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This is especially appropriate for HN and other software engineering forums where embedded/systems, frontend, backend, imperitive, functional, etc programmers all constantly yell at each other about whether the elephant is a rope or a snake or a tree.

It's easy to think your experience encompasses all of "software" and give definitive advice to others who work in a vastly different space than you do.

> One text tells of a fever epidemic that struck the infant daughter of the king. She was still a nursing baby when she became ill. She never recovered from the fever and her health declined precipitously until she passed away.

Wow, the infant daughter was nursing a baby? Were the Hittites like aphids which can be pregnant while still in the womb?

As much as I hate AI slop, sometimes I think people are better off leaving writing to robots.

I lean towards a hybrid review process where humans accept their limitations, focus what they're good on(higher level concepts and architecture of the proposed change), and let the LLMs do the rest.

Doing a line by line review as a human is silly now.

Think of the docs as a cache. You're saving tokens by starting with a map of the code. Why try to figure it out each time?

Reducing which risk? The risk that the models of big American companies cause harm? What if they abide by some rules while models of others remain unfettered? That also carries risk. I appreciate the wish to have tame AI which only does good things but I'm afraid we're already beyond that.

Again you're shifting your arguments and not addressing your initial response.

It's frequent for SWEs to make blanket statements with considering the vast space of issues other people face that they don't have experience with or awareness of. Anyway, I'm not going to tell you what you do or don't need, only what worked and didn't for me.

In my codebase it is difficult to get agreement on comments and documentation so rather than rely on it I adapted. One of the first things I did when I succumbed to agentic development was to point codex at the code and ask it to generate a high level description of where important files, such as our public API, reside, what the hierarchy is, what the code does, etc. In my case, this level of documentation is fairly static if I avoid implementation details. So now I have a handful of agent files in my tree and it seems to save quite a few tokens and improve my results. I frequently have other devs ask me how I get such good results when doing agentic reviews of their changes(always my first step now before I start my human review). I also include instructions in the agents files instructing the agent to maintain the agent files if any relevant changes are made. It seems to work quite well for me.

So you want to regulate the sale of GPUs? How are you going to do that and why would it be more effective than currently failing measures to regulate nearly everything else?

Good examples. We are currently failing at all of that.

They very likely will via shell companies in jurisdictions outside the west. Are you suggesting we go to war to stop them? The massive datacenters are needed to serve models to millions. Criminal orgs don't need massive data centers anyway.

As Bruce Schneier recently discussed, law and tax law are code, just like source code. LLMs are great at finding holes in them. Illicit organizations looking to launder funds are most certainly interested in what AI can do for them.

Ok but this response has nothing to do with your other comment. What exactly were you trying to say?

So you cede the frontier of human progress to illicit organizations and other nations?

Nuclear weapons take a bit more work than doing math.

So you are contending that individuals cannot run advanced models? What brought you to that conclusion?

Secondly, are you contending that progress in model efficiency and hardware just stops at whatever level you think is sufficient to prevent individuals or organizations from acquiring sufficient resources to run advanced models?

Humanity has discovered a way to create a form of intelligence using math. This knowledge is not going back in the box.