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AI Architecture › L5 · Applications & Copilots
L5 · Applications & Copilots

Agentic Tool-Use With Bounded Actions

Every copilot action is a typed, bounded tool call — read, simulate, or propose — with no tool that writes directly to the plant.

THE STACK · click to jumpL7Ecosystem & StrategyL6Experience & VisualizationL5Applications & CopilotsL4OrchestrationL3Twin Modeling & AIL2Data FabricL1Control PlaneL0Foundation▲tlmctl▼L5 · APPLICATIONS & COPILOTSAgentic copilots that reason over the machine.1Plasma Copilotscenario design2Engineering Copilotsubsystem analysis3Operations Copilotrunbooks & procedures4Agentic Toolsbounded action-taking5Knowledge BaseRAG over the fabric6Guardrailssafety-boundedMACHINE TIEReads the twin and fabric; proposes actions that route through L4.KRONOS FUSION ENERGYAI-NATIVE S.M.A.R.T. GENERATORAPPLICATIONS & COPILOTSSHEET 07REV. 2026-08L5 · AI-NATIVE STACK
L5 · Applications & Copilots — its place in the stack (left, click any layer) and its internal components (right). Telemetry rises; control descends.

Actions are tools, and tools are bounded

L5 copilots are agentic: they plan and call tools rather than emitting free text alone. The safety of the whole layer rests on one principle — every tool is bounded and typed, and no tool in a copilot's toolbox writes to the hard-real-time control path. The available actions fall into three classes: read (query L2, query twin state), simulate (run a twin module or surrogate), and propose (submit an action to L4 for authorization).

The three action classes

Copilot action classes
Readquery telemetry, retrieve documents, read twin stateno side effectSimulaterun twin module, surrogate, or scenariono side effect; bounded computeProposesubmit an action to L4 for authorizationside effect only after L4 + human approval

There is no fourth class. A copilot cannot command an actuator, arm a pulse, or change a persistent setting directly. The strongest thing it can do unilaterally is compute. Everything with a plant consequence becomes a proposal object handed to L4.

Typed tool schemas

json
{
  "tool": "twin.simulate_scenario",
  "class": "simulate",
  "args": {"machine": "breeder", "waveforms": {...}},
  "bounds": {"max_runtime_s": 30, "envelope_required": true},
  "side_effect": false
}

Bounded tool-use is what lets a copilot be genuinely agentic without being dangerous: it can chain dozens of reads and simulations to reason its way to an answer, yet it structurally cannot touch the machine. The next pages detail the action schemas and the planning loop that sequences them, and the L4 authorization gate that every proposal passes through.

Content reviewed August 2026 · design-and-simulation stage