And to put it plainly: we won't be able to manage LLM-generated contributions without LLMs. It's physically impossible at this scale.
Which means the immune system has to be built from the same substrate as the threat. The question isn't whether to use AI for review — it's whether that review layer will be open, distributed, and community-owned, or closed, centralized, and controlled by whoever gets there first.
But there's a layer above that which is easy to skip over: human supervision.
Not line-by-line review — that's already gone. What remains is supervision of curated logs, at ratios that might look something like 1 in 10^10. The human role is no longer technical production. It's oversight. And that's a genuinely new function that we don't have good tools for yet.
The flow is perpetual. It doesn't stop, it doesn't slow down, it only accelerates. Which means we'll need to build tooling specifically designed to absorb volume, abstract it into supervisable signals, and train us to work at that level of abstraction — where the unit of human attention is no longer a line of code or a PR, but a pattern across millions of automated actions.
Automation isn't the threat to manage. It's the only viable response to production at this frequency. The question is whether we build the abstraction layer deliberately, as a community, before someone builds it for us.
Which means the immune system has to be built from the same substrate as the threat. The question isn't whether to use AI for review — it's whether that review layer will be open, distributed, and community-owned, or closed, centralized, and controlled by whoever gets there first.
But there's a layer above that which is easy to skip over: human supervision.
Not line-by-line review — that's already gone. What remains is supervision of curated logs, at ratios that might look something like 1 in 10^10. The human role is no longer technical production. It's oversight. And that's a genuinely new function that we don't have good tools for yet.
The flow is perpetual. It doesn't stop, it doesn't slow down, it only accelerates. Which means we'll need to build tooling specifically designed to absorb volume, abstract it into supervisable signals, and train us to work at that level of abstraction — where the unit of human attention is no longer a line of code or a PR, but a pattern across millions of automated actions.
Automation isn't the threat to manage. It's the only viable response to production at this frequency. The question is whether we build the abstraction layer deliberately, as a community, before someone builds it for us.