AGF

The 19 Primitives

Named patterns for governed agentic systems — runtime, lifecycle, and substrate primitives organized into the Rings Model.

The 19 primitives are the building blocks of AGF. They are not new inventions — they are named patterns drawn from established practice across distributed systems, security engineering, compliance, and control theory. The contribution is pulling them together into a composable architecture for the agentic context.

Runtime Primitives (#1–#17)

These operate within or across the ring pipeline during agent execution.

#PrimitiveRingOne-Line Description
1Separation of Producer & Verifier0+1The agent that creates output must not be the sole agent that validates it
2Validation Loops with Convergence Gates1Iterative verification until quality thresholds are met or budget is exhausted
3Self-Improving Cycles3The system gets better by learning from its own execution
4Adversarial Critique1Dedicated challenger that actively tries to find flaws
5Structured Output PersistenceFabricEvery ring produces and consumes structured artifacts — the data contract
6Provenance ChainsFabricEvery output carries its full decision history
7Bounded Agency2Agents operate within explicit, enforced boundaries
8Governance Gates2Explicit decision points where execution pauses for authorization
9Policy as Code2Governance rules as versioned, executable, testable objects
10Event-Driven ObservabilityFabricEvery ring emits structured events — the shared nervous system
11Trust Ladders2+3Trust is earned through demonstrated performance, not granted by default
12Memory-Augmented Reasoning0+3Agents reason with persistent memory, not just immediate context
13Error Handling & RecoveryFabricGraceful degradation, checkpointing, compensation
14Identity & AttributionFabricEvery agent has authenticated, inspectable identity
15Adversarial RobustnessSecurityAssume breach. Defense in depth. Verify explicitly.
16Transaction & Side-Effect Control0+2Pre-commit/commit/post-commit for irreversible actions
17Data Governance & Confidentiality2+FabricClassification, consent, PII, lineage, retention at every data flow

Lifecycle Primitive (#18)

#PrimitiveScopeOne-Line Description
18Evaluation & AssurancePre-deploymentThe gate before the gate — validates configurations before they reach production

Substrate Primitive (#19)

#PrimitiveScopeOne-Line Description
19Agent Environment GovernanceAll ringsGoverned composition of context, instructions, tools, workspace, and memory

How They Map to the Rings

The Rings Model showing primitive placement
  • Ring 0 (Execution): #1, #5, #12, #14, #16 — the agent works, produces structured output, with identity
  • Ring 1 (Verification): #1, #2, #4 — separate verifier, iterative loops, adversarial critique
  • Ring 2 (Governance): #7, #8, #9, #11, #16, #17 — boundaries, gates, policy, trust, transactions, data governance
  • Ring 3 (Learning): #3, #11, #12 — self-improvement, trust calibration, memory
  • Fabric: #5, #6, #10, #13, #14, #17 — structured output, provenance, events, errors, identity, data governance
  • Security: #15 — adversarial robustness as a pervasive concern

Primitive Interaction Tensions

The primitives are not always harmonious. AGF names seven tensions with architectural invariants that resolve them:

TensionConflictInvariant
Self-Improvement vs. Reproducibility#3 changes behavior; #6 requires traceabilityAlways reproducible at a specific version
Trust Ladders vs. Governance Gates#11 reduces oversight; #8 ensures accountabilityCan skip a spot-check, never regulatory approval
Bounded Agency vs. Self-Improvement#7 constrains; #3 improves — can it expand itself?The box can get smarter inside. It cannot grow itself.
Validation vs. Latency/Cost#2 improves quality; each pass costs time and moneyQuality bounded by economics, not just capability
Memory vs. Signal-to-Noise#12 accumulates knowledge; stale memories inject noiseGrowth without curation is hoarding, not learning
Policy as Code vs. Self-ImprovementCan Ring 3 change Ring 2's policy rules?Can suggest governance changes, cannot enact them
Environment vs. Governance Integrity#19 optimizes the environment — but it IS the control surfaceThe environment can get better. It cannot get less governed.

Implementation Priority

For a practical implementation roadmap organized by phase, see the AI Engineering Profile.

For the complete primitive catalog with full patterns, deployment modes, security architecture, and existing work mapping, see the canonical source.

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