Community-Governed Moderation: Product Design for an Open-Source Content Filter

Quick Overview

Product design case on an open-source content filtering system whose rules are set by a decentralized community instead of one company. It tests scoping users and content, designing labeling, review and appeals, building governance that resists capture, handling illegal content, and choosing success metrics.

Community-Governed Moderation: Product Design for an Open-Source Content Filter

Company: Pagoda

Role: Product Manager

Category: Product Design & Strategy

Difficulty: medium

Interview Round: Other

Design an open-source system for filtering content in which a decentralized community, not a single company, sets and enforces the rules. Explain who it serves, how it works, how the community governs it, and how you would measure success. ```hint Separate deciding from enforcing With no central owner, nobody can remove content everywhere. Think about what the community decides, what each app or user does with that decision, and how a contested decision gets reversed. ``` ### Clarifying Questions - What content is being filtered: posts on a decentralized social network, listings in a marketplace, or anything that apps built on an open protocol publish? - Does "filtering" mean the community removes content, or that it publishes labels and filter lists that each app and user chooses whether to apply? - Who counts as the community, and how does someone gain a say: token holders, reviewers with earned reputation, or every user? - Is content that the law requires operators to remove quickly in scope, or handled outside the community process? ### What a Strong Answer Covers - A chosen content context, the user groups involved (end users, app developers, reviewers, creators) and a clear goal - How the system works: open rule sets and models, labeling, review, appeals and a public decision record, delivered to apps through an API or SDK - A governance model that resists capture, brigading and fake accounts, with a fast path for urgent threats - Handling of illegal content, reviewer incentives and wellbeing, and how quickly decisions take effect - Metrics for harmful-content exposure, decision accuracy and governance health ### Follow-up Questions - Spammers can read open-source rules too. How does the system stay effective when every rule is public? - Two parts of the community disagree about what is acceptable. How does your design handle that without splitting the network? - How would you stop a wealthy actor from acquiring enough voting power to rewrite the rules?

Overview: Product design case on an open-source content filtering system whose rules are set by a decentralized community instead of one company. It tests scoping users and content, designing labeling, review and appeals, building governance that resists capture, handling illegal content, and choosing success metrics.

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Pagoda
Feb 18, 2025
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Design an open-source system for filtering content in which a decentralized community, not a single company, sets and enforces the rules. Explain who it serves, how it works, how the community governs it, and how you would measure success.

Clarifying Questions Guidance

  • What content is being filtered: posts on a decentralized social network, listings in a marketplace, or anything that apps built on an open protocol publish?
  • Does "filtering" mean the community removes content, or that it publishes labels and filter lists that each app and user chooses whether to apply?
  • Who counts as the community, and how does someone gain a say: token holders, reviewers with earned reputation, or every user?
  • Is content that the law requires operators to remove quickly in scope, or handled outside the community process?

What a Strong Answer Covers Guidance

  • A chosen content context, the user groups involved (end users, app developers, reviewers, creators) and a clear goal
  • How the system works: open rule sets and models, labeling, review, appeals and a public decision record, delivered to apps through an API or SDK
  • A governance model that resists capture, brigading and fake accounts, with a fast path for urgent threats
  • Handling of illegal content, reviewer incentives and wellbeing, and how quickly decisions take effect
  • Metrics for harmful-content exposure, decision accuracy and governance health

Follow-up Questions Guidance

  • Spammers can read open-source rules too. How does the system stay effective when every rule is public?
  • Two parts of the community disagree about what is acceptable. How does your design handle that without splitting the network?
  • How would you stop a wealthy actor from acquiring enough voting power to rewrite the rules?