Governance Framework
Understand how GrantChain uses $GRANT and AI to coordinate upgrades, decisions, and proposals across the network.
Governance on most blockchains is slow, reactionary, and often captured by a few whales.
GrantChain changes that by introducing AI-assisted governance — where proposals are enhanced, simulated, and prioritized by machine intelligence, and decisions are made collectively through token-weighted voting.
🧠 AI Copilot for Governance
GrantChain includes a native Governance Copilot that helps coordinate decision-making by:
Scanning network activity and usage trends
Surfacing relevant proposals (e.g. model upgrades, treasury rebalances)
Suggesting actions based on simulation outcomes
Preventing spam or low-quality proposals
This turns governance from a passive process into an intelligent, proactive system.
⚙️ Proposal Flow
Submit — Anyone can propose a change: model, agent, parameter
AI Review — The Copilot scores and summarizes the proposal
Simulation — AI simulates the effect (economic, social, agent impact)
Vote — $GRANT holders vote with token-weighted power
Execute — If passed, it’s triggered on-chain
💬 Types of Proposals
Register new models or update existing ones
Approve or restrict specific agent behaviors
Modify marketplace fees
Allocate funds from the treasury
Upgrade agent frameworks or SDK standards
🪙 Voting Power & Staking
$GRANT must be staked to vote
The more staked, the more influence
Longer lockups = boosted weight
Stakers also gain priority access to AI compute resources
🧪 Coming Soon: Predictive Governance
GrantChain is developing predictive governance modules, where:
AI simulates different outcomes for a vote before it’s live
Community can preview projected impact
Bad proposals are filtered before they waste attention or gas
Think: “Simulate before you vote.”
With AI-powered foresight and intelligent participation, governance on GrantChain isn’t just democratic — it’s strategic, data-driven, and adaptive.
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