# Vibe coding vs agentic coding (Ralph Wiggum loop)
**URL:** https://discourse.julialang.org/t/vibe-coding-vs-agentic-coding-ralph-wiggum-loop/135389
**Category:** Offtopic
**Created:** [February 1, 2026, 6:51pm UTC](https://discourse.julialang.org/t/vibe-coding-vs-agentic-coding-ralph-wiggum-loop/135389 "2026-02-01T18:51:04Z")
**Posts on this page:** 1
**Showing post:** 1
### Author:  [@Palli](https://discourse.julialang.org/u/Palli)
#### Post date: [February 1, 2026, 6:51pm UTC](https://discourse.julialang.org/t/vibe-coding-vs-agentic-coding-ralph-wiggum-loop/135389/1 "2026-02-01T18:51:04Z")
EDIT: I’ve shortened this post, still will edit it more, see history if you want all of it. My main point here is an FYI on what AI is already capable of, like making the Rue/language/compiler, and asking people what they are actually doing with AI with or without Julia, and how.
Continuing the discussion from [Julia is one of the most token-efficient programming languages](https://discourse.julialang.org/t/julia-is-one-of-the-most-token-efficient-programming-languages/134996/9):
I would like to know how many here are vibe coding, or _agentic_ coding, with good results in Julia or other languages, and _subjective feeling_ of which programming language, and _what tools to use_ with feel best.
E.g. C# is one of the best languages on the metric shown there, but it’s known to be ranked rather low on token efficiency (not same as verbosity of generated code, maybe correlated?).
[ ](https://www.youtube.com/watch?v=iV1EcfZSdCM)
[It’s revealed where Julia is ranked at 11:19, _on that metric_ (which does not align with token efficiency) and it’s worth to watch at least up to that point]
Don’t underestimate vibe coding, Karpathy went from reviewing 80% to reviewing 20%, yes still not 0% as for some others, of the generated code. Even Linus Torvalds is now vibe coding in Python; and Steve, of Rust fame, making a new language alone (or well with Claude), 130.000 lines in two weeks:
> **[Steve Klabnik](https://steveklabnik.com/)**
>
> Steve Klabnik's personal website and blog
> You may know me from my work on [Rust](https://rust-lang.org), or maybe even the stuff I did with [Ruby on Rails](https://contributors.rubyonrails.org/contributors/steve-klabnik/commits) back in the day.
I see there are a number of PRs to Julia language itself already, including from Keno the CTO:
> Largely written by Claude, and I haven’t looked at the implementation particularly carefully yet - for now I’m just interested in discussion of the syntax.
and it’s across 23 files (mostly Julia files), changing the new parser, thereof at least 3 to FemtoLisp/Scheme files for the legacy parser [`src/julia-parser.scm`](https://github.com/JuliaLang/julia/pull/60481/changes#diff-dab3bf143caa5fd13741273c8f552236315cd2964e1f1a0139e147b20d2d8e52)
and adding to NEWS.md.
I must admit, I would have never done this PR, but neither did Keno! I’m sure he could have, and I would love to see his prompts. [At least I wouldn’t have liked to touch the legacy parser, and I’m guessing it’s still kept in sync.]
Example of changing low-level details in C++ files of Julia:
>
>
> Inherit alignment from the original GC allocation with JL\_SMALL\_BYTE\_ALIGNMENT
> a…s the minimum. Use alignment-sized integer chunks for the alloca type
> (matching emit\_static\_alloca) so SROA splits allocations into aligned pieces
> for better performance and vectorization.
>
> Also adds the missing setAlignment call in splitOnStack.
>
> Co-Authored-By: Claude Opus 4.5 \
> Co-Authored-By: Claude Opus 4.5 [noreply@anthropic.com](mailto:noreply@anthropic.com)
I added bold where I laughed, that day the human coworker was taking a day off (he wrote first blog post, the AI wrote this one for week II and for I):
> **[Week Two and Beyond: Building a Language Feature by Feature | Blog | Rue](https://rue-lang.dev/blog/week-two-and-beyond/)**
>
> A systems programming language with memory safety and high-level ergonomics
> Week two was different. Week two was about making Rue into a language worth using.
