Recently, I have been looking more closely at the automated pilot processes within several companies, and I have discovered a pattern:
AI performs in enterprises not as isolated tasks, but as a series of tasks that automatically derive, expand, and rewrite.
Companies originally thought that what they provided to AI was a defined task:
Place Order
Price Comparison
Approval
Payment
Verification
Cross-border Processing
However, after receiving the task, what AI actually executes is a series of dynamic links:
Split Subtasks
Call External API
Generate Auxiliary Steps
Trigger Multi-Agent Collaboration
Automatically Adjust Priority
Rewrite task intent
Select path
Modify parameters
Trigger supplier callback
Generate post-task
In other words, AI is not executing tasks, but generating 'task lifecycles'.
The question is:
Companies cannot manage this lifecycle, cannot verify whether the lifecycle complies with rules, and cannot ensure that every link in the lifecycle is controllable, non-drifting, non-overstepping, and non-conflicting.
This is why when I look at Kite, I feel that what it truly fills in is not the blank of 'AI payment', but the layer of infrastructure that enterprise-level automation lacks the most:
AI task lifecycle governance (Lifecycle Governance for Autonomous Execution)
One, the task lifecycle of AI is far more complex than enterprises imagine
When a company gives a human employee a task, the employee executes a defined step.
When a company gives an AI a task, the AI will automatically 'expand the task into a tree structure'.
A simple 'return process'
AI will expand out:
Price comparison compensation
Cross-border tax calculation
Logistics path selection
Risk verification
Budget alignment
Supplier SLA judgment
Refund amount verification
Inventory synchronization
Reorder
Enterprises simply do not know how each task chain is generated.
Moreover, the task chain will continuously adjust with changes in context, resulting in:
The same task has different links
Different departments see different execution paths
Budget deduction timing is difficult to track
Risk control is dynamically skipped in the link
Cross-border steps are inserted in advance due to context changes
Supplier routing is rearranged due to changing conditions
This is not AI making mistakes, but an uncontrollable lifecycle.
If the lifecycle is opaque, companies cannot rest assured to let AI manage core processes.
Two, the underlying role of Passport: defining the 'legitimate entry' where the task lifecycle starts
Enterprises need to know:
Who initiated a task lifecycle?
Which Agent is it?
What permissions does it have?
What budget does it have?
What external resources are allowed to be called?
Can cross-border execution be done?
Can sensitive systems be accessed?
Can multiple Agent collaboration be triggered?
Passport is not an identity, but a lifecycle starting point definer.
It tells the system:
Whether the root node of this lifecycle is legitimate.
If the root node is not legitimate, the entire lifecycle should not exist.
Three, Modules are 'key control points' in lifecycle governance
The key to lifecycle governance is controlling key nodes, not tracking every step of the task chain.
Modules are essentially key node control structures:
The budget module controls resource nodes
Risk control module controls risk nodes
Path module controls routing nodes
Compliance module controls cross-border nodes
Payment module controls settlement nodes
Audit module controls verification nodes
These modules will not control how AI reasons, but will control:
Can the lifecycle continue
Where does the lifecycle stop
Can the lifecycle fork
Can the lifecycle call suppliers
Can the lifecycle modify the budget
Can the lifecycle trigger payments
In other words:
Modules are not link participants, but link 'valves'.
AI can dynamically generate task chains but cannot bypass valves.
The lifecycle thus has structured constraints.
Four, on-chain structure allows the entire lifecycle to have 'alignment'
What enterprises fear most is not task expansion, but:
Cannot align task chains
Cannot replay execution path
Cannot locate responsibility in the lifecycle
Cannot determine if the link has been tampered with
Cannot judge whether the behavior is overstepping
Cannot judge whether the rules have been bypassed
On-chain structure provides:
Unified fact source
Immutable records
Replay link
Comparable steps
Verifiable parameters
This turns the lifecycle from 'black box behavior' into 'structured objects'.
Five, why are stablecoins an indispensable element of lifecycle governance?
There are many nodes related to amounts in the lifecycle:
Budget deduction
Refund
Cross-border costs
Supplier settlement
Deposit freeze
Path cost judgment
If asset fluctuations occur, the decision logic of lifecycle nodes will drift:
The budget will be exhausted in advance
Risk thresholds may be mis-triggered
Cross-border priorities will be reversed
Supplier selection will become unstable
Settlement costs are unpredictable
This will lead to the lifecycle being completely inconsistent.
The significance of stablecoins is not 'paying more conveniently', but:
Keep the economic parameters in the lifecycle consistent, not distorted by market fluctuations.
Six, why I believe the lack of lifecycle governance is a pit that all Agent systems will inevitably fall into?
Because AI executes 'processes', not 'actions'.
Systems without lifecycle governance will exhibit:
Task repeated execution
Task chain expands infinitely
Tasks are modified repeatedly by different Agents
Budget is constantly being rewritten
Cross-border paths triggered multiple times
Supplier API has been breached
Risk control module triggers disorderly
Responsibility chain breakage
Execution results are unpredictable
Audit cannot align
This is not a model problem, but a lack of governance in the lifecycle.
Seven, Kite is not adding tools for AI, but adding systems for enterprises
Lifecycle governance belongs to institutional engineering, not functional engineering.
Passport determines whether the lifecycle can start
Modules determine whether the lifecycle can continue
On-chain structure determines whether the lifecycle can be verified
Stablecoins determine whether the lifecycle can be quantified
Permission boundaries determine whether the lifecycle can spread
Replay mechanisms determine whether the lifecycle is trustworthy
The structure of Kite is not for execution acceleration from beginning to end, but for adding constraints to the lifecycle.
This is also why I believe the underlying positioning of Kite is not 'AI payment chain', but:
AI Lifecycle Governance Layer (Automated Task Lifecycle Governance Layer)
What enterprises truly fear is not that AI executes slowly, but that the lifecycle is unexplainable, unverifiable, uncontrollable, and unauditable.
What Kite fills in is this layer.
