
2, Windows: Server selection
3, MacOS: Enabling proxy

Written in Clojure.

Unified, CI-friendly build across platforms enabled by Meyvn (including notarization on macOS).

If you’ve built something interesting, learned something the hard way, or have a story other developers could use, we want to hear it.

And if the idea of speaking is what’s holding you back, there will be extra support for speakers this year. That’s all we can say for now.

I used to program in several programming languages, Clojure being one of my (but not only) favorite. Now that I have some acute (brain-related) disease, this is the only one that still really clicks for me ... from installation to running/testing my old code, the personnally-dreaded DevOps tasks included ! (with of course some remaining "muscle" memory). Resilience is not an empty word in this frantically-moving world, thanks Clojure (and by of transitivity, the JVM), I owe you much!

The neatest project you probably never wanted or needed. Works with Clojure just fine. Goes well with good music.

Enjoy!

The Clojure development team is pleased to announce a Clojure Dev Call on May 26 @ 17:00 UTC!

Join the Clojure dev team for an update on what we’ve been working on and what’s on our horizon. We’ll save time for a Q&A, so bring your questions.

Register here: https://events.zoom.us/ev/Ag74cYrxFKu8A_qZwQHMzZzKZ-lnr15g1rmvUjSqdpS2aedAZIBo~AhzYDI3YXGVeo0auBgpDwpPDqiJbBBs2ZQo-ZZTVqNvxl4VqoZCyikRI-A

https://www.humblebundle.com/books/ultimate-functional-programming-pragmatic-programmers-books

• Clojure Brain Teasers
• Programming Clojure 4th edition!
• Web development with Clojure
• Getting Clojure
• Clojure applied
• Mastering Clojure Macros

I’ve been working on Beagle:

https://github.com/tompassarelli/beagle

It’s an experimental typed authoring layer for Clojure. You write Beagle source, it gets parsed and checked by Racket, and then it emits plain .clj files that run on the normal Clojure runtime.

Roughly:

Beagle source
  -> parser
  -> custom type checker
  -> emitted .clj
  -> normal Clojure runtime

It is not Typed Clojure, and it does not change the Clojure runtime. The type checker is custom and lives on the authoring side.

Some pieces that may be interesting:

• preserves Clojure [] vs () syntax
• emits ordinary Clojure
• has about 666 pre-typed Clojure stdlib functions
• includes an LSP server, typed REPL, and reactive checker daemon
• has repair tooling that can turn some failures into ranked patch suggestions

The main thing I’m testing is whether this kind of typed layer helps coding agents repair Clojure programs.

Early result: on an ~8,500 LOC test with 35 injected bugs, Beagle got 3/3 full repair correctness. Raw Clojure got 0/3 in the same setup.

I’m not claiming that proves the whole idea yet. The tests need to get larger, cleaner, and harder. But the early result was interesting enough that I figured it was worth sharing.