On January 19, 2026, at 8:00 AM UTC+8, Ethereum co-founder Vitalik Buterin posted a series of messages on X, systematically criticizing the current mainstream DAO governance model and offering several improvement directions that he believes have been long overlooked. On the surface, this appears to be a technical review of the "token holder voting + treasury management" model, but it reflects a renewed confrontation between the ideals of decentralized governance and the reality of its implementation: DAOs were supposed to be experimental grounds for open collaboration and collective decision-making, yet they are often criticized for being inefficient and controlled by a minority, functioning merely as treasury voting machines. Vitalik attempts to shift the discussion from "what to vote on and how much to manage" to "how to discuss, how to protect participants, and who bears the decision-making burden," incorporating communication layers, ZK privacy, and AI tools into the design space of DAOs, pointing towards a new governance paradigm: transitioning from a single voting mechanism to a multi-layered, multi-tool collaborative autonomous structure.
The Gap from Ideal Autonomy to Treasury Voting Machines
In recent years, the governance of most Ethereum ecosystem DAOs has revolved around a highly singular paradigm: addresses holding governance tokens can vote on proposals, with the core content of proposals often focused on financial decisions such as treasury fund usage, budget approvals, and incentive distributions. On the surface, any token holder enjoys equal proposal and voting rights, but the actual operational outcome is that governance activities heavily rely on on-chain voting interfaces and multi-signature treasury control, compressing the community into a back-and-forth between voting pages and treasury panels. This structure was initially seen as an innovation that was "transparent and auditable," but as project sizes grew, problems began to emerge: voting frequency increased, proposals became more fragmented, yet participants grew increasingly fatigued, leading to a continuous decline in voter turnout.
In this round of posts, Vitalik directly pointed out the structural flaws of this model. He believes that simplifying governance to "token-weighted voting + treasury control" can easily evolve into governance capture by a minority of large holders or interest groups. On one hand, voting rights are directly tied to the number of tokens, allowing wealthy individuals or institutions to easily dominate key proposals; on the other hand, ordinary participants find it difficult to invest enough time and energy to understand the details of high-frequency, technical proposals, often opting to follow leading opinions or abstain entirely, further exacerbating power concentration. A deeper issue is that the daily operations of DAOs increasingly resemble a "budget approval committee," with a large number of governance agendas revolving around subsidy issuance and expenditure approvals, while in-depth discussions involving vision, rules, and product paths are continuously marginalized, reducing autonomous communities to machines that distribute funds quarterly, starkly contrasting with early expectations of "self-organization and autonomy."
Absence of Communication Layer: DAOs Reduced to Voting and Results
In response to this imbalance, Vitalik proposed a key module that has long been absent in DAO design—the communication layer. In his narrative, a healthy governance process should not start with "initiating on-chain voting," but rather with sufficient discussion, interest coordination, and proposal refinement before the proposal stage. If there is only a voting interface without a systematic communication layer, governance will devolve into a series of disconnected, information-asymmetric voting events. In traditional community governance, whether in urban planning hearings or corporate board meetings, there is usually a long period of topic clarification, opinion exchange, and compromise negotiation before formal voting, whereas many DAOs jump directly from a post on a forum or social media to on-chain voting, with very weak filtering and sedimentation processes in between.
In reality, DAOs do have multiple off-chain communication venues—Discord, Telegram groups, X timelines, forum sections, etc.—but these tools are mostly designed for "ordinary socializing" and have not undergone structural transformation for governance decision-making. The result is a fragmented and platform-disconnected information flow: very few members have the time to deeply read long forum posts, and most receive second-hand interpretations in a fragmented manner through social media, naturally concentrating discourse power among a few high-frequency speakers, core developers, or influential KOLs. The disagreements, alternative solutions, and trade-off details behind proposals are difficult to systematically record and trace back, and even if participants want to understand seriously, they lack a clear knowledge pathway.
In the more complete communication layer envisioned by Vitalik, proposals are no longer "finished products" suddenly thrown out by a certain address, but rather a process where topics gradually take shape both off-chain and on-chain: initial ideas can be questioned, supplemented, and rewritten in public spaces, dissenting opinions and minority viewpoints receive clear display positions, and supporters and opponents can engage in multiple rounds of debate around key parameters and potential risks; only when discussions gradually converge does the proposal enter the formal on-chain voting stage, with the key points, evidence, and compromise solutions from off-chain debates attached to the proposal in a traceable manner. This intertwined communication layer of on-chain and off-chain is not simply about adding a new tool, but about inserting time for "understanding" and "negotiation" into the governance process, transforming voting from an isolated event into a part of a continuous narrative.
