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Operations Patterns

Operational patterns including SLM→LLM decision flows, ownership maps, and implementation guidance.

SLM → LLM Decision Flow

Production handoff logic for routing between SLM and LLM tiers.

flowchart TD
    A[Incoming task / event / request] --> B[SLM preprocess]

    B --> C[Intent classification]
    C --> D[Policy / risk scan]
    D --> E[Tool-needed check]
    E --> F[Complexity estimate]
    F --> G[Confidence score]

    G --> H{Blocked by policy?}
    H -->|Yes| X[Refuse / redact / quarantine]
    H -->|No| I{Simple and high confidence?}

    I -->|Yes| Y[Return SLM path result]
    I -->|No| J{Tool first?}

    J -->|Yes| K[Run tool / workflow]
    K --> L[SLM compress + validate tool output]
    L --> M{Enough to answer?}
    M -->|Yes| Y
    M -->|No| N[Escalate]

    J -->|No| N[Escalate]

    N --> O[Prepare compact escalation context]
    O --> P[LLM reasoning / synthesis]
    P --> Q[Post-LLM policy / quality check]
    Q --> R[Return final response]
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Threshold Guidelines

Use configurable thresholds, not hardcoded logic.

Stay in SLM Path Escalate to LLM
High confidence Confidence below threshold
Classification/extraction/screening Policy ambiguity exists
Short, bounded output Tool outputs conflict
Unambiguous tool result Multi-agent disagreement
Low risk User-facing, high impact

Decision Schema

{
  "intent": "ci_failure_triage",
  "risk_level": "medium",
  "needs_tool": true,
  "complexity": "medium",
  "confidence": 0.81,
  "policy_status": "allow",
  "recommended_path": "tool_first",
  "escalate": false
}

Repo-to-Service Ownership Map

Maps conceptual stack into likely repo/service boundaries.

flowchart LR
    R1[pvc-ai-gateway repo] --> S1[AI Gateway Service]
    R2[cognitive-mesh repo] --> S2[Cognitive Mesh Service]
    R3[codeflow-engine repo] --> S3[CodeFlow Engine Service]
    R4[agentkit-forge repo] --> S4[AgentKit Forge Service]
    R5[phoenixrooivalk-* repos] --> S5[PhoenixRooivalk Edge + Command Services]
    R6[shared-platform / contracts / schemas repo] --> S6[Shared Contracts / Telemetry / Policy / SDKs]
    R7[infra repo] --> S7[Azure Infra / Monitoring / Deployment Pipelines]
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Ownership Summary

Repo Owns
pvc-ai-gateway Ingress API, routing contracts, escalation policy, provider abstraction, semantic cache, audit envelope
cognitive-mesh Specialist routing, task decomposition, agent state model, synthesis orchestration, disagreement logic
codeflow-engine PR event models, diff classification, CI log triage, contract break workflows, comment generation
agentkit-forge Tool registry, tool selection schemas, arg extraction, execution-loop state, retry/fallback logic
phoenixrooivalk-* Edge event schema, local alerting, escalation packet format, command-layer integration
shared-platform Telemetry envelope, routing decision schema, model usage schema, audit/trace IDs, reusable schemas
infra Azure deployment, Grafana/ADX dashboards, Key Vault wiring, service identities, networking

Implementation Order

First

Define shared contracts:

  • Routing decision schema
  • Model usage event
  • Tool execution event
  • Audit envelope
  • Edge escalation packet

Second

Implement telemetry in the gateway:

  • Trace ID propagation
  • Decision logs
  • Provider usage events
  • Cost estimation fields

Third

Bring CodeFlow and AgentKit onto same telemetry envelope.

Fourth

Add Cognitive Mesh orchestration and disagreement telemetry.

Fifth

Add Rooivalk edge packet telemetry and sync audit.

Architectural Recommendation

For your environment, the strongest production stance is:

  1. AI Gateway is the only public AI ingress
  2. All routing decisions emit one shared RoutingDecision contract
  3. All model calls emit one shared ModelUsageEvent
  4. All tool invocations flow through a broker or shared event schema
  5. All edge escalations use compact evidence packets
  6. ADX/Kusto + Grafana becomes the operational truth layer

This gives you:

  • Cost visibility
  • Quality visibility
  • Compliance evidence
  • Easier A/B testing of SLM routing
  • Cleaner failure diagnosis