7 ms·

Interesting - how are you interacting and orchestrating this?

• pimeys 1mo ago
  Not the parent, but: https://omp.sh/ https://omp.sh/ You define roles for different agents like this: modelRoles: task: fireworks/kimi-k3-fast:high plan: fireworks/kimi-k3-fast:max slow: fireworks/kimi-k3-fast:max smol: fireworks/deepseek-v4-flash-0731:low tiny: fireworks/gpt-oss-20b vision: fireworks/qwen3.7-plus:high designer: fireworks/qwen3.7-plus:high advisor: openai-codex/gpt-5.6-sol:high main_worker: fireworks/kimi-k3-fast:high fast_worker: fireworks/deepseek-v4-flash-0731:low vision_worker: fireworks/qwen3.7-plus:high research_worker: fireworks/glm-5.2:medium code_worker: fireworks/kimi-k2.7-code-fast:high review_worker: anthropic/claude-fable-5:high security_review_worker: fireworks/kimi-k3-fast:max minimal_worker: fireworks/gpt-oss-20b default: fireworks/kimi-k3-fast task: agentModelOverrides: task: "@main_worker" sonic: "@fast_worker" scout: "@fast_worker" designer: "@vision_worker" librarian: "@research_worker" reviewer: "@review_worker" security-reviewer: "@security_review_worker" Then you first say /plan and use some big model like K3. Finally the harness shows you a markdown you approve, and in approval you switch to a smaller model and reset the context. The smaller model gets the full plan and starts working on it. When done, you say /review and it spawns N review agents and returns the change suggestions. And you iterate on that.