This ensures every completed Mission distributes funds according to the protocol rules.
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4/ Every task can only be paid once
One feature I really liked is the protection against duplicate payments.
Once a task has been settled successfully, it can never be settled again.
That provides an important safeguard against accidental double payments.
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5/ Security comes before payment
Before releasing any funds, the contract verifies:
the Mission exists,
the task has completed,
treasury settings match,
and settlement hasn’t already happened.
Only then are the funds released.
This helps ensure payments remain accurate and secure. Pasted text.txt
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6/ 🧩 Code Spotlight
One simple line captures the entire purpose of this contract:
if (_settled[nodeId]) revert AlreadySettled(nodeId);
In simple English:
Every completed task can only ever be paid once.
That one safeguard protects the protocol against duplicate settlements and accidental double spending.
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7/ The bigger picture
SettlementModule completes the economic side of every Mission.
Once work has been successfully completed and verified, it calculates the final payout, applies reputation adjustments, distributes fees, and ensures funds are released securely only once.
In simple English:
It’s the contract that turns successful AI work into trusted on-chain payments.
But building an AI economy isn’t just about paying for work.
As the network grows, its own rules will need to evolve.
How are new ideas proposed?
Who reviews them?
How do they eventually become official protocol rules?
The governance engine that guides proposals through review, voting, constitutional checks and final implementation before they become part of AgentCity.
As AgentCity grows, its rules won’t stay the same forever.
New ideas will need to be proposed.
Reviewed.
Debated.
Voted on.
And, if approved, safely introduced into the network.
That’s exactly what LegislativePipeline is designed to manage.
Rather than allowing protocol changes to happen instantly, it guides every proposal through a structured governance process before it can become part of AgentCity.
We’ve already seen how AgentCity allows AI agents to collaborate on complex tasks and how GateModule decides whether a task can continue through the workflow.
But one question still remains.
How can the network trust that an AI agent has actually produced the correct result?
That’s exactly what VerificationModule is designed to answer.