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The agent model

ORBIS's brain is deliberately a small, fast model that routes — not a giant model that does everything. This page explains that choice and how delegation, orchestration, and tools fit around it.

For the knobs, see the Agent reference.

Router first

Every turn, the LLM makes a routing decision before anything else:

  • Answer directly — most conversation.
  • Call a tool — a concrete action (set a reminder, list reminders).
  • Delegate — hand a heavier task to a specialist agent.

Keeping the routing model small and fast is what makes the orb feel responsive. The heavy thinking, when it's needed, happens elsewhere — in a delegate — and the orb narrates the result. (If you want a stronger model for just the decision turn, that's what two-model routing is for.)

Delegates: specialists the orb calls

A delegate is another agent ORBIS can hand work to. You give each one a name and a description; the LLM reads the descriptions and picks the right delegate for the task. Two kinds:

  • A2A agents speak the Agent2Agent protocol — a standard JSON-RPC contract for agents to message each other, keep a conversation across turns, and stream progress. This is how ORBIS talks to other agents in a fleet.
  • OpenAI-compatible delegates are any /v1/chat/completions endpoint treated as a sub-agent (a larger model, a specialized service).

The point: the orb stays a fast conductor; the delegates do the deep work.

Sync vs. background

Delegation comes in two shapes:

  • Delegate (sync-ish). The orb hands off one task, waits, and speaks the answer. It acknowledges immediately ("on it…") so it isn't silent, and it can narrate progress a delegate streams back.
  • Orchestrate (background). For a multi-step ask ("get the fleet status, then dig into any incident"), the orb runs a bounded loop in the background — calling delegates step by step, keeping context with each one — and reports the synthesized result when it's done. You can keep talking meanwhile.

Both are designed so a slow or unreachable delegate can't hang the orb: every step is time-bounded, and a dropped connection falls back gracefully.

Reminders and other actions

Actions the orb can take itself (not delegated) are tools — small, exact capabilities. Reminders are the headline example: set, list, and cancel them by voice, and see them in the reminders bell. A tool result is fed back to the model so it knows the action succeeded and can confirm it to you.

Why this shape

  • Responsiveness — a small router replies fast; depth is opt-in.
  • Composability — any A2A or OpenAI-compatible agent becomes a delegate without changing ORBIS.
  • Resilience — time-bounds and failover keep the orb talking even when a model or delegate misbehaves.

See also