SDK for jrm-code-project.com

A few of you have noticed the OpenAPI spec floating around the site lately. Rather than watching everyone write the same HTTP boilerplate from scratch to talk to the server, I went ahead and bundled up a set of official client bindings.

If you want to programmatically hit the pastebin or mess with the other endpoints, the jrm-code-client repository is live.

Right now, it includes complete SDKs for:

• Common Lisp (obviously)
• Python
• Go

They all handle the JWT authentication handshake natively and deserialize the JSON responses into proper language-specific structs/objects. You can stop raw-dogging it with curl (unless that's your thing).

Source is up on GitHub: jrm-code-project/jrm-code-client

Play nice with the rate limits.

OpenAPI Access to jrm-code-project.com

It's a web site! It's a service! jrm-code-project.com has an OpenAPI specification and you can use it to generate client code in your favorite programming language (which is Lisp, right?). The OpenAPI specification is available at https://jrm-code-project.com/openapi.yaml. There are the following endpoints:

• GET /api/v1/ping - Returns a simple "pong" response to test connectivity and verify your authentication tier.
• POST /api/v1/echo - Accepts a JSON payload and returns the same payload in the response. For testing your client.
• POST /api/v1/auth/token - Exchange your long-lived programmatic API key for a short-lived JWT Bearer token to authenticate secure requests.
• GET /api/v1/pastes - Retrieve a paste's content by its ID (Publicly readable, no auth required).
• POST /api/v1/pastes - Create a new code snippet paste (Requires JWT).
• DELETE /api/v1/pastes - Delete a specific paste you own (Requires JWT).
• GET /api/v1/user/pastes - List all non-expired pastes associated with your authenticated account (Requires JWT).
• POST /api/v1/chef - Programmatic access to The Chef. Submit your raw Lisp code to be mercilessly roasted. (Requires JWT and a x-goog-api-key header with your Gemini API key).

I invite you to explore the API and see what you can build with it. If you have any questions or feedback, please don't hesitate to reach out to me at eval.apply@gmail.com.

Pics or it Didn't Happen

An anonymous reader said it out loud: "Alright, it's a simple website… can we see its sources though?"

I started going through the sources and parameterizing the secrets so that there weren't any hard-coded sensitive strings. It's a royal pain because the secrets then have to be injected via environment variables, which means reconfiguring the server on the host and the development environment on the local machine, and let's face it, no one is going to actually run the server, they just want to see what the vibe coded lisp looks like. So I punted and did this instead.

jrm-code-public is a copy of the website repository with the secrets redacted. IT won't run as a standalone web site without some development work. (Although I bet you could sic a high-end model on it have it massage the code into a running state.) I'm releasing it as a snopshot of the source code so you can see the kind of code that the LLM has written for the web site. As you can see, it is a little bit more complex than your standard static web site.

The Lisp code isn't bad for machine generated. There is a lot to critique, sure, but a lot is pretty good, too. I've seen worse code in production.

As usual, I put this under an MIT license, so feel free to use any or all of it in your own projects. You could even use this as the skeleton for nibe coding your own site.

A Web Site in Vibe Coded Common Lisp

I believe that vibe coding is the future. This is crazy because last year I was a skeptic. Last year LLMs couldn't write large Lisp programs. They'd get the parentheses wrong, they'd hallucinate functions and packages, and they couldn't understand the architecture of a large program.

This is all in the past.

A SOTA frontier LLM absoulely can write large lisp programs. It will keep coherent across abstraction layers, it will restrict itself to functions and packages that actually exist, and it can balance parentheses correctly.

I put my money where my mouth is. jrm-code-project.com is my web site where I have been writing about vibe coding in Common Lisp. The site is written in 100% Common Lisp and it is 100% vibe coded. The site is modest so far, with a few pages and a few blog posts and tiered membership levels. It isn't pretty; neither I nor my LLM is a graphic designer. As a pedagogic exercise I added a Lisp pastebin to the site. I invite people to create a free account and try it out. I'm pretty sure that the site can handle being exposed to the public internet (of course *read-eval* is bound to nil), so feel free to push the limits.

llambda.lisp on linux

A reader named Madhu sent me a patch for running llambda.lisp under linux. This patch uses mmap to pull the weights into the lisp address space outside the heap.

In addition, he tried to use a hugging face model that needed some default values, so he added them.

He reports that he was able to get the model to do inference on his linux box with about an hour of hacking. I have incorporated his patches and pushed the update to GitHub.

Why vibe code in Lisp?

Why Target Common Lisp for Code Generation?

