- MESA introduces stake-weighted aggregation to set SOL inflation rates through validator voting on multiple fixed options.
- The model retains Solana’s fixed terminal inflation rate while enabling more efficient consensus on annual deflation adjustments.
- MESA builds on lessons from SIMD-228, aiming to reduce governance friction with expanded voting structures and predictable outcomes.
Solana’s new governance initiative MESA comes as a solution for changing the monetary policy of the blockchain through validators. It empowers validators to vote on annual deflation rates, which can be done instead of a yes-or-no decision. This stake-weighted voting infrastructure allows multiple outcome possibilities so that participants are uniquely equipped to assist in fine-tuning the SOL inflation curve.
In addition to enhancing decision-making processes, MESA aims to make collective decisions on behalf of a diverse group of validators. It also provides a wide range of input options and eliminates the rigid yes or no system. Because preferences might differ in a network, MESA can contribute to a fairer form of governance. The policy aims to improve decisiveness on inflation matters while expanding consensus on the same.
Proposal Outlines Stake-Based Aggregation Model
According to MESA, the disinflationary curve should remain the same and continue to decline until the long-term inflation rate exceeds 1.5%. Although the terminal inflation rate is kept constant, MESA provides a new method for calculating annual deflation percentages. The validators are also empowered to vote for several options, including 15%, 17.5%, or 30%, each of which is considered a YES vote.
The new method is more elaborate in calculating the result through stake-weighted averages only based on the YES votes for the final tally. However, during voting NO and ABSTAIN still exist but they are not calculated in the final vote. This ensures that the deflation rate selected is the one that the active participating validators seek to encourage or support regarding policy changes.
Also, the change from switching between two options with different values allows avoiding the vote cycling effect, in which multiple votes are required to select the desired value. In this way, MESA provides for faster yet more accurate policy decisions as different viable solutions are included in one vote.
MESA Addresses Previous Governance Limitations
Attempts made before, like in the case of SIMD-228, revealed problems with the existing Solana voting mechanism. Therefore, the SIMD-228 community was also concerned with the issue of high inflation rates. However, it also showed that single-majority rule systems deprive participation and do not express differentiated preferences. While that proposal approved the terminal rate of 1.5%, it brought discussions on the fixed 15% deflation rate change annually.
MESA was designed in response to such limitations, as it provides a means of expanded involvement and sophisticated preference indication. MESA is better aligned with the true intention, as it allows validators to choose deflation percentages rather than support and oppose proposals. It not only optimizes governance’s effectiveness but also increases the involvement of the validators.
Thus, the validators who seemed to lack choices now have the means to state their preferences in detail, which may lead to higher turnout and better aggregation.
Defining Vote Structure and Governance Parameters
MESA also presents a sophisticated vote structure specifying procedures for achieving viable and legitimate results. Some modifications must meet a quorum for the process to be considered valid. According to the SIMD-228 guidelines, the current plan requires at least two-thirds of the total value of the validator’s stake to be within the YES range for any result to be considered.
Alternatively, once the quorum condition is achieved, the number of deflations is obtained from the weighted mean of the supporting YES votes. This model provides some degree of flexibility and structure that will help ensure that the policy directions reflect validator consent. Furthermore, it provides a clear way for validators to adjust supply emotion directly and predictably and with a repeatable methodology.
