Yeah, the question is whether this applies to all of context management.

I've been using a custom harness based on https://minimal-agent.com/ (itself based on swe-mini-agent), which is like 50 lines for the core logic. Bash is all you need.

For small tasks, I find it's about 8x faster (and uses 8x fewer tokens) than the standard harness for each model.

For bigger tasks I haven't tested it much. It seems to work too but I think they're a bit less focused and productive in that case. It could be that those big harnesses' 20k token system prompts are doing something important with regard to steering software development workflows. (e.g. I heard Fable has a custom system prompt in Claude Code which might explain its markedly more proactive behavior.)

So I want to say there's still a lot of value in context engineering though it seems to diminish with each model release (since they're fine tuned on mostly non stupid behavior and need less hand holding).

> So I want to say there's still a lot of value in context engineering though it seems to diminish with each model release

I can't see how it would diminish unless you are literally working on public domain stuff. Unless stuffing context becomes cost effective and will not affect AI reasoning (this will be much harder), I don't see why context engineering is here to stay until we have close to AGI.

In think in all cases where I've seen it compared CC performed worse than a minimal harness.