Claude Code, Codex and OpenCode work in one team. Each does what it’s best at, and you’re not tied to one vendor or its limits.
An independent opinion.
The best teams bring in outside consultants: an insider stops seeing what they’re used to, an outsider doesn’t. Let Codex review the code Claude wrote. Or ask three models from three vendors the same question and get three unbiased answers.
Routine work goes to cheap and local models.
Don’t spend your flagship’s limits on simple work. Hand data labelling, reading and sorting texts, and rough checks to a local or low-cost model through OpenCode. The flagship sets the task and gets the answer back.
The right model for the job.
Models have different strengths. In the author’s experience, Codex writes better texts and articles, and Claude writes better code. Build a team where everyone does what they do best.
Your own models, through OpenCode.
OpenCode runs local models with no vendor lock-in. It’s the best way to put your own model on the team: harnsy delivers its tasks and brings back its answers like any other agent’s.
The weekly limit ran out on Wednesday. The work didn't.
Claude can hand routine work to another model.
How: through OpenCode a local or low-cost model joins the team, and harnsy carries its tasks.
Claude delegates routine work to a local model through OpenCode.
I train models. Claude runs the whole training process. Data labelling I gave to GLM on a subscription and to Qwen, which runs locally on my machine. They do it pretty well, and I don’t spend my Claude subscription on labelling.
Pavel Buchnev · CTO, author of harnsy
Or ask Codex to review code written by Claude.
Limits, honestly
Savings aren’t measured yet: the cost of a team depends on how many agents you run.
The model comparison is the author’s observation, not a benchmark.
OpenCode is free; the model behind it may not be.
Your first AI team is one prompt away.
Installing takes one sentence to your agent.
Install harnsy following https://harnsy.dev/llms.txt
