Comment on Linus Torvalds to critics of AI coding in Linux: "Fork it. Or just walk away."

• iocase@lemmy.zip ⁨1⁩ ⁨week⁩ ago

  I appreciate the feedback regarding verbosity, and I think that concern is both understandable and illustrative of the broader discussion we’re having. However, I would suggest that your response actually reinforces the systemic dynamics that I’m attempting to highlight. Specifically, while you are entirely correct that an individual response can simply be closed or ignored if it fails to meet project standards, that observation does not necessarily scale in environments where the overall volume of incoming communication increases by one or two orders of magnitude.

  To elaborate, the issue isn’t that any individual AI-generated pull request, issue report, or discussion comment is impossible to dismiss. On the contrary, as you’ve demonstrated, a maintainer can absolutely review a single submission, determine that it lacks sufficient value, and reject it accordingly. The challenge emerges not at the level of individual interactions but at the aggregate systems level, where review capacity becomes the scarce resource rather than code generation capacity.

  For example, if one contributor submits an unnecessarily verbose pull request, the cost of evaluating that submission may be relatively modest. If ten contributors do the same, the cost increases proportionally. If one hundred contributors begin submitting plausible-looking but low-value AI-assisted changes every week, each of which requires even a few minutes of human evaluation before being confidently rejected, the cumulative impact becomes substantially more significant. This isn’t because any individual submission is uniquely problematic but because the total review burden scales with submission volume while maintainer attention does not.

  From a queueing theory perspective, this creates an interesting imbalance. Human review throughput remains relatively fixed, whereas AI-assisted content generation dramatically increases the arrival rate of new work. Once the arrival rate consistently exceeds the processing rate, backlog accumulates regardless of how efficient reviewers become at rejecting individual items. Consequently, “just reject it” is a locally optimal strategy that may nevertheless fail to address the global characteristics of the system.

  Furthermore, I think it’s useful to distinguish between identifying low-quality contributions and doing so at scale. The cognitive effort required to conclude “this is not worth merging” is still non-zero. Every submission requires context switching, repository loading, architectural reasoning, verification that nothing subtle has been overlooked, and ultimately a decision. While each of these activities may appear trivial in isolation, their cumulative effect across hundreds or thousands of submissions represents a meaningful opportunity cost for maintainers who might otherwise be spending that same time reviewing genuinely valuable work or implementing new features.

  For that reason, I don’t think the existence of a rejection mechanism meaningfully addresses the broader concern being discussed. Rather, it demonstrates that the cost of filtering remains attached to human reviewers even as the marginal cost of generating candidate contributions approaches zero.

  In other words, I agree that you can close this thread.

  Now imagine doing that another 699 times today…

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  • Epp@lemmus.org ⁨1⁩ ⁨week⁩ ago

    Alright, you’ve demonstrated the difficulty posed by reality; let’s hear your proposed solution?

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    • iocase@lemmy.zip ⁨1⁩ ⁨week⁩ ago

      Well it’s what maintainers are already doing. Closing community contributions or burning out. A reputation system can be games unless the requirements for contributing are so restrictive it kills contributions anyways since most people don’t have the time and energy to get 100 PRs reviewed and accepted in a gold-standard group of projects to prove they won’t suggest slop.

      Honestly I think the solution is the true price of tokens being charged to end users. If it costs you $15 instead of $0.10 to generate a slop PR now you actually give a shit about how it works. I think we’re heading there soon… Anthropic already hiked their prices 9-27X, and it looks like they need at least 2 more of those hikes in a row to begin to break even.

      I think the eventual mature path for AI is as a coding assistant instead of autopilot. An expensive tool you use like an intern for making unit tests or finding a persistent bug in your code.

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      • Epp@lemmus.org ⁨1⁩ ⁨week⁩ ago

        Eh…I don’t know that that’s a viable solution.

        Take me, for example - I get $19 of tokens per month through one of my employers. That used to be more than enough to do nearly everything I wanted every month. Now, that’s one minor feature per month. So I don’t bother even using them. Instead, I use the GPU on my leisure/gaming laptop, and it processes all my LLM requests locally. So I have unlimited tokens.

        I think the actual solution is patience. As the tools improved in quality, so too do the quality of the PR. Soon, I believe, they will be better quality than they have been ever before. If maintainers can just hold out that long … 🤞

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