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The Engine is the backbone of 2501. Command Center is the UI, Engine is the backend; everything else is automation around them.

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How a task gets executed

Command Center / Gateway / CLI
        │
        ▼
      Engine ─── spawns ───▶ Agent container (lifecycle manager)
                         └─▶ Executor container (ssh / winrm / gMSA / kube pod)
        │
        ▼
   Agent runs its task on the target host, then both containers exit
Two containers run permanently in your infrastructure: Engine and Command Center. Every task spawns short-lived containers — one for the agent, one for the executor that matches the target’s protocol — and tears them down when the task ends. (MCP plugins add one container each, only if configured.) The same flow runs whether the task came from the Command Center UI, a gateway ticket, or the CLI. Engine doesn’t care.

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The two-engine agent

Every agent uses two LLMs in tandem, each with a distinct job.

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Main engine — the executor

Does the work: navigates the filesystem, reads and modifies files, executes commands, interacts with CLIs and MCPs. This is the model that consumes most tokens because it carries the operational context required to act reliably.

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Secondary engine — the copilot

Watches the main engine. It generates the initial plan so the main engine can focus on heavy lifting, and reviews every command before it runs to answer:
  • Does this comply with the active operational rules? If not, redirect.
  • Is the agent trying to alter the system while running in read-only mode? If yes, block.
  • Is the agent drifting away from the task? If yes, refocus.
This separation is why investigate-only mode works reliably: the secondary engine acts as a judge over the main engine’s commands.

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The tenant engines

Engines aren’t just per-agent. Two more sit at the tenant level — the defaults used everywhere an agent isn’t running:
Used forEngine
Gateway routing (which ticket → which agent on which host)Tenant Text LLM model
Parsing PDFs and images attached to ticketsTenant Multimodal model
AI Assistant conversationsTenant Text LLM model
Knowledge ingestion (turning your docs into rules + facts)Tenant Text + Multimodal
Tenant defaults are picked in Settings → Tenant from the model catalog. A 70–300b model is usually plenty here — routing is lighter work than executing.

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Where the LLMs come from

The catalog is managed in Command Center → Settings → Models and Providers. Adding a provider or a model is pure UI configuration — no engine restart, no editing env files. See Providers.