Comment by rerdavies
6 days ago
C++, Linux: write an audio processing loop for ALSA
reading audio input, processing it, and then outputting
audio on ALSA devices. Include code to open and close
the ALSA devices. Wrap the code up in a class. Use
Camelcase naming for C++ methods.
Skip the explanations.
``` Run it through grok:
https://grok.com/
When I ACTUALLY wrote that code the first time, it took me about two weeks to get it right. (horrifying documentation set, with inadequate sample code).
Typically, I'll edit code like this from top to bottom in order to get it to conform to my preferred coding idioms. And I will, of course, submit the code to the same sort of review that I would give my own first-cut code. And the way initialization parameters are passed in needs work. (A follow-on prompt would probably fix that). This is not a fire and forget sort of activity. Hard to say whether that code is right or not; but even if it's not, it would have saved me at least 12 days of effort.
Why did I choose that prompt? Because I have learned through use that AIs do will well with these sorts of coding tasks. I'm still learning, and making new discoveries every day. Today's discovery: it is SO easy to implement SQLLite database in C++ using an AI when you go at it the right way!
That rely heavily on your mental model of ALSA to write a prompt like that. For example, I believe macOS audio stack is node based like pipewire. For someone who is knowledgeable about the domain, it's easy enough to get some base output to review and iterate upon. Especially if there was enough training data or you constrain the output with the context. So there's no actual time saving because you have to take in account the time you spent learning about the domain.
That is why some people don't find AI that essential, if you have the knowledge, you already know how to find a specific part in the documentation to refresh your semantics and the time saved is minuscule.
Fer goodness sake. Eyeroll.
Run it through grok. I'd actually use VSCode Copilot Claude Sonnet 4. Grok is being used so that people who do not have access to a coding AI can see what they would get if they did.
I'd use that code as a starting point despite having zero knowledge of pipewire. And probably fill in other bits using AI as the need arises. "Read the audio data, process it, output it" is hardly deep domain knowledge.
Results with gemini
https://pastebin.com/6b4yhfYw
A 5 second search on DDG ("easyeffects") and a 10 second navigation on github.
https://github.com/wwmm/easyeffects/blob/master/src/plugin_b...
But that is GPL 3.0 and a lot of people want to use the license laundering LLM machine.
N.B. I already know about easyeffects from when I was seeking for a software equalizer
EDIT
Another 30 seconds exploration ("pipewire" on DDG, finding the main site, then goes on the documentation page, and the tutorial section).
https://docs.pipewire.org/audio-dsp-filter_8c-example.html
There's a lot of way to find truthful information without playing Russian roulette with an LLM.