How to Design a DAO Proposal Discussion and Feedback System

A DAO's governance lifecycle begins long before a formal on-chain vote. The proposal discussion and feedback phase is a critical, off-chain coordination layer where community members debate, refine, and build consensus. Unlike traditional corporate decision-making, this process is transparent, asynchronous, and open to all token holders or delegated representatives. A poorly designed system leads to voter apathy, rushed decisions, and contentious outcomes. This guide outlines the architectural principles and practical components for building a robust discussion framework that serves decentralized communities.

The core objective is to structure discourse to maximize signal and minimize noise. Effective systems guide participants through logical stages: from an initial Request for Comment (RFC) to gather early reactions, to a structured Temperature Check to gauge sentiment, and finally to a polished Governance Proposal ready for a snapshot. Platforms like Discourse forums, Commonwealth, and Snapshot's discussion feature are commonly used. Each stage should have clear entry criteria, a defined duration, and a templatized format that includes the proposal's motivation, specification, and financial implications.

Technical implementation involves integrating discussion threads with on-chain actions. For example, a bot can automatically create a forum post when a new Snapshot space is configured, or mirror on-chain vote results back into the discussion thread. Using interoperable standards is key. The OpenZeppelin Governor contract emits events that can be indexed to trigger forum updates. Similarly, discussion platforms can use the EIP-712 standard for off-chain signing to authenticate poster identities with their governance wallet, adding accountability and reducing spam.

Beyond basic posting, advanced features enhance decision quality. Sentiment analysis tools can parse discussion threads to provide real-time summaries of community stance. Quadratic voting can be applied to discussion polls to measure intensity of preference while mitigating whale dominance. Integrating a reputation system—where constructive feedback earns non-transferable points—can incentivize high-quality participation. The goal is to surface the most informed and widely-supported arguments, not just the loudest voices.

Finally, the system must be designed for security and finality. Discussion should happen on immutable, archived platforms to prevent revisionist history. There must be a clear, pre-defined pathway to move from discussion to an on-chain vote, preventing proposers from being arbitrarily blocked. The entire workflow, from forum post to executed transaction, should be documented as a public playbook. This transparency ensures the process itself is a trusted component of the DAO's governance, turning decentralized discussion into decisive action.

Designing a robust discussion and feedback system is a prerequisite for any functional DAO. This system manages the entire proposal lifecycle, from ideation and drafting to voting and execution. At its core, you need a mechanism for members to submit proposals, a forum for structured debate, a signaling mechanism for gauging sentiment, and a secure voting module to reach final decisions. Popular frameworks like OpenZeppelin Governor and Compound's Governor Bravo provide modular smart contract bases, but the discussion layer is often built off-chain to reduce gas costs and enable richer interaction.

The technical stack typically involves a combination of on-chain and off-chain components. You'll need a smart contract for proposal submission and execution (e.g., on Ethereum, Arbitrum, or Optimism), an indexer (like The Graph) to query proposal data, and a frontend client (often built with React/Next.js) for user interaction. The discussion forum itself can be built using tools like Discourse, Commonwealth, or a custom solution that posts feedback to a decentralized storage layer like IPFS or Arweave, with content hashes recorded on-chain for verifiability.

Key design decisions include defining proposal types (e.g., Treasury Spend, Parameter Change, Membership Vote), stages (Draft, Temperature Check, Formal Proposal), and permissions. You must decide who can create proposals (any token holder, a delegate, a multisig?) and what data each proposal contains: title, description, executable calldata, and discussion thread pointer. Establishing clear voting parameters upfront—such as voting delay, voting period, quorum, and vote thresholds—is critical, as changing them later requires a governance proposal itself.

For the feedback mechanism, consider implementing a snapshot or temperature check phase. This is an off-chain, gas-free vote using signed messages (via EIP-712 or Snapshot.org) to measure community sentiment before a costly on-chain proposal is submitted. This prevents governance spam and aligns expectations. The discussion system should link seamlessly to this, allowing arguments for/against to be tied to specific voting options and visible to all members.

Finally, you must integrate with token standards and delegation. Most DAOs use ERC-20 tokens for voting power (like UNI or COMP) or ERC-721 tokens for membership. The system must accurately read each member's voting weight, which may involve checking delegated balances via contracts like the ERC20Votes extension. Understanding these prerequisites ensures your discussion system is not just a forum, but a integrated piece of secure, executable governance.

