Mission state
Keep the durable goal, active wave, task state, approvals and operator-visible progress outside any one model prompt so work can be resumed and inspected.
AI AGENT ORCHESTRATION · TECHNICAL REFERENCE · REVIEWED 21 SEP 2026
AI agent orchestration architecture: keep goals, tasks, authority and recovery in one durable execution model.
Orchestration is more than calling multiple agents. A production architecture needs durable mission state, dependency-aware task execution, bounded delegation, approvals, recovery and evidence that survives beyond one model turn.
DURABLE MISSION STATEBOUNDED DELEGATIONAPPROVAL + EVIDENCE
MISSION SCOPE
MISSION
WAVE
TASK
STATEdurable execution context
ORDERdependency waves
AUTHORITYpolicy + approval
01 · DEFINITION
What is AI agent orchestration architecture?
AI agent orchestration is the runtime discipline for coordinating durable work across tasks, agents, tools and human decisions. Agent orchestration architecture coordinates long-running work across agents, tools and people while preserving state, task dependencies, authority boundaries and execution evidence. The orchestrator does not replace every worker; it decides how work is decomposed, delegated, gated and resumed.
In Createting, missions and execution plans carry durable work state, worker contracts bound delegated execution, approvals gate consequential actions, and replanning can respond to dependency failures or operator intervention.
02 · SCOPE
The architecture problem is not “how many agents?” It is how state and authority move through the work.
The architecture decision starts with what state must survive, which tasks depend on one another, what a delegated worker may do, where approval can pause execution and how a failed plan resumes without replaying completed work.
Dependency graph
Tasks should start only when their dependencies are satisfied. Wave assignment and bounded concurrency make parallel work explicit instead of implicit in chat.
Delegation contracts
Worker execution should inherit a bounded contract: goal, allowed capabilities, autonomy context, success criteria and the evidence expected back from the delegated run.
03 · EXECUTION MODEL
Plan the work as dependencies and waves—not as an unstructured chain of agent messages.
MISSION / PLAN
WORKER EXECUTION
Primary roleHold the goal, dependencies and current execution state
Primary roleExecute one bounded task and return a result
Typical sourceMission goal, constraints, plan and prior task state
Typical sourceWorker contract, task context and granted capabilities
Default posturePreserve durable state and release tasks by dependency
Default postureStay inside the delegated contract and return evidence
Key questionWhat must happen next, and which dependencies block it?
Key questionWhat may this worker do, and what must it return?
04 · AUTHORITY & APPROVALS
Delegation does not transfer unlimited authority.
A worker can execute only inside the contract and policy context it receives. Consequential actions can pause for approval; Mission Control exposes pending approvals and intervention state without turning observation into the execution engine itself.
01Plan
Decompose the mission into explicit tasks and dependencies.
READY02Delegate
Delegate bounded work through a worker contract rather than handing over the entire mission context.
BOUNDED03Gate
Pause, approve or deny consequential work at the policy boundary—then resume from the next permitted state.
APPROVAL05 · RECOVERY & REPLANNING
A durable orchestrator needs a recovery model, not just a retry button.
Dependency failure, deadline risk or operator intervention can invalidate the current plan. Replanning should preserve completed work, identify remaining tasks, create a new plan revision and resume from an explicitly permitted point instead of replaying the entire mission.
DEPENDENCYTask dependency cleared
→
EXECUTIONsource · worker · time
→
EVIDENCEverified + resumable
A failed worker call should change mission state and evidence—not disappear inside a chat transcript.
06 · OBSERVABILITY & EVIDENCE
Mission Control should show the execution model that actually exists underneath it.
Operators need the current wave, task state, delegated workers, pending approvals and execution evidence—not a decorative dashboard. The board is an observation and intervention surface over durable mission and execution state.
AGENT STUDIOMISSIONSSUBAGENTSVOICEBROWSERAUTOMATIONSEVIDENCETOOLS
07 · PRACTICAL QUESTIONS
AI agent orchestration architecture: practical design questions.
What is the difference between agent orchestration and a multi-agent chat?
A multi-agent chat coordinates messages. Orchestration coordinates durable work: mission state, task dependencies, delegated workers, approvals, recovery and evidence that can survive beyond one conversation turn.
Why model orchestration as tasks and waves?
Explicit dependencies prevent tasks from starting before prerequisites are complete. Wave assignment makes safe parallelism visible and gives the runtime a concrete place to pause, resume or replan.
What should a delegation contract contain?
At minimum: the bounded goal, execution context, allowed capabilities, autonomy or policy constraints, success criteria and evidence expected from the worker. The parent mission should not hand over unlimited authority.
How do approvals fit into agent orchestration?
Approvals are execution gates, not separate workflow decoration. When a consequential action requires review, the mission can pause at that boundary and resume after a bound decision.
What happens when an orchestrated plan fails?
The system should preserve completed work, record the failure, identify remaining tasks and create a revised plan when recovery requires more than retrying the same step. Resume should start from an explicitly valid state.
Is Mission Control the orchestrator?
No. Mission Control is the operator-facing observation and intervention surface. Durable mission, execution, policy and worker state remain in the underlying runtime rather than inside the board UI.
ARCHITECTURE REVIEW
Map one long-running agent workflow into mission state, dependencies and authority boundaries.
Bring one workflow that currently crosses agents, tools or people. We’ll map the durable state, task graph, delegation boundaries, approvals, recovery path and evidence needed for production execution.