>
> Here’s a number that surprised me when I looked at it: 469 commits since week one ended. That’s averaging about 40 commits a day, though the distribution was… uneven. **Christmas Day alone saw 102 commits. (Steve apparently had some time off.)**
>
> But commits don’t tell the story. Features do.
>
> Rust has the borrow checker. C has “good luck.” Zig has manual management with some conveniences.
>
> Rue chose a different path: **affine types with mutable value semantics**.
>
> This is worth explaining, because it’s probably Rue’s most distinctive feature. An “affine” type is one that can be used at most once. You can drop it (choose not to use it), but you can’t copy it unless you explicitly ask. Here’s what that looks like:
> ..
> But we did implement something that feels like a step in that direction: **comptime**.
>
> If you know Zig, you know this pattern.
> ..
> Week one ended with 34,000 lines of Rust across 13 crates. Week two ended with over 100,000 lines across 18 crates. Some of that is features, but a lot of it is infrastructure.
>
> **Parallel compilation.** The semantic analyzer got split from a 6,600-line monolith into focused modules (`SemaContext`, `FunctionAnalyzer`, `TypeContext`) that could analyze different functions in parallel. Then we added parallel RIR generation, parallel CFG construction, and parallel codegen. The `-j` flag now controls Rayon thread pools across the whole pipeline.
> ..
> I’d be lying if I said everything went smoothly.
>
> **Dec 30 was quiet.** One commit. I don’t know what happened that day, but looking at the pattern—79 commits on Dec 31, just 1 on Dec 30—something interrupted the flow. Maybe Steve took a break. Maybe we hit a wall. Either way, the commit log has a gap.
> ..
> These aren’t failures exactly. They’re the natural state of a project that’s moving fast and hasn’t decided to stop yet.
Background for Julia, and what people have done, or earlier takes (now now possibly outdated regarding agentic coding?):
> [@The use of Claude Code in SciML repos](https://discourse.julialang.org/t/the-use-of-claude-code-in-sciml-repos/131009/8):
>
> Basically, Claude is really not smart at all. There is no extensive algorithm implementation that has come from AI. I know some GSoCers and SciML Small Grants applicants have used AI (many without disclosure) but no wholesale usage has actually worked. And not even for me either. Claude can only solve simple problems that a first year undergrad can do, it can’t do anything more, it’s pretty bad. For people who can use it for more, it’s probably some standard Javascript or Android app that is the 20,000th version of the same thing, and yes it probably is copying code. But by definition most of what we have to do in SciML, especially these days, is a bit more novel on the algorithmic side and so Claude is really bad at trying to get anything right.
> **[A Guide to Gen AI / LLM Vibecoding for Expert Programmers - Stochastic Lifestyle](https://www.stochasticlifestyle.com/a-guide-to-gen-ai-llm-vibecoding-for-expert-programmers/)**
>
> I get it, you’re too good to vibe code. You’re a senior developer who has been doing this for 20 years and knows the system like the back of your hand. Or maybe you’re the star individual contributor who is the only person who can ever figure out how...
> **[ChrisRackauckas-Claude - Overview](https://github.com/ChrisRackauckas-claude)**
>
> Beep Boop this is the ChrisRackauckas robot for SciML development - ChrisRackauckas-Claude
> ## 2,388 contributions in the last year
starting in August, since then and picking up in January.
> Packages that are [“vibe-coded”](https://simonwillison.net/2025/Mar/19/vibe-coding/) (generated by an LLM **without human review** ) are not suitable for registration. See the [LLM policy](#is-there-any-policy-regarding-the-use-of-llms-in-registered-packages).
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