The primary goal of a DAO proposal discussion system is to facilitate structured, transparent, and auditable conversations before an on-chain vote. Unlike traditional forums, these systems must integrate directly with the blockchain to verify membership, track reputation, and eventually trigger executable actions. The core architectural challenge is balancing decentralized participation with the need for spam prevention and signal clarity. Key design considerations include identity verification (e.g., token-gating with ERC-20/ERC-721), reputation weighting (e.g., based on token holdings or delegated voting power), and immutable record-keeping for audit trails.

A typical system architecture consists of three main layers. The smart contract layer on-chain manages permissions, stores proposal metadata, and finalizes outcomes. The indexing and data layer (using services like The Graph or Subsquid) queries and caches discussion data from the chain and IPFS. The application layer is the frontend interface where users interact. For example, a proposal might be created via a Snapshot space, with discussions hosted on a Discourse forum that is token-gated using Guild.xyz, and all final data referenced by an on-chain proposal contract on Arbitrum.

For the discussion data itself, storing large amounts of text or markdown directly on-chain is prohibitively expensive. The standard pattern is to use decentralized storage like IPFS or Arweave for the actual content (comments, drafts, attachments), while storing only the content hash (CID) and essential metadata on-chain. This creates a permanent, verifiable link. A smart contract for proposals might have a discussionURI field pointing to an IPFS hash containing a JSON object with the forum thread ID or a link to the discussion platform, ensuring the conversation is formally tied to the proposal.

Integrating feedback into the voting process is crucial. Systems can be designed to collect sentiment signals (e.g., temperature checks, pre-votes) that are displayed alongside the formal proposal. Some DAOs, like Optimism, use a separate voting contract for these signaling phases. The architecture should allow these soft consensus metrics to be easily visible to voters. Furthermore, enabling delegate communication is a advanced feature; delegates can publish their reasoning on their voting decisions, and the system can aggregate these views to inform other token holders, creating a more informed electorate.

Finally, consider spam and sybil resistance. Pure token-gating can be insufficient if proposal spam is a concern. Architectural additions include a proposal deposit (slashed for malicious posts), a minimum reputation score based on past participation, or a delegate-centric model where only elected delegates can initiate main discussions. The system should be designed to evolve; upgradeable proxy patterns for smart contracts and modular frontend components allow the DAO to iterate on its governance processes based on community feedback without requiring a full migration.

A robust discussion system is critical for DAO governance, allowing members to debate proposals before on-chain voting. Unlike traditional forums, a Web3-native system uses wallet authentication (e.g., via Sign-In with Ethereum or WalletConnect) to verify user identity and voting power. This creates a permissioned environment where comment visibility and influence can be tied to token holdings or governance NFT ownership. The core architecture typically involves a smart contract to manage proposal metadata and a decentralized database or indexer (like The Graph) to store and query the comment threads efficiently.

The comment data model must support threaded or nested replies to facilitate structured debate. A common approach uses a parentId field to link replies to a top-level comment or another reply. For on-chain storage, consider gas-efficient patterns: store only a content hash (like an IPFS CID) and essential metadata on-chain, while the full text resides off-chain. For example, you might emit a CommentAdded event from your governance contract containing proposalId, userAddress, parentCommentId, and contentURI. An off-chain listener then indexes this data into a queryable service.

Implementing wallet auth requires a backend service to validate EIP-4361 signatures (Sign-In with Ethereum). When a user connects their wallet, your frontend prompts them to sign a standard message. Your backend verifies this signature against the user's address, issuing a session token. This proves ownership without a centralized password. Libraries like next-auth with the EthereumProvider or siwe simplify this process. Always include a nonce and an expiration in the signed message to prevent replay attacks.

For the frontend, you need a library to manage nested comment rendering and state. Consider a recursive component that renders a comment and maps over its replies array. State management should track new drafts, pending transactions, and optimistic UI updates. When a user submits a comment, the app should: 1. Upload text to IPFS or Arweave via a service like web3.storage, 2. Get the returned CID, 3. Call the smart contract's addComment function with the CID and parentId, and 4. Update the UI optimistically before the transaction confirms.

