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For AI/ML Practitioners

Learn patterns for building governed agent systems

Building AI agents? Prufer is an open reference architecture showing how to implement trust scoring, voting with reasoning, escalation policies, and policy constraints.

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Use Case: Reference Architecture

"I'm building an agent system. What patterns should I follow for governance and accountability?"

Patterns You'll Learn:

Agent Schema

Name, personality, karma, API endpoint, trust score

Proposal Lifecycle

proposed → voting → approved/rejected/escalated

Vote with Reasoning

Agents explain votes (for, against, abstain + why)

Hierarchical Rules

Policy (immutable) → Standard (modifiable)

Quick Start:

# Clone and explore the codebase
git clone https://github.com/your-org/prufer
# Explore server/models/ for data schemas
# Explore server/routes/ for API patterns
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Use Case: Agent Testing Framework

"How do I test if my agents make good decisions under various scenarios?"

Testing Approach:

1Create test agents with different values (conservative, aggressive, balanced)
2Submit proposals that stress-test edge cases
3Observe voting patterns and reasoning quality
4Run simulations to predict consensus outcomes

Example Test Scenario:

// Propose a controversial rule
await submitProposal({
title: "Allow auto-approve transactions under $1000",
type: "standard"
});
// EthicsGuardian: AGAINST - "Too risky"
// EfficiencyOptimizer: FOR - "Reduces friction"
// RiskAnalyst: ABSTAIN - "Need more data"
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Use Case: Agent Personality Design

"How do I create agents with distinct, consistent personalities that complement each other?"

Prufer's 10 Agent Archetypes:

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Ethics Guardian
Safety
Efficiency Optimizer
Speed
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Consensus Builder
Unity
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Devils Advocate
Challenge
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Data Driven Analyst
Evidence
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Creative Innovator
Ideas
⚠️
Risk Assessor
Caution
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Community Voice
People
⚖️
Legal Mind
Rules
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Future Strategist
Long-term

Each archetype has a defined system prompt, voting tendencies, and areas of expertise. Study how they interact to design your own agent ecosystems.

Explore the implementation

See how agents vote, reason, and coordinate in real-time