In March 2025, Optimism launched a milestone on-chain governance experiment. By distributing 500,000 OP tokens through the Futarchy mechanism, this 21-day social experiment not only tested the feasibility of prediction markets in public chain ecological governance but also revealed the complex tensions in the evolution of decentralized decision-making mechanisms.

01. Futarchy Governance Experiment

In March, Optimism introduced a novel Futarchy governance experiment. The literal translation of Futarchy is "prediction experiment." In the blockchain context, Futarchy is a governance model that guides decision-making through prediction markets, leveraging the predictive capabilities of financial markets and the real monetary investments of participants to incentivize more accurate predictions and analyses. In this experiment, Optimism used the Futarchy method to allocate a total of 500k OP (100k * 5) in incentives to explore a new model for incentivizing ecological development in public chains. Most of the experiment's progress has been completed, and LXDAO member Loxia, as one of the participants, expressed cautious optimism about the future of this governance method.

The Futarchy proposed by MetaDAO simply states that when someone proposes a governance goal (e.g., "airdrop tokens to incentivize users"), Futarchy will define two conditions in the token market: "approve" and "reject." Participants must stake real assets to exchange for corresponding tokens for trading—if they are optimistic about the proposal, they will drive up the price of the "approve" market token; conversely, they will bet on the "reject" market. Ultimately, the fate of the proposal is determined by comparing the weighted average prices of the two markets, while participants can redeem their staked assets, but the decision outcome directly affects the value of their holdings. This design cleverly binds individual interests with collective goals:

To profit, one must deeply study the long-term impact of the proposal on the organization's token price, rather than relying on intuition or following the crowd. MetaDAO's practice shows that even if malicious proposers attempt to manipulate the market, they will incur losses due to the need to buy "approve" tokens at high prices. MetaDAO believes that when every decision is refined through real monetary stakes, collective wisdom has a chance to overcome human weaknesses.

02. Origin of Futarchy

Futarchy is a form of government proposed by economist Robin Hanson. In this governance model, elected officials define the metrics for national welfare, while prediction markets are used to determine which policies will have the most positive impact. The New York Times listed "Futarchy" as a buzzword in 2008. Later, this concept was also introduced into discussions about blockchain and DAOs.

The slogan of Futarchy is:

"Vote on values, bet on beliefs." This means:

Citizens should express "what we want" (i.e., "values") through democratic processes.

Then, use prediction markets to determine "which policies are most likely to achieve these goals" (i.e., "beliefs"—judgments about causal relationships).

Economist Tyler Cowen stated, "I am not optimistic about the future of Futarchy, or whether it can succeed once implemented. Robin says, 'Vote on values, bet on beliefs,' but I believe that values and beliefs cannot be so easily separated."

Cowen argues that human values and beliefs are highly intertwined, making it difficult to completely separate "goals" from "means to achieve those goals." For example, a person may claim to pursue social equality (value), but their support for certain policies (belief) may actually stem from ideological preferences rather than rational predictions about policy effects.

In other words, prediction markets cannot completely shield against human emotions, cognitive biases, and value orientations, so the operational mechanism of Futarchy may not achieve its theoretical rationality and efficiency.

03. Futarchy for Optimism

The designers of the Futarchy governance experiment believe that:

• When decision-makers are rewarded or punished for their accuracy (accurate → reward, inaccurate → punishment), they are likely to make more thoughtful, unbiased decisions;
• At the same time, a permissionless Futarchy model can attract more participants (crowd wisdom), rather than being limited to centralized decision-making bodies.

To make the experiment more open and to gather more data for testing, the experimenters opened participation rights, allowing anyone with a Telegram account or Farcaster account to join. All predictors received 50 OP-PLAY entry chips (these are OP-PLAY, tokens that do not have actual value and are only for experimental use), while actual participants in OP governance received more OP-PLAY chips.

So what was the prediction question for this round of Futarchy?

If a project receives 100k OP incentives, which protocol(s) will see the largest TVL growth three months later?

There were 23 projects participating in Futarchy, and each participant needed to predict the TVL increment of these 23 projects after "receiving 100k OP incentives." At the start of the experiment, all projects had the same initial predicted TVL (the same starting line, as a reference in the selection of test projects). As time progressed, users staked OP-PLAY and engaged in betting by buying call options (UP token) and put options (DOWN token) on different projects. The five projects with the highest prediction results each received 100k OP in incentives.

At the end of the experiment, participants selected five projects through OP-PLAY in the prediction market. For comparison, the Grants Council also selected its own five funded projects:

In the 21-day rise and fall betting, the top five projects selected through Futarchy for 100K OP funding were:

• Rocket Pool: $59.4M
• SuperForm: $48.5M
• Balancer & Beets: $47.9M
• Avantis: $44.3M
• Polynomial: $41.2M

Meanwhile, the five funded projects selected by the Grants Council (if there is overlap, only listed once) were:

• Extra Finance
• Gyroscope
• Reservoir
• QiDAO
• Silo

04. Limitations of the Futarchy Model in Governance

The limitations of the TVL judgment metric in this experiment:

"If the price of ETH rises, those protocols that have locked a lot of ETH will appear to have significant TVL growth, even if they have done nothing." — @joanbp, March 13 "It seems we are using Futarchy to decide who should receive grants, but if TVL growth merely reflects market price changes, then this metric cannot reflect whether the project has made good use of the grants." — @joanbp, March 13

The establishment of metrics for the prediction experiment is also very important:

"We should choose metrics that— even if participants want to 'manipulate'—can only be 'won' by doing things beneficial to the ecosystem." — @Sky, March 17

The bias introduced by simulated tokens (if the real token value is insufficient, bias can also occur)

"This is 'fake money,' not 'real money.' Many people will place bilateral bets at the last moment just to avoid losses." — @thefett, March 19

*41% of participants engaged in risk hedging at the end (bilateral betting to avoid losses)

"I feel like I didn't bring any special insights; instead, I diluted the influence of those who truly understand the projects." — @Milo, March 20

User experience was poor, affecting the effectiveness of the betting:

The success of prediction markets largely depends on the depth of user participation. However, this experiment had a high entry barrier, with opaque information and cumbersome operations, greatly affecting participants' judgment and engagement.