ZK Privacy Emerges: Reassessing Voting Security
While reconstructing the communication layer, Vitalik also emphasized another long-underestimated prerequisite—the privacy and security of voting. In this round of expression, he clearly pointed out that DAOs need to systematically address privacy issues, as completely public and traceable voting records can create pressure or even retaliation risks for participants in reality. For stakeholders with resources or connections, it is not difficult to check a certain address's position on key controversial proposals, which forces many members to consider "will this offend someone" when voting, rather than simply assessing what is more beneficial for the project.
In this regard, Vitalik places some hope in the application potential of ZK technology. He did not provide a specific technical path for implementation but emphasized a direction: using zero-knowledge proofs to achieve anonymous voting and confidential preference expression, while ensuring that the overall results are verifiable, minimizing the risk of pinpointing individual addresses' positions. At the same time, ZK tools are also expected to alleviate issues like vote buying and coercive voting, making it more difficult for external parties to exploit the binding relationship between "what votes were cast" and "who cast the votes" through more complex commitment structures and verification methods. Since the briefing did not disclose specific protocol designs and parameter settings, related implementations remain at the level of principles and trends.
Once the privacy dimension is strengthened, the behavioral incentives within the DAO may also change accordingly. Some members who previously chose to abstain or "go with the flow" may be more willing to express their true preferences due to concerns about reduced anonymity, allowing minority opinions and dissenting votes to gain more breathing space. For those holding a large amount of voting power, the difficulty of organizing vote-buying and clearly delineating factions will significantly increase under conditions where "who supported whom" cannot be easily verified, raising the cost of governance capture. More importantly, when participants believe they will not face public backlash or resource blockades for an ill-timed vote, their willingness to engage in governance over the long term is also expected to rise, which overall helps alleviate the "silent majority" problem, shifting the decision-making structure of DAOs from polarized mobilization confrontations to a richer and more decentralized spectrum of preferences.
AI is Not a New Dictator: Alleviating Decision Fatigue Rather Than Making Decisions for People
Even with a more secure voting mechanism and a more robust communication layer, DAOs still face a real bottleneck: decision fatigue. Vitalik repeatedly mentioned in this round of posts that as the number and complexity of proposals a community needs to handle continue to rise, the time and attention of ordinary participants clearly cannot keep up. Faced with a barrage of budget requests, protocol parameter adjustments, partner introductions, and technical upgrade proposals, most people neither have the energy to delve into each one nor can they maintain long-term rational judgment output, resulting in either mechanical following of "recommended vote warehouses" or complete disengagement, with voting rights subtly shifting towards a minority of "time-rich, information-advantaged" groups.
In this context, Vitalik turns his attention to AI, but he clearly emphasizes that AI should be viewed as an enhancement tool, not a new dictator replacing human judgment in DAO governance. The scenarios he envisions resemble a layered assistant system: at the outer layer, AI can help participants automatically categorize and cluster a large number of proposals, bundling highly similar or related topics to avoid information being drowned in fragmentation; at a deeper level, AI can generate risk alerts and summaries tailored to different roles, simplifying technical details for members with weak technical backgrounds and highlighting potential vulnerabilities and uncertainties for risk-sensitive members. On this basis, AI can also rank and filter proposals based on individual past voting behavior and areas of interest, reducing the unrealistic expectation that "every DAO member must understand all proposals from scratch."
However, any proposal to introduce AI into governance must confront risks and boundary issues. The training data and algorithm biases of the model itself may amplify certain positions in "recommended summaries" while systematically ignoring others; if only a few technical elites control the model's tuning and deployment rights, they inadvertently gain control over a "discourse filter," partially black-boxing what should be a transparent governance process. Vitalik's attitude is closer to a cautious engineering perspective: AI can alleviate information overload and improve understanding efficiency before decision-making, but the final stance and voting must still be made by human members under public rules, and the input and output pathways of model participation should be recorded and auditable as much as possible to prevent "technical intermediaries" from quietly becoming new power centers.