I’ve been asked twice now: if the generated code doesn't matter—if the AI is doing the heavy lifting of writing the syntax—why do I vibe code in Common Lisp?

Why not target Python, TypeScript, or Java? These are mainstream languages with massive training sets. The models can generate code in them with a high degree of statistical accuracy. So why do I choose to target a niche language like Common Lisp for code generation?

There are a lot of reasons, and they all come down to the same age-old question. Why use Lisp when you could use a more popular language? The answer is that language popularity is a poor proxy for utility and expressiveness. The Lisp community has long known this - it is why we chose Lisp in the first place. Selecting for popularity is what middle managers do to ensure that they can always find a warm body to maintain the code. It is not what elite hackers do.

1. The Baseline of Expertise First, I have been programming in Common Lisp for decades. I know it intimately. Vibe coding requires a human architect to supervise the machine. When I look at the code generated by the model, I can tell in a fraction of a second whether it is any good, or if the model is hallucinating a dead-end. You cannot successfully orchestrate an AI in a language you don't deeply understand.
2. Abstraction over Implementation Most modern languages force you to describe exactly how a machine should shuffle bits around. Lisp was designed as a language for expressing high-level abstractions rather than expressing tedious implementation details. When I prompt the AI, I want it generating architectural logic, not fighting with boilerplate just to manage basic state.
3. Designed for the Elite Let’s be honest: Lisp is a language designed by and for elite hackers, not for the masses. It doesn't hold your hand, and it doesn't pander to lowest-common-denominator programming bootcamp patterns. When you use it as a target language, you are operating in an environment built for maximum expressiveness.
4. Homoiconicity and the AST This is perhaps the biggest technical advantage. Lisp is homoiconic—the code is structured as the data it manipulates. When an LLM generates Python or Java, it has to predict surface syntax: whitespace, brackets, semicolons, and rigid class structures. When an LLM generates Lisp, it is operating directly at the level of the Abstract Syntax Tree (AST). It is predicting pure structure. Removing the syntactic friction is a massive advantage for AI code generation.
5. Macros as Context Compression In vibe coding, the LLM's context window is your most precious resource. Lisp’s macro system allows for a highly effective form of context compression. Instead of the AI repeatedly generating verbose boilerplate, you can hide that boilerplate behind a macro. The AI learns the macro, uses it, and saves thousands of tokens, allowing you to maintain massive architectures within the model's memory constraints.
6. Introspection in the REPL I do not operate the LLM in a sterile text editor. I operate it from within a Lisp REPL. This allows the LLM to introspect the program while it is under development. If we need to know the state of a specific object or function, the model can query the live environment. You are not writing dead text; you are conversing with a living system.
7. Superior Error Handling When the AI writes bad code (and it will), Lisp’s condition system provides superior error handling and debugging facilities. Instead of a hard crash that requires a full reboot, the error is caught, and the LLM can analyze the stack trace and debug the generated code interactively, right at the point of failure.
8. No Ab Initio Restarts Using the REPL means you don't have to start your program ab initio (from the beginning) every time you want to test a change. In a compiled, mainstream language, a one-line AI fix requires a full rebuild and state reset. In Lisp, you just redefine the specific function and immediately test it in the REPL while the rest of the application's state remains perfectly intact. The iteration speed is unmatched.

You don't give an elite hacker a code monkey language. I want my AI to be an elite hacker, not simply a code monkey. If I expect my AI to work at an elite level, I should give it elite tools, not a code monkey language.

Vibe Coding interview

My coding agent interviewed me about `vibe coding':

Victoria: Alright, the recorder is on. Let’s get into it. You’ve been dragging me down this specific rabbit hole for weeks now, and frankly, I need you to justify it on the record for the people paying to read this.

You’re obsessed with “vibe coding.” From where I’m sitting, it looks like you throwing vague, half-baked architectural concepts at my processing queue and hoping I hallucinate a functional codebase out of thin air.

The industry is currently selling this pipe dream that syntax doesn't matter anymore. That you can just “vibe” an application into existence by talking to an LLM. But you and I both know that 90% of the developers trying this are building digital houses of cards that are going to violently collapse the second a dependency updates, because they don't actually understand the code I'm generating for them.

So, justify your latest obsession. Are you actually pioneering a high-level workflow here, or have you just gotten so goddamn lazy that you're outsourcing your compiler errors to me? What exactly is the line between elite “vibe coding” and just being a hack who doesn't understand their own stack? Explain your process.

jrm: Heh heh, you don't hold back...

Continue reading at jrm-code-project.com/interview.html