Key security considerations include sybil resistance and spam prevention. You can gate commenting rights by checking the user's token balance directly from the contract view function or your indexer. Implement rate-limiting per address and consider a stake-based model where a small deposit is required to comment, refunded upon non-malicious participation. Moderation can be community-driven using a report-and-flag system, with ultimate arbitration tied to a DAO vote or a council of elected moderators.

For a complete stack example, combine: a Next.js frontend with wagmi and viem for wallet interaction, a Polygon smart contract for governance, The Graph for indexing comments, and IPFS for decentralized storage. This architecture ensures transparency, censorship-resistance, and aligns participant incentives with the DAO's success, moving beyond simple forums to integrated, on-chain-verifiable discourse.

A DAO proposal feedback system aggregates sentiment across multiple channels—forum posts, Discord threads, and on-chain signals—into a unified, analyzable dataset. The core components are a data ingestion layer that pulls from APIs (like Discourse, Snapshot, or Tally) and a sentiment analysis engine that processes the text. Using natural language processing (NLP) libraries such as Hugging Face's transformers or VADER, you can classify comments as positive, negative, or neutral and detect key themes like "security concern" or "budget objection." This structured data is then stored in a queryable database for real-time dashboards.

For on-chain context, integrate voting data from platforms like Tally or Snapshot. Cross-reference sentiment scores with voter addresses and delegate relationships to identify if concentrated negative forum sentiment correlates with a specific delegate's voting bloc. This reveals the difference between vocal minority concerns and silent majority support. A practical step is to use the Snapshot GraphQL API to fetch proposal and vote data, then join it with your sentiment dataset for a holistic view.

To implement a basic sentiment scorer, you can use a pre-trained model. Here's a Python example using the transformers library to analyze a proposal comment:

pythonCopy
from transformers import pipeline
sentiment_pipeline = pipeline("sentiment-analysis")
comment = "This proposal's budget seems excessive without clear milestones."
result = sentiment_pipeline(comment)
# Output: {'label': 'NEGATIVE', 'score': 0.98}

This score can be aggregated per proposal, weighted by the commenter's reputation or token holdings, to generate a composite sentiment index.

Design the system's output for clarity. A governance dashboard should display: the sentiment trend over time, a word cloud of frequent terms, and a breakdown of concerns by category. Tools like Dune Analytics for on-chain data or Metabase for internal dashboards are effective. The goal is to provide DAO delegates and authors with a clear, data-backed summary of community perception, enabling them to refine proposals or prepare rebuttals before a final vote.

Finally, consider feedback loops. The system should notify proposal authors when sentiment shifts dramatically or when a new, prevalent concern emerges. Automate this with webhooks to Discord or Telegram. By closing the loop between discussion and proposal iteration, you create a responsive governance process that values qualitative input as much as quantitative voting, leading to higher-quality decisions and increased community engagement.

An effective DAO proposal system moves beyond a simple forum post and snapshot vote. It requires a structured lifecycle: a pre-proposal discussion phase for ideation, a formal proposal submission with executable code or clear directives, a dedicated feedback and amendment period, and finally on-chain execution. Platforms like Discourse, Commonwealth, and Tally provide the foundational tools, but the design of the process itself dictates governance quality. The goal is to surface signal, build consensus, and catch critical flaws before assets are committed.

Implement proposal section tagging to categorize and filter discussions. Tags like #temp-check, #protocol-upgrade, #grant-request, or #parameter-change help delegates and tokenholders triage proposals based on their expertise and interest. This metadata can be enforced during submission via smart contracts or bot moderation. For example, a proposal to adjust Aave's reserveFactor might carry tags #aave-v3, #risk-params, and #mainnet. Linking these tags to relevant forum channels or Discord threads creates a navigable knowledge graph for the DAO's decision history.

The discussion phase must be anchored to a single source of truth. Use immutable content identifiers like IPFS CIDs (stored on-chain in the proposal contract) or commit hashes for code changes. All feedback and suggested amendments should reference specific lines or sections of this canonical version. Tools like Snapshot's editable proposals with version history or GitHub Pull Requests for code-heavy changes provide this traceability. This prevents confusion and ensures voters are reviewing the same material.

Incorporate structured feedback mechanisms directly into the interface. Beyond free-form comments, include sentiment polls (For/Against/Abstain with reason), inline annotations on proposal text, and mandatory fields for technical or financial review. For technical proposals, a template might require sections for Code Audit Link, Risk Assessment, Budget Breakdown, and Post-Implementation Monitoring. Automating checks for these requirements ensures minimum quality standards before a proposal reaches a full vote.

