This solution leverages futarchy to allocate capital based on market predictions of future fee generation. By creating conditional markets for each funding proposal, we enable participants to profit by correctly identifying which mechanisms will generate the most fees, creating a self-sustaining allocation system.
Core Mechanisms
(1) Proposal Markets: When builders want funding, they submit a proposal specifying how much funding they need, their target fee generation (e.g. $1000/month), and their measurement period (6-18 months). For each proposal, the system mints two types of conditional tokens:
PASS-TOKEN: Redeemable for 1 ALLO if the project meets or exceeds its fee target
FAIL-TOKEN: Redeemable for 1 ALLO if the project falls short of its target
(2) Market Formation: Once a proposal is submitted, a 10-day trading period begins. The system creates liquidity pools that enable trading between these conditional tokens and ALLO. Traders can buy PASS tokens if they believe the project will succeed, or FAIL tokens if they think it won’t meet its targets.
(3) Impact Calculation: The market’s prediction of a proposal’s value is calculated through the price difference between PASS and FAIL tokens. This difference, multiplied by the requested funding amount, determines the predicted impact. If this impact is positive, indicating the market believes the project will succeed, the proposal is automatically approved for funding.
(4) Execution & Settlement: Successful proposals receive their requested funding from the Allo treasury. As the funded project operates, its fee generation is tracked directly onchain. When the measurement period ends, PASS and FAIL tokens become redeemable based on whether the project met its target.
Potential Concerns
Manipulation in Proposal Markets: Without safeguards, small groups can distort prices in less-traded proposals, leading to incorrect funding decisions.
Short-Termism: The fixed trading period and impact calculation might favor projects with quick fee realization over those with delayed but higher returns.
Target Gaming: Builders optimizing for approval rather than maximum fee potential could undermine the system’s effectiveness.
we’re talking securities lawyer time because binary options are used for financial hedging … keep it to something innoculous (beta-testing) and avoid any US customers until you get a few $M in backing
So sorry for suggesting something that US regulators might have some issues with, didn’t realize they were thought policing our forums
thank you for the constructive feedback!
one question i have re; futarchy is "are the most important things in the allo ecosystem measurable? and how much can these things be gamed by goodharts law?
how could we point futarchy at finding the best talent? (quality is hard to quantify). that is the top of the funnel.
then after we’ve got the apps in our ecosystem… i think its pretty easy to measure the funding flowing through them. GMV = Gross Marketplace Value. perhaps that could be a futarchic market.
My understanding is that GMV is the metric being optimized for, so that’s what the predictors would be betting on. In principle, the betting markets would act as a curation mechanism to surface the most promising builders based on the future expected GMV. Betting markets could actually be quite good at surfacing dark horse talent, since there is an incentive to bet big on unknown builders that you have high conviction on before the market realizes how good they are. This is a strength of prediction markets as opposed to voting mechanisms which are typically more conservative and revert to popularity contests– making it much harder to take non-consensus bets.
However, in practice I’m not sure how this would play out. There would likely need to be a lot of experimentation to determine the exact design and what other mechanisms to layer in. For this reason, I am not necessarily in favor of Allo starting out with futarchy, but I wanted to flesh out a minimum viable design to keep in mind and potentially pilot down the line.
I’d like to propose an amendment which I believe could make the design useful from the beginning.
The MetaDAO token price on pass/fail model works well. But it’s a proposal-centric view of DAOs, i.e., how much will a proposal affect token price.
If Allo is designed to maximize its return on capital, there’s a mismatch between the goal and the mechanism: This approach almost guarantees the DAO will regularly fund projects with returns far worse that the global maxima.
Why force the DAO to evaluate every single proposal it receives equally, one-at-a-time?
Instead, use a capital-centric POV which focuses on maximizing return on capital, i.e., given we want to allocate some fixed amount of capital, which proposal produces the greatest amount of the effect I want, e.g., GMV?
Then you can evaluate multiple proposals at once and guarantee that you’re always getting the highest ROI for every ALLO or $ you allocate.
this would be tight. if the market could auto-discover the best up and coming builders in the ecosystem… and then we can coordinate ways to acceleate them.
though i worry about goodharts law by having the builders focus TOO MUCH on GMV / TVF (total value flowed)
