China and/or Russia might have a collection of zero-days they've been sitting on, which they could surreptitiously provide to Iran. Of course, there's attribution risk there, and the opportunity cost of not saving those zero-days for their own later use.

Containers here, though I don't run Claude Code within containers, nor do I pass `--dangerously-skip-permissions`. Instead, I provide a way for agents to run commands within containers.

These containers only have the worker agent's workspace and some caching dirs (e.g. GOMODCACHE) mounted, and by default have `--network none` set. (Some commands, like `go mod download`, can be explicitly exempted to have network access.)

I also use per-skill hooks to enforce more filesystem isolation and check if an agent attempts to run e.g. `go build`, and tell it to run `aww exec go build` instead. (AWW is the name of the agent workflow system I've been developing over the past month—"Agent Workflow Wrangler.")

This feels like a pragmatic setup. I'm sure it's not riskless, but hopefully it does enough to mitigate the worst risks. I may yet go back to running Claude Code in a dedicated VM, along with the containerized commands, to add yet another layer of isolation.

Julia is aimed at scientific computing. It competes against Python with numpy/scipy, R, etc.

Use the exoskeleton at the warehouse to reduce stress and injury; just keep lifting weights at home to not let yourself atrophy.

> the “art” part of it is writing sound, scalable, performant code that can adapt and stand the test of time.

Sure, and it's possible to use LLM tools to aid in writing such code.