Recently, while looking at the multi-Agent workflows being piloted within enterprises, one detail has been repeatedly mentioned:
Enterprises are not concerned about AI executing slowly or inaccurately; their biggest concern is that every task initiated by AI cannot be proven to be genuinely authorized.
You let an Agent execute the payment task
Another Agent runs the approval logic
Let another Agent trigger cross-border calls
The task transfer between them is automated
But enterprises cannot verify which part of the task chain is genuinely authorized and which is inferred by the model.
As long as AI can expand steps, derive tasks, and rewrite intentions in the link, a structural risk will arise:
Which action is authorized for execution?
Which action was added by AI itself?
Which task source is real business and which is generated by misjudgment?
Companies must know one thing for accountability, audits, compliance, and financial accounting:
Who generated the task, how it was forwarded, and who 'signed' it during execution.
But AI will not 'sign'.
AI will not say 'This is a task I officially initiated'.
AI will not leave intention signatures before execution.
This explains why the more I look at Kite, the more I feel it is not an 'AI payment chain'.
What it does is something more critical:
Ensure that every execution action of AI must carry a 'verifiable task signature'.
1. AI's task generation mechanism naturally lacks 'task legitimacy proof'
This point is the easiest pitfall for companies when implementing AI.
Model inference has probabilistic nature
Agent links will self-expand
Context will shift during execution
External APIs provide inconsistent input
Multiple Agents will rewrite plans for each other
The orchestration system will merge and split tasks
Thus a originally simple action:
"Book a flight"
Will automatically derive a dozen tasks:
Change hotels, compare prices, adjust travel times, update budgets, check visas, trigger insurance recommendations...
If there is no signature layer, companies cannot determine:
Which tasks belong to the real execution chain
Which tasks are derived inferences
Which tasks belong to exceeding authority expansion
Which tasks should not be executed at all
Even companies may not know:
Is this the same task chain?
Who is the person rewriting in the middle?
Is the task forged?
Kite's idea is: tasks must be signed, and execution must be structured.
2. Passport is the first layer of task signatures: determining 'who is initiating the task'
I observed for a while that the role of Passport has never been 'to issue credentials to Agents'.
What it really decides is:
Whether this task comes from an execution subject recognized by the company.
This means:
Tasks cannot be anonymous
Tasks cannot be forged
Tasks cannot be impersonated
Tasks must point to an authorized, limited, and bounded subject.
From the enterprise perspective, this is 'task initiation legitimacy'.
Without legitimacy, audits cannot start, audits cannot be implemented, and responsibilities cannot be defined.
Passport turns 'what AI wants to do' into 'whether AI is allowed to do it'.
This is the entry point of task signatures.
3. Modules are the second layer of task signatures: determining 'whether this task meets execution conditions'
Traditional software performs multiple checks before executing tasks:
Parameter verification, permission validation, status checks, risk control filtering.
But AI will not verify these itself; it will only think it is 'reasoning correctly'.
Modules do not add functionality, but provide verifiable execution trajectories for tasks:
Budget Module: Prove this task is within budget
Risk Control Module: Prove this task has not triggered risks
Path Module: Prove it chose a compliant path
Compliance Module: Prove regional strategy is met
Audit Module: Prove execution steps are fully recorded
In other words, each module is equivalent to 'stamping' on the task:
This task is legitimate
This task is executable
This task has not exceeded authority
This task meets corporate strategy
The execution reason of this task is verifiable
The more modules, the more complete the task signature.
4. The most challenging part of task signatures: the execution link must be replayable, traceable, and alignable.
Companies will not only ask:
"Why was this task executed?"
Companies will ask in more detail:
"If I let you replay, can you generate the same task chain completely?"
Can every calling parameter be proven?
Has anyone modified the task in the link?
"Is there a concurrency conflict?"
"Where is the responsibility node?"
Traditional systems cannot satisfy 'replayable execution links' because AI's execution is probabilistic and context-driven.
And Kite's on-chain mechanism solves this problem:
Each task signature
Each module judges
Each payment action
Each path selection
Each budget deduction
Each cross-border judgment
All forced into a chain structure, making execution rely not on model output but on facts on the chain.
The ultimate goal of task signatures is not 'recording', but:
Execution Consistency
Behavior is reproducible
Responsibilities can be pinpointed
Path can be compared
Parameters can be aligned
This is the biggest challenge for automated systems.
5. The role of stablecoins is not payment, but to make task signatures economically verifiable.
If the task signature involves amounts and the amounts fluctuate, it will undermine the verifiability of the signature.
What companies fear the most is:
The same task executed at different times incurs different costs
Different Agents executing the same link generate different costs
Cross-border processes lead to inconsistent results due to price shifts
Stablecoins eliminate all of this.
It gives task signatures:
Deterministic Amount
Fixed Economic Impact
Comparable settlement results
Execution consequences that do not vary with market fluctuations
This makes task signatures a real verifiable on-chain object, rather than a vague process record.
6. Why I believe that all scaled Agent systems in the future must have a 'task signature layer'
Because without task signatures, there is no:
Compliance
Responsibility Attribution
Audit Link
Process Reproduction
Conflict Resolution
Cross-Organization Collaboration
Cross-Border Execution
Process Approval
Risk Contrast
Budget Verification
Companies cannot allow a system without signature capabilities to execute real tasks.
The task signature layer will become:
The core of AI execution governance
Key component of automated enterprise architecture
The minimum requirement for cross-organization Agent collaboration
And now in the entire industry, only Kite is doing on-chain versions of task signatures.
7. If AI automation is to enter the core processes of enterprises, what Kite does is that irreplaceable foundational layer
It is not about payment
Not about identity
Not about routing
Not about narrative
What it does is:
Ensure that every automated task has legitimacy, verifiability, auditability, and executability.
Without this layer, companies will never be able to scale AI to execute real actions.
Once this layer is built, it becomes the core infrastructure of the automation era.
