1. Control Surfaces for Automated Systems
Perhaps the most transformative application of MetaPolls is as parametric control systems for automated infrastructure. This creates a direct interface between collective preferences and executable code.
How It Works
The MetaPoll becomes a user interface that N people collectively operate to control various aspects of their shared systems. The ranked preferences generate variables that are passed directly to functions, smart contracts, or agent systems.
Consider what makes an effective control surface:
Explicit optionality - Include the full range of possible values, even when some seem obvious
Variable mapping - Design option titles that can be interpreted as function parameters
Automated execution - Connect poll results to code execution through APIs or smart contracts
Continuous adjustment - Focus on parameters that need ongoing community alignment
For example, in treasury management, we might define asset allocation parameters:
title [Treasury asset allocation]
options [
=Asset Allocation
==ETH
===100%
===100% to 70%
===69% to 30%
===29% to 10%
===0%
==USDT
===100%
===100% to 70%
===69% to 30%
===29% to 10%
===0%
==DAO token
===100%
===100% to 70%
===69% to 30%
===29% to 10%
===0%
]
This creates a direct mechanism for treasury rebalancing based on collective risk preferences. The community isn't voting on one-off allocation decisions but creating an ongoing sentiment stream that drives treasury composition.
The critical insight here is that explicit agreement, even on seemingly obvious choices, creates legitimacy and accountability. If ETH allocation is ranked highest with "100%" as the top sub-option, this creates a clear record of community intent that can be referenced when actions are taken.
Other examples of control surface applications include:
Community-controlled funding allocation
Automated market maker parameter adjustment
DAO governance rule calibration
Protocol parameter optimization
Community-driven AI agent direction
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