72 karma · joined January 3, 2026
It's wild to me to claim that it's tricky to customize one of these harnesses and for that to be the entire justification for an entirely different harness.
It's really not that hard. If you want to reduce costs then all you need to do is practice delegation: instead of using the strong model, all the time to do everything, instead, you have the stronger model delegate well-defined tasks to a weaker model. Patterns like these are really easy to wire up.
But they didn't address the criticism. "cutting ~75% of tokens while keeping full technical accuracy" is an empirical claim for which no evidence was provided.
Are Chinese model shops propped up by investor money? Is Google?
Open weights models are only 6 months behind SOTA. If new model development suddenly stopped, and today's SOTA models suddenly disappeared, we would still have access to capable agents.
- Opencode (anomalyco/opencode) is about 670k LOC
- Codex (openai/codex) is about 720k LOC
- Gemini (google-gemini/gemini-cli) is about 570k LOC
Claude Code's 500k LOC doesn't seem out of the ordinary.
This is an oversimplification.
If you have taste and talent, then the LLM output you get is going to reflect that.
So on the one hand, yes: tasteless and talentless people won't know good output from bad output. On the other hand, people with taste and talent can actually get good output.
This couldn't be more wrong. The simplest refutation is just to point out that there are temperature and top-k settings, which by design, generate tokens (and by extension, ideas) that are less probable given the inputs.
Unprompted they're not unlike a human sleeping or in a coma. Those states don't preclude consciousness in other states.