My workflow is to design, then use goal and loop prompts to RALPH a feature. At that point, usually there is a bunch of AI generated code that is generally correct but needs refinement, editing, testing, benchmarking, etc... That human-in-the-loop iterative step is the 'de-slop'. Would you prefer different phrasing, or is the trigger here the use of coding agents?
The biggest problem with obviously AI driven projects right now is that nobody knows how much expertise you have in this area (seems low given you don't know about systems that do very similar things), nor how carefully you thought about the problem and the implementation.
If I look at a project like Verus I know that experts thought about how to structure the system and it's concrete guarantees and semantics as well as the actual implementation.
So the result is that I trust Verus and I don't trust this.
You description of "design, then use goal and loop prompts to RALPH a feature" makes me even more convinced that this is slop because it sounds like you haven't thought deeply about every line of code and have delegated it to an AI that we all know makes mistakes. Thinking about the design is not really a substitute for thinking about the implementation.
People keep making AI OSS projects and expecting the same reaction as people had to OSS projects before AI, but pre-AI OSS came with a bunch of implicit promises about quality and effort and care that AI projects do not have.
I've interviewed several "I just read design docs and delegate all the actual thinking/analysis to the AI" engineers recently, and they are not grounded enough in reality to know when the AI is telling them something true or false and so confidently show me huge piles of code that purports to do things that I know are just nonsense. At some point I know these folks were good engineers, but they just drank too much of the kool aid.
To be clear, I have some of my own 100% slop projects where I have only vague ideas of what is going on beyond the high level design. But I have that currently put in a containment zone where I can easily verify the outputs or don't care about reliability (it's mostly UIs) and the scale of the damage they can do is minimal. Everything else, while basically still 100% AI generated at this point, is still reviewed and often repeatedly re-prompted to do precisely what I want the code to do, because if you let the coding agents make decisions for you, they still make bad decisions.
I'm not that commenter, but I feel like you wouldn't have to de-slop the project if it wasn't slop to begin with.
My workflow is to design, then use goal and loop prompts to RALPH a feature. At that point, usually there is a bunch of AI generated code that is generally correct but needs refinement, editing, testing, benchmarking, etc... That human-in-the-loop iterative step is the 'de-slop'. Would you prefer different phrasing, or is the trigger here the use of coding agents?
The biggest problem with obviously AI driven projects right now is that nobody knows how much expertise you have in this area (seems low given you don't know about systems that do very similar things), nor how carefully you thought about the problem and the implementation.
If I look at a project like Verus I know that experts thought about how to structure the system and it's concrete guarantees and semantics as well as the actual implementation.
So the result is that I trust Verus and I don't trust this.
You description of "design, then use goal and loop prompts to RALPH a feature" makes me even more convinced that this is slop because it sounds like you haven't thought deeply about every line of code and have delegated it to an AI that we all know makes mistakes. Thinking about the design is not really a substitute for thinking about the implementation.
People keep making AI OSS projects and expecting the same reaction as people had to OSS projects before AI, but pre-AI OSS came with a bunch of implicit promises about quality and effort and care that AI projects do not have.
I've interviewed several "I just read design docs and delegate all the actual thinking/analysis to the AI" engineers recently, and they are not grounded enough in reality to know when the AI is telling them something true or false and so confidently show me huge piles of code that purports to do things that I know are just nonsense. At some point I know these folks were good engineers, but they just drank too much of the kool aid.
To be clear, I have some of my own 100% slop projects where I have only vague ideas of what is going on beyond the high level design. But I have that currently put in a containment zone where I can easily verify the outputs or don't care about reliability (it's mostly UIs) and the scale of the damage they can do is minimal. Everything else, while basically still 100% AI generated at this point, is still reviewed and often repeatedly re-prompted to do precisely what I want the code to do, because if you let the coding agents make decisions for you, they still make bad decisions.
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