ARCHITECTURE
Agentic AI ArchitectureFrom responsibility
to structure.
Architecture makes selected structural concerns,
boundaries and interfaces legible.
ZeroField maps where agent actions cross trust boundaries, which permissions and human approvals apply, and how execution remains traceable and recoverable.
SCROLLTO EXPLORE
FROM CONCEPT TO STRUCTURE
From conceptual
responsibility to
selected structural views.
The Framework identifies responsibilities. Architecture translates them into visible boundaries, permissions, interfaces and control points. Systems and applications express these concerns within a particular implementation.
Framework
Conceptual
responsibilities
Architecture
Selected structural concerns, boundaries and interfaces
Systems / Applications
Concrete
implementations
SELECTED PUBLIC ARCHITECTURAL MODEL
Six responsibility
domains.
One selected
structural view.
The six domains coexist within the ZeroField Framework. This model shows a selected public architectural view, without implying specific implementations or domain-to-domain dependencies.
Context
Situation
Meaning
Relevance
Intelligence & Roles
Knowledge
Capabilities
Roles
Control & Governance
Authority
Permissions
Oversight
Coordination & Execution
Events
Actions
Progression
Escalation
State, Memory & Knowledge
State
History
Context
Continuity
Integration & Interfaces
External systems
Data
Interfaces
System actions
ARCHITECTURAL MODEL
Context
Situation · Meaning · Relevance
Coordination & Execution
Events · Actions · Progression
Intelligence & Roles
Knowledge · Capabilities · Roles
State, Memory & Knowledge
State · History · Context
Control & Governance
Authority · Permissions · Oversight
Integration & Interfaces
External systems · Data · Interfaces
Context
Situation · Meaning · Relevance
Intelligence & Roles
Knowledge · Capabilities · Roles
Control & Governance
Authority · Permissions · Oversight
Coordination & Execution
Events · Actions · Progression
State, Memory & Knowledge
State · History · Context
Integration & Interfaces
External systems · Data · Interfaces
KEY ARCHITECTURAL CONCERNS
Key architectural concerns
Boundaries, Interfaces,
Authority and Control
Architecture makes responsibility boundaries explicit: which actor may access an interface, which operations are permitted, and when approval is required. A reachable tool or API is a capability—not automatic authority to create an external effect.
Execution and
Continuity
Architecture accounts for how work happens and what remains relevant across time. It includes execution concerns such as events, actions and decisions, and continuity concerns such as state, history, context, memory and traceability — without implying specific runtime or storage architectures.
Integration with
External Systems
Architecture provides for deliberate interaction with external systems, data, identity environments and other interfaces. These integrations allow ZeroField-based systems to operate within broader environments while maintaining clear responsibility and boundary distinctions.
AGENTIC AI ARCHITECTURE
What agentic AI architecture
must define.
An agentic AI architecture is not only a model, prompt or orchestration layer. It must make responsibility, authority, execution, state, interfaces and evidence legible enough for the system to act within explicit boundaries.
Agentic AI architecture defines which actors may use which tools, where trust boundaries and human approvals apply, how actions affect external systems, and which state and evidence remain for review and recovery.
Context & Purpose
Architecture identifies the operating context, relevant participants, intended outcomes and constraints that shape what the system is responsible for.
Authority & Control
Identity, permissions, delegated authority, approvals and escalation define which actions may be taken autonomously and which remain under human control.
Execution & Interfaces
Actions, tools, data and external systems create execution paths and trust boundaries. Architecture makes those paths explicit without prescribing one runtime stack.
State, Memory & Evidence
Working context, durable state, history, knowledge and action records support continuity, evaluation and traceability across time.
These concerns connect back to the six ZeroField responsibility domains; Architecture turns those conceptual responsibilities into selected structural views.
EXECUTION, TOOLS & ORCHESTRATION
Reasoning becomes architecture
when it can act.
