A case for AI garbage collection + triage
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该讨论探讨了人工智能在开发社区中进行垃圾回收和分类的潜力。核心问题在于，人工智能在未经明确授权的情况下，对于删除内容往往持保守态度，从而将清理工作推回给人类开发者。此外，人工智能在没有明确指导的情况下，难以推断出工件的内在价值，这使得判断哪些内容值得保留变得困难。
I’m curious what people here think about this.
AI pipelines generate a growing amount of transient material and intermediate paper trail:
- VS Code / Codex threads
- ChatGPT chats
- document drafts
- plan files
- stale metadata
- intermediate image generations
- temporary outputs and side-effect files
AI is understandably conservative about deleting things without explicit authorization, so housekeeping gets pushed back onto its carbon-based counterpart (aka us). At the same time, AI is not always good at inferring the axiological value of an artifact - what is actually worth keeping - without guidance.
It seems like we need a core garbage-collection + triage mechanism.
Periodically, based on user-defined rules, the AI could collect likely-transient artifacts into a new kind of "recycle bin" or staging area. The user could then quickly triage them - keep, archive, promote, or discard.
The important distinction is that the AI would not decide what has value on its own. It would surface likely garbage and make the human decision cheap.
As AI makes it possible to generate artifacts at much greater scale, digital housekeeping probably needs to scale with it.
What do you think?