It is fine to move up a level, and use models with their providers' harnesses, as long as you stay away from extras like their own memory and infrastructure. There is not much investment required, and you will end up with a more robust solution. A simple setup that works:

- Agents live in their own directories, for example ~/Agents/[project]/[instance]/

- In a tmux session run each agent in its own window and directory. Pi, OpenCode, Claude Code, Codex, a combination, whatever works best at any given time.

- Tell them that they are working with other agents, and that knowledge is shared and stored in an agreed format. They are very good at using OKF[1], for example. In my actual setup I use a harvester agent whose only job is to ensure the quality of the knowledge.

- They can communicate with each other simply by sending messages to each other's tmux windows with tmux send-keys. If the team grows, or you work with other people, you can use a general messaging system (I wrote and maintain https://github.com/awebai/aweb but I am sure there are others).

1: https://okf.md