Agentic systems act through tools, APIs, workflows and other agents. Architecture should make each invocation inspectable: actor identity, delegated scope, target interface, permitted operation, expected external effect and applicable approval.
Orchestration coordinates this progression without becoming a substitute for governance. Planning, handoffs, retries and multi-agent collaboration still operate inside authority, permission and state boundaries.
See how these concerns appear in concrete AI agent systemsWhat can the system do?
Tools expose bounded capabilities such as retrieval, calculation, data access or external actions. Discovery does not imply permission to execute.
Who may invoke what?
Tool use should reflect actor identity, delegated authority, applicable permissions and the context in which an action is requested.
How does work progress?
Plans, steps, handoffs, retries and agent-to-agent coordination create execution sequences that must remain observable and bounded.
Where does reasoning become action?
Calls into business systems, APIs, data stores or physical processes cross trust boundaries and may require stronger authorization or approval.
STATE, MEMORY, EVIDENCE & CONTINUITY
Continuity is
more than memory.
A reliable architecture distinguishes what is temporarily available from what must persist. Memory can inform future behavior, but state, history, commitments, evidence and recovery concerns determine whether behavior remains coherent and reviewable over time.
Working Context
Immediate task context, active inputs and short-lived information used during current reasoning or execution.
Durable State
Persistent facts about progress, decisions, commitments and system condition that must survive individual interactions.
Memory & Knowledge
Historical and domain information that can support future interpretation without becoming an uncontrolled source of authority.
Evidence & Traces
Evidence links actions to actors, permission and approval decisions, tool results and state changes for later review.
Continuity & Recovery
Clear state and evidence make it possible to resume, reconcile or recover work without pretending that every prior assumption remains valid.
OBSERVABILITY & AUDITABILITY
Execution should leave evidence.
Observability connects architecture to evaluation. Agent actions, tool use, approvals, handoffs and state changes should be traceable enough to explain what happened, assess whether boundaries were respected and support later assurance work.
Explore evaluation and assurance researchFAILURE BOUNDARIES, GUARDRAILS & RECOVERY
A safe path must include
a way to stop.
Agentic AI architecture should define more than the successful path. It should also make failure states, deterministic guardrails, interruption points and recovery responsibilities visible before an autonomous sequence reaches an irreversible outcome.
Guardrails
Deterministic limits can block prohibited actions, constrain loops or steps, enforce policy checks and keep model behavior inside known operational boundaries.
Failure Boundaries
Tool errors, unavailable dependencies, invalid state and authorization failures should stop or redirect execution instead of silently propagating uncertainty.
Interruption & Safe Shutdown
Pause, cancel, override and escalation mechanisms provide explicit paths for human or system intervention when continued autonomy is no longer justified.
Recovery & Reconciliation
Before retrying an uncertain action, distinguish completed, failed and unknown effects. Reconcile external state, then recheck assumptions and approvals before resuming.
ZeroField treats these as architectural responsibilities, not as a claim that one universal runtime, guardrail engine or recovery mechanism fits every implementation.
REFERENCE CONTEXT
Industry architecture
context.
ZeroField’s responsibility model is its own. The external references below provide current industry context for terminology around agent tools, orchestration, permissions, guardrails, memory, auditability and human oversight.
ARCHITECTURE IS SELECTIVE BY DESIGN
Enough to understand.
Not the complete implementation.
The public Architecture page reveals the structural concerns needed to understand ZeroField without claiming to reproduce its complete internal implementation.
FROM FRAMEWORK TO SYSTEMS
From architecture
to concrete systems.
These architectural concerns can be expressed differently across systems, environments and use cases.
ZeroField Framework
Conceptual
responsibilities
Architecture
Selected structural concerns, boundaries and execution-oriented views
Systems / Applications
Concrete
implementations
Explore system designs
informed by ZeroField.
From architecture
to concrete systems.
See how these architectural concerns can be expressed in different systems, application contexts and environments.
These architectural concerns can be expressed differently across systems, environments and use cases.
Explore Systems