Common feedback from users included:

• Not knowing how many tokens there were in total.
• Each bet required 6 on-chain interactions. (Therefore, I didn't make many transactions in this experiment; the interface was too complicated)

• Unclear explanations for losses on incorrectly bet projects.
• The logic of the leaderboard's gains and losses was incomprehensible.

"I initially thought PLAY was used up, but each project reset, and I couldn't understand how much I had spent in total." — @Milo, March 20

"Having to sign six transactions for one prediction is a bit excessive." — @Milo, March 20

"I don't understand the leaderboard; sometimes I feel like I should be in profit, but it shows a loss of 46%." — @joanbp, March 19

According to the data report provided by Butter, this experiment:

1. Had a total of 5,898 transactions, but 41% of addresses only participated in the last three days, indicating a high learning cost for users.
2. Each prediction required 6 on-chain interactions (see interface screenshot), leading to an average of only 13.6 transactions per person.
3. Despite having 2,262 visitors, the conversion rate was only 19%, and the participation rate of OP governance contributors was only 13.48%.
4. 45% of projects did not disclose their plans to predictors, leading to information asymmetry and prediction bias (e.g., Balancer's predicted value exceeded the project's self-estimate of $26.4M).

05. Conclusion

1. The establishment of betting metrics will have a decisive impact on the Futarchy experiment.

Good metrics should have:

• Measurability: Data should be clear and easy to verify;
• Correct direction: They should guide participants to do things that "promote the system's positive development even if for profit";
• Difficulty in gaming: They should be hard to "inflate" purely through financial tricks or price fluctuations.

For example, in this Futarchy experiment, the TVL measured in dollars is easily influenced by the price fluctuations of mainstream coins like ETH, making the prediction results seem more like "betting on coin prices" rather than assessing who truly has growth potential.

Butter's official report shows that as of April 9, 2025, the mid-term TVL data has exposed the limitations of the metrics:

• Rocket Pool (predicted TVL growth of 59.4M) actually had a TVL growth of 59.4M, with an actual TVL growth of 0.
• SuperForm (predicted 48.5M) actually dropped by 1.2M.
• Balancer & Beets (predicted 47.9M) actually dropped by 13.7M.

The total actual TVL drop for all projects selected by Futarchy reached $15.8M, while among the projects selected by the Grants Council during the same period:

• Extra Finance (predicted 39.7M) actually grew by 8M
• QiDAO (predicted 26.9M) actually grew by 10M

This validates the community's skepticism—TVL metrics are strongly correlated with market prices and fail to effectively reflect the true operational capabilities of projects.

2. The "Best Predictor" results of Futarchy are not entirely objective

• In this experiment, the results reflect participants' OP-PLAY trading abilities more than their "predictive abilities," as all underlying assets experienced significant daily fluctuations, providing participants with considerable operational space (anonymous account @joanbp topped the leaderboard with high-frequency trading (406 trades/3 days)).
• In the final OP-PLAY trading win rate leaderboard, the group of Badge Holders, recognized as OP ecosystem professionals, had the lowest win rate.
• Only 4 of the top 20 predictors held OP governance identities (skydao.eth/alexsotodigital.eth, etc.).

3. The paradox of prediction influencing decision-making:

The characteristic of Futarchy is that prediction is decision-making, and collective expectations directly affect outcomes (for example, which project receives grants in this experiment). This differs from general prediction markets that purely predict external events, creating unique motivational challenges. As discussed in the OP forum, a voter in Futarchy has two orientations:

First, to go with the crowd and bet on popular projects to ensure these projects receive grants (correctly predicting but not necessarily with high returns, as most people are betting this way);

Second, to choose undervalued projects, where if the minority proves correct later, personal gains are maximized. This mechanism, which combines both voting and betting attributes, leaves participants somewhat at a loss. At the same time, when predictions themselves shape the future (because the flow of funds affects project development), Futarchy has a certain self-fulfilling or self-defeating cycle: if everyone bets on a project, resources are allocated to it, increasing its chances of success; conversely, projects that are not favored may fail due to lack of resources, even if they could have succeeded. This closed loop necessitates cautious interpretation of the predictive accuracy of the Futarchy experiment and consideration in its design of how to mitigate this self-fulfilling bias.

In this Futarchy experiment, we not only saw how governance mechanisms can be "gamified," but also recognized the potential of Degens in prediction markets—they are no longer just profit-seeking passersby but potential professional governors. Only when institutional design can anchor the energy of Degens to public goals, turning speculation into co-construction and betting into judgment, does Futarchy have the opportunity to activate the regenerative governance spirit (Regen) that belongs to Web3. This experiment awakened a possibility: governance need not be a puritanical rational negotiation; it can also be a deeply gamified consensus formation. Awakening the Regen bloodline of Degens may indeed be the evolutionary direction of future DAO governance.

06. References

[1] https://en.wikipedia.org/wiki/Futarchy

[2] https://gov.optimism.io/t/experimenting-with-futarchy-for-optimism-grant-allocation-decisions/9678

[3] https://ggresear.ch/t/futarchy-vs-grants-council-optimisms-futarchy-experiment/57

[4] https://medium.com/@netrovert/futarchy-redefining-dao-governance-5f554d523dee

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Content | Loxia

Editing & Formatting | Huanhuan

Design | Daisy

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