Examples

AI Replenishment

AI replenishment shows model-swappable actor wiring with identical loop constraints and deterministic approval policy.

Loop behavior

States: SIGNAL_DETECTED -> AI_ANALYSIS -> PENDING_BUYER_APPROVAL -> PO_TRIGGERED
AI actor transition: recommend_replenishment
Hard guards: confidence_threshold, approval_obtained
Human-only transition: approve_replenishment

Scenario

Lumebondé Bond Repair Serum (LMB-BRS-001) spikes +89% at DC-East with currentStock=142, reorderPoint=280, forecastedDemand=527, and leadTimeDays=14.

Loop definition

1import { LoopBuilder } from "@loop-engine/sdk"
2 
3const replenishmentLoop = LoopBuilder
4  .create("scm.replenishment", "scm")
5  .version("1.0.0")
6  .description("Triggered replenishment from demand signal")
7  .state("SIGNAL_DETECTED")
8  .state("AI_ANALYSIS")
9  .state("PENDING_BUYER_APPROVAL")
10  .state("PO_TRIGGERED", { isTerminal: true })
11  .state("DEFERRED", { isTerminal: true })
12  .initialState("SIGNAL_DETECTED")
13  .transition({ id: "start_analysis", from: "SIGNAL_DETECTED", to: "AI_ANALYSIS", actors: ["automation"] })
14  .transition({
15    id: "recommend_replenishment",
16    from: "AI_ANALYSIS",
17    to: "PENDING_BUYER_APPROVAL",
18    actors: ["ai-agent", "automation"],
19    guards: [
20      {
21        id: "confidence_threshold" as never,
22        description: "AI confidence >= 0.75",
23        failureMessage: "Confidence below threshold",
24        severity: "hard",
25        evaluatedBy: "external"
26      }
27    ]
28  })
29  .transition({ id: "approve_replenishment", from: "PENDING_BUYER_APPROVAL", to: "PO_TRIGGERED", actors: ["human"] })
30  .outcome({ id: "replenishment_triggered", description: "PO submitted", valueUnit: "replenishment_triggered" })
31  .build()

Anthropic and OpenAI actors

Both providers create the same AIAgentActor shape and submit evidence with identical keys.

1import { actorId } from "@loop-engine/core"
2import type { AIAgentActor } from "@loop-engine/actors"
3 
4const claudeActor: AIAgentActor = {
5  type: "ai-agent",
6  id: actorId("agent:demand-forecaster"),
7  agentId: "claude-sonnet-4-20250514",
8  gatewaySessionId: "claude-session-001"
9}
10 
11const openAiActor: AIAgentActor = {
12  type: "ai-agent",
13  id: actorId("agent:demand-forecaster"),
14  agentId: "gpt-4o",
15  gatewaySessionId: "openai-session-001"
16}

Guard outcomes

1"cmt">// confidence 0.58 -> held at AI_ANALYSIS
2const lowConfidence = await engine.transition({
3  aggregateId,
4  transitionId: transitionId("recommend_replenishment"),
5  actor: claudeActor,
6  evidence: { ai_confidence: 0.58, ai_reasoning: "Insufficient certainty" }
7})
8"cmt">// lowConfidence.status === "guard_failed"
9 
10"cmt">// confidence 0.82 -> advances to PENDING_BUYER_APPROVAL
11const highConfidence = await engine.transition({
12  aggregateId,
13  transitionId: transitionId("recommend_replenishment"),
14  actor: openAiActor,
15  evidence: { ai_confidence: 0.82, ai_reasoning: "Demand spike sustained" }
16})
17"cmt">// highConfidence.status === "executed"