Convex and Concave: Vitalik's View of DAO Risk Curves and Design Trade-offs
To provide a unified analytical framework for these dispersed improvement directions, Vitalik once again borrowed a concept he has frequently used in recent years—convex and concave. In his understanding, some types of decisions are naturally suited to be entrusted to highly decentralized groups, pursuing excess returns through "diversification + trial and error," corresponding to a convex risk curve: individual judgments, even if significantly deviated, can still yield unexpected positive results in the long term as long as the system is not destroyed in one fell swoop. Conversely, some decisions are closer to a concave risk structure, where extreme errors can lead to irreversible losses, making "robustness" and "preventing extreme failures" far more important than "pursuing surprise successes."
In specific scenarios such as oracle improvements, on-chain dispute resolution, and long-term protocol maintenance, the differences in these risk curves are particularly evident. Adjustments to oracle mechanisms concern the entire system's perception of the external world, and a serious error could lead to large-scale liquidations or asset mismatches; such decisions clearly require more robust structures, higher scrutiny thresholds, and stronger accountability bindings. On-chain dispute resolution exhibits both convex and concave characteristics: it requires diverse perspectives and case accumulation to drive rule evolution while ensuring that individual case rulings are not completely unbalanced by emotional influences; as for long-term maintenance and upgrade planning of protocols, it leans more towards the concave risk of "avoiding long-term erosion," often needing to find an appropriate division of labor between open participation and professional review to prevent the accumulation of technical debt and maintain a balance between security and usability.
Within this framework, the communication layer, ZK privacy, and AI tools are not isolated functional points but rather a complete set of governance views centered around "avoiding extreme failures and expanding moderate successes." The communication layer allows for more information and viewpoints to be fully exchanged and recorded before decision-making, reducing the likelihood of extreme errors caused by misunderstandings and information blockages; ZK privacy lowers the chances of voting being distorted by fear and retaliation, enabling the system to capture the true preference distribution even when facing controversial topics; AI tools alleviate participation thresholds and decision fatigue without usurping decision-making power, distributing the information processing capabilities that originally belonged only to a few "full-time governors" to ordinary members in a smoother manner. By establishing different "buffer layers" across various risk curves, DAOs can maintain openness and diversity while reducing the probability of being overwhelmed by a single catastrophic decision, leaving more space for those less flashy but consistently positive moderate success cases.
The Next Chapter of DAO: From Voting Tools to Multi-Layer Governance Infrastructure
From this round of posts, it is clear that the core message Vitalik conveys is very straightforward: the DAO paradigm supported solely by token voting and treasury management has reached a bottleneck. What the ecosystem needs is more types of DAOs with more refined designs, rather than continuously building new treasuries and governance pages on the same template. From the absence of a communication layer to insufficient privacy protection, and the ongoing exacerbation of decision fatigue, these issues do not stem from any specific protocol or project team, but are a natural result of an overly singular design philosophy. If DAOs continue to operate at the level of "whoever holds the tokens has the say, and once the vote is done, the money is distributed," it will be difficult to undertake more complex and long-term collaborative tasks.
Based on this, an increasingly clear judgment is: whoever can take the lead in creating replicable governance examples in communication layers, privacy mechanisms, and AI collaboration will have a better chance of becoming the next generation of infrastructure-level DAOs, regardless of whether it ultimately exists in the form of a protocol, platform, or toolset. A DAO with a strong communication layer may become the governance hub for other organizations; a DAO that establishes standards in ZK voting and privacy preference expression may output universal governance components; and those projects that successfully tame AI to reduce the burden on participants within transparent rules are expected to gain advantages in both decision-making efficiency and participation breadth.
The dimensions worth observing next include the specific timelines for the new round of DAO experiments, as well as the community's genuine feedback on the adoption of ZK and AI governance tools. Whether representative communication layer protocols will emerge on-chain, whether we will see the large-scale deployment of privacy voting in medium to large DAOs, and whether participants are willing to trust and use AI-based proposal summaries and risk alerts will all determine how far this vision of the "next chapter of DAO" can go. Regardless of the outcome, this renewed discussion on DAO design in early 2026 has shifted the focus from a singular token voting mechanism to a broader imaginative space for governance infrastructure.
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