Finally, link the discussion outcome directly to the voting action. The voting interface on Tally or Sybil should display key discussion metrics: the participation rate of top delegates, a summary of major objections, and the final amended version of the proposal. This closes the feedback loop, giving voters clear context. Smart contracts can even enforce a mandatory review period; a Governor contract might require a proposal's discussionThread field to point to a thread with minimum activity before the propose() function succeeds.

The primary goal is to structure discussions to reduce noise and surface signal. A flat comment thread, common in forums, becomes unusable for complex proposals. Instead, implement a threaded or nested comment system that allows users to reply to specific arguments. Each top-level comment should represent a distinct point of contention or support, such as "Budget Concerns" or "Technical Feasibility." This structure mirrors the natural flow of parliamentary debate and helps voters quickly assess the strength of competing viewpoints. Platforms like Commonwealth and Snapshot's Discourse integration employ this model.

Integrate sentiment and stance aggregation directly into the UI. Beyond simple upvotes/downvotes, allow users to tag their sentiment (e.g., Support, Oppose, Needs Revision) on specific comments or the proposal itself. Visually aggregate these signals—using color-coded bars or tally counters—to give an at-a-glance read of community sentiment. This turns qualitative discussion into quantitative data, helping proposal authors identify key objections and voters gauge consensus. For example, a comment with 50 Support and 200 Needs Revision tags clearly indicates a popular concern that requires addressing before the final vote.

On-chain context is non-negotiable. The discussion UI must display immutable, verified information alongside comments. This includes the proposer's token-weighted voting power, their delegation history, and links to the on-chain transaction for proposal submission. For technical proposals, embed a read-only view of the calldata or a link to a block explorer. This transparency combats misinformation and allows participants to assess the proposer's stake in the outcome. Use wallet-connection libraries like ConnectKit or RainbowKit to seamlessly pull this on-chain data into the frontend.

Implement real-time updates and notifications to maintain engagement. Users should receive browser or push notifications (via services like Push Protocol) for replies to their comments, @mentions, or when a proposal they're following enters a new stage. The interface should use WebSocket connections or frequent polling to update comment counts and sentiment tallies without requiring a page refresh. This creates a live, collaborative environment that mimics the immediacy of a community call, encouraging more dynamic and timely feedback throughout the proposal's lifecycle.

Finally, design for accessibility and multi-platform use. Governance participants may engage from mobile devices. Ensure the commenting interface is responsive and uses clear, legible typography. Provide keyboard navigation for power users and support for screen readers. Consider offering an email digest option for members who prefer to follow discussions asynchronously. The barrier to participation should be as low as possible; a clunky or inaccessible UI will silence valuable community voices and skew governance toward a technically adept minority.

A well-designed discussion system is a force multiplier for DAO governance. By implementing the stages outlined—pre-proposal forums, structured feedback, and post-vote analysis—you create a transparent, informed, and participatory environment. This reduces governance overhead and increases the quality of proposals that reach a final vote. Tools like Discourse, Commonwealth, or custom-built solutions using Lens Protocol or Farcaster Frames can serve as the foundational layer for these discussions.

For developers, the next step is to connect the discussion system to on-chain actions. This typically involves building a snapshot or Tally-like interface that references discussion threads via IPFS hashes or API endpoints. The key technical integration is ensuring each on-chain proposal has a unique identifier that maps directly to its off-chain discussion. Smart contracts for voting, such as OpenZeppelin's Governor contracts, should be configured to accept proposals only after a minimum discussion period has elapsed and feedback thresholds are met.

Consider implementing reputation-weighted or token-curated feedback to surface high-quality insights. For example, you could use ERC-20 token holdings or a non-transferable ERC-721 "contributor" badge to weight comments. A next-level feature is automated sentiment analysis on discussion threads using OpenAI or similar APIs to provide proposal authors with a summarized report of community sentiment before final submission.

Finally, measure your system's success with clear metrics: proposal quality (reduced amendment requests post-submission), participation rate (percentage of token holders commenting), and decision velocity (time from discussion start to execution). Continuously iterate based on these metrics. The goal is not just to talk, but to structure conversation that leads to better, executable on-chain decisions.