1. Control Surfaces for Automated Systems

Intro

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.

Control surfaces function as organizational cockpits: arrays of levers and dials that communities can collectively manipulate. In this analogy, the organization is the aircraft, and MetaPoll provides the instrumentation panel. What's unprecedented is our ability to compress the distributed intelligence of millions into a single coherent signal—achieving the clarity of CEO-level decision-making while preserving the collective wisdom of the crowd.

The key insight is coherent aggregation: transforming cacophonous individual preferences into actionable organizational direction.

Traditional governance either suffers from executive bottlenecks (one person decides) or coordination chaos (everyone decides). MetaPoll threads this needle by creating structured preference revelation mechanisms that scale.

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.

For example, in treasury management, we might define asset allocation parameters:

title [Treasury asset allocation]
options [
=Asset Allocation
==ETH
===100%
===90% to 70%
===69% to 30%
===29% to 10%
===0%
==USDT
===100%
===90% to 70%
===69% to 30%
===29% to 10%
===0%
==DAO token
===100%
===90% to 70%
===69% to 30%
===29% to 10%
===0%
]

Expand here for the full MetaPoll Example:

title [Member Desired Treasury Management]
options [
= Spending Priorities
== Spending Area
=== Research and Development
==== High Spend
==== Medium Spend
==== Low Spend
==== No Spend
=== Administration
==== High Spend
==== Medium Spend
==== Low Spend
=== Existing Products
==== High Spend
==== Medium Spend
==== Low Spend
=== Operating Expenses
==== High Spend
==== Medium Spend
==== Low Spend
== Spending Budgets
=== Core team salaries
==== Nothing
==== 0.1% of Treasury
==== 0.2% of Treasury
==== 0.5% of Treasury
==== 1% of Treasury
==== 2% of Treasury
==== 3% of Treasury
==== More than 3%
=== Incoming Proposals
==== Nothing
==== 0.1% of Treasury
==== 0.2% of Treasury
==== 0.5% of Treasury
==== 1% of Treasury
==== 2% of Treasury
==== 3% of Treasury
==== More than 3%
=== Grant Allocation
==== Nothing
==== 0.1% of Treasury
==== 0.2% of Treasury
==== 0.5% of Treasury
==== 1% of Treasury
==== 2% of Treasury
==== 3% of Treasury
==== More than 3%
= Treasury Size
== Rapidly Increasing
== Steadily Increasing
== Maintaining
== Steadily Decreasing
== Rapidly Decreasing
= Treasury Pricing
== ETH
== USD
== ENS
== Other
= Asset composition
== ETH
=== 0%
=== 5%
=== 10%
=== 20%
=== 30%
=== 40%
=== 50%
=== 60%
=== 70%
=== 80%
=== 90%
=== 100%
== ENS
=== 0%
=== 5%
=== 10%
=== 20%
=== 30%
=== 40%
=== 50%
=== 60%
=== 70%
=== 80%
=== 90%
=== 100%
== USDT
=== 0%
=== 5%
=== 10%
=== 20%
=== 30%
=== 40%
=== 50%
=== 60%
=== 70%
=== 80%
=== 90%
=== 100%
== USDC
=== 0%
=== 5%
=== 10%
=== 20%
=== 30%
=== 40%
=== 50%
=== 60%
=== 70%
=== 80%
=== 90%
=== 100%
== Other Stables
=== 0%
=== 5%
=== 10%
=== 20%
=== 30%
=== 40%
=== 50%
=== 60%
=== 70%
=== 80%
=== 90%
=== 100%
== Other Tokens
=== 0%
=== 5%
=== 10%
=== 20%
=== 30%
=== 40%
=== 50%
=== 60%
=== 70%
=== 80%
=== 90%
=== 100%
= Defi Revenue
== Usage of Treasury
=== No use of Treasury
=== Up to 1% of Treasury
=== Up to 2% of Treasury
=== Up to 3% of Treasury
=== Up to 5% of Treasury
=== Up to 10% of Treasury
=== Up to 20% of Treasury
=== Up to 30% of Treasury
== Target APY
=== Above Average
=== Market Average
=== Below Average
== Volatility
=== High
=== Medium
=== Low
= Rebalance Strategy
== Target Slippage Fee
=== 0.5% Max
=== 1% Max
=== 2% Max
=== 3% Max
=== 4% Max
=== 5% Max
== Rebalance Method
=== Time based
==== Daily
==== Weekly
==== Monthly
==== Quarterly
==== Semi-Annually
==== Annually
=== Value based
==== > 0.5% off balance
==== > 1% off balance
==== > 3% off balance
==== > 5% off balance
==== > 10% off balance
==== > 15% off balance
==== > 20% off balance
]

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.

When to use control surfaces

• 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

Thinking about possibilities

dynamic budget allocation where community members adjust spending priorities in real-time, with changes reflected immediately in organizational resource flows. Or multi-dimensional policy spaces where voters navigate trade-offs between competing values, generating nuanced mandates rather than binary choices.

The control surface metaphor captures something essential—governance as continuous adjustment rather than discrete elections. MetaPoll is a new collective intelligence that can operate at the speed and scale that our interconnected world demands.