Vibe Coding Custom Nodes
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I apologize if this has been discussed before....
Has anyone had any luck in vibe coding new nodes (SNEX or C++)? If so, could you share anything that might either talk me out of even trying or, better still, point me in the right direction?
Chances are I would mostly be porting existing code into custom scriptnodes. There might be cases where I try to vibe code something from scratch...
Any advise would be greatly appreciated.
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@scottmire What experience do you have so far with agentic coding?
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TLDR At Bottom
It's pretty rough in my opinion.
(But also, take my opinion with a grain of salt, I get a bit serious when it comes to DSP).I'd say it depends what kind of quality (and efficiency) you are after.
AI can totally make a "working" C++ node very easy, but it won't be that efficient and will have all kinds of artefacts, and there are things that are straight up impossible to develop without investing in additional equipment.
So it comes down to what kind of effect/synth you're wanting to develop, and how much of a purist you are!(again, this is my opinion) The main issue with Agentic Coding (and especially vibecoding) is that it works by asking the AI to deliver an outcome. And you're then at the mercy of whatever method the AI decides to use, to fill in the gaps in your prompt.
Vagueness and lack of knowledge can be a problem, for example, ask it to create a waveshaper distortion effect. Sure, it will write one, and it'll probably be smart enough to suggest that it needs to be oversampled to reduce aliasing, or use a modern antialiasing technique such as ADAA.
Well, if that's all bundled implicitly into the vague prompt of "make a waveshaper distortion" then it will probably not devote much effort to deriving a good quality oversampler, it probably won't realize that a quick and dirty oversampler can audibly roll off your high end or give you ripples in the frequency response. And there is the tradeoff of latency to consider if you want to go linear phase... And designing the coefficients for an oversampler is an entire research task in its own right. Techniques like ADAA have tradeoffs depending on how exactly this waveshaper is going to be used in your final plugin. For example if this is in a plugin that already has latency, you could probably use a higher quality oversampler and compute it gradually over time, using the latency that the other parts of the plugin are creating as extra time to do processing, massively reducing CPU and allowing you to do a much higher quality result.But since the prompt was just "create a waveshaper distortion" the AI will likely just throw together the most quick and dirty method, and then hand that back and say "there you go, the waveshaper is done!". And you'll be none the wiser.
For some people this is good enough.
But you can imagine how worse this gets for actually complex DSP.
If we take analog modelling as an example, the current leading industry methods involve measuring DC and other electrical measurements from real real circuits under different conditions in order to get the datasets you need to replicate how components behave when they are actually inside a specific circuit, and to be able to compare your emulation to the real thing and find out why it differs.
But an Agent, if asked to analog model a piece of hardware, is unlikely to tell you anything about this process, and will just "imagine" the measurements and then give you back a program full of made up assumptions, claiming this is a good analog model.But the thing is, the program will totally work. And lots of people are happy with this, so really it depends.
If you're a hobbyist, it's probably going to give you a result better than you could've made without the AI.
Plus, the "simple" approach the AI takes means it's quite easy to debug, and you won't get challenging cross platform issues or with different hardware not supporting the approach.
And heck, if we are talking about purely creative sound design, then it doesn't matter: maybe that "roll off" in the highs and ripple, are part of "the sound" and people love it.So there are advantages. But the likelihood for "quality" DSP or low-artefacts is very low.
Since it just skips right to the end result instead of doing the months of research required to produce the kind of work a professional engineer would deliver.You can tell, I get frustrated with AI, but I'm actually not against using it for audio coding. I just wish it was better suited for the task, because I'm constantly arguing with it and having to give up and do it by hand
TLDR:
If you're writing stuff from scratch, you might run into problems down the line.
And you might need to end up learning all the DSP theory anyway, just so that you can tell the AI exactly what to do, or complain at it.On the other hand if you're just porting existing DSP to C++ Scriptnode Nodes, that will work excellently as long as you make sure to tell the AI agent to check that the CPU performance and Numerical Outcome of the DSP is the same as the original code. AI can still make transcription mistakes and end up taking shortcuts that remove optimizations "by accident". DSP is pretty fragile math, subtle changes can end up creating a different sound.
If you're going to do this, I recommend Codex:
https://chatgpt.com/codex/?utm_source=google&utm_medium=paid_search&c_id=24184341331&c_agid=198291088223&c_crid=822139703727&c_kwid=kwd-111182835&c_ims=&c_pms=9208073&c_nw=g&c_dvc=c&utm_campaign=24184341331&gad_source=1&gad_campaignid=24184341331&gbraid=0AAAAA-I0E5dTcdT4kjWBldRGjwm0ADIX7&gclid=Cj0KCQjwxKfWBhDkARIsAMKwkNbDY-zY7xKGSKfYxHXKVElvVZLUsP64_A6UMpZV2h8trCJ-l6ZoeIEaArGXEALw_wcB
