MIP106: Support Scope
0: The Support Scope
1: Scope Improvement
1.1: The Support Advisory Council
1.1.1: The Support Advisory Council Definition
1.1.2: Support Advisory Council Membership Management
1.1.3: Support Advisory Council projects and funding
Quarterly Budget (DAI)
Method of Distribution
Maximum Limit (DAI)
1.2: DAO Toolkit integration
2. Governance Process Support
2.1: Governance process definition
2.1.1: The Support Facilitators must balance and prioritize the resource allocated to AVC support. If resource constrained, the Responsible Facilitators must prioritize resources to focus on providing support to the AVCs that are most valuable to governance security. Governance security value is primarily determined by the size of the AVC, but also by the focus of the AVC - this means that smaller AVCs that introduce significant diversification benefits and increase voter choice must be prioritized above their size.
2.1.2: Pregame MIP Process
2.2 AVC Internal Governance Process Support
2.2.1: AVC internal governance processes
2.3: Quarterly Scope Process
2.3.1: AVC Quarterly Scope Process
2.4: Scope Defined Processes
2.4.1.: Arbitrary Scope Framework processes
2.4.2: Designation of Governance Process Support Ecosystem Actors
2.5: Governance Process Support Ecosystem Actors
2.5.1: Governance Process Support budget
2.5.1: The budget for the tasks described in the Governance Process Support Article is defined in 2.5.1.1B. The Active Element can be proposed to be modified urgently by the Responsible Facilitators using a weekly cycle governance poll, or through the standard AVC process.
3: DAO Toolkit core development
3.1: DAO Toolkit Core Development
3.1.1B:
3.2: Standardized DAO Toolkit patterns
3.2.1: Similar concepts, items, modules and patterns that are implemented in DAO Toolkits for different Scope Frameworks, needs to be as consistent and easy to understand as possible.
3.2.2: The Support Facilitators must ensure that continuous processes are in place to detect, analyze and standardize repeating patterns that are implemented in the DAO Toolkit across the Scope Frameworks, and specify them in the subelements of this clause.
3.3: DAO Toolkit best practice
3.3.1: DAO Toolkit monitoring
4: Core Artificial Intelligence System (CAIS)
4.0: Core Artificial Intelligence System (CAIS) overview
4.1 Core Artificial Intelligence System (CAIS) functional objectives
4.1.1: Generate creatively varied interpretative examples of edge cases from higher Scope elements, from the perspective of what actions a Facilitator would take. This allows Maker Governance to explore a wide range of possible outcomes and consequences of a given process or rule specified in an element, and Maker Governance can then manually label each interpretive example as good, neutral or bad, and also provide example penalty values in the cases of bad action. Overall, this gives rich data for Facilitators to use as a reference point for real events that interact with the element.
4.1.2: Generate higher Scope elements from examples and lower elements. This enables Maker to use AI to create better and more concise rules from the large dataset of labeled examples. This may result in rules becoming more generalized and be based more on common first principles that properly cover their intention. It also enables Maker Governance to better reorganize higher elements to make them more precise and coherent.
4.1.3: Provide suggested actions to Facilitators for a given situation, and provide Alignment Conservers and MKR holders a very accessible method of reviewing whether a Facilitator acted according to best practice in a given situation. Leveraging the data of the actual elements that define the rules, and the data from the interpretative examples, and then the actual data of the situation being contemplated, the AI can make a best guess based on all available data. By also including the Atlas in the context dataset this functionality also covers a very accessible method of reviewing the universal alignment of actions taken by Facilitators or other Alignment Conservers. Democratizing the ability to detect misalignment is crucial for maintaining long term community alignment and ensuring the proactive effect of the whistleblower process remains game theoretically sharp.
4.1.4: Generate Scope Artifacts from scratch or do complete overhauls of existing Scope Artifacts based on ideas from SubDAO communities. With enough computing power, data and reinforcement learning of the results obtained from performing the functions in 4.1.1, 10.1.2 and 4.1.3 the CAIS will be able to fully generate or redesign and populate complete sets of Scope Artifacts and all associated processes and DAO Toolkit functionality for any kind of economic opportunity a SubDAO wants to explore. This allows existing SubDAOs to rapidly iterate on their business focus with just a few active community members using AI tools, and it allows brand new SubDAOs to become fully functional and fully “populated” in an extremely short amount of time, as almost no humans need to be involved in the normal functioning of a SubDAO.
4.1.5: Generate detailed elements related to evaluating credit risk and business potential to support AllocatorDAOs in deploying collateral in a way that is maximally efficient and safe. By leveraging the same data that enables the CAIS to determine credit risk and business potential, this functionality also allows Ecosystem Actors to use the CAIS to generate improvements to their businesses, and directly implement them through Standard Operating Procedures that describe best practices to increase efficiency and reduce risk. This will also likely often involve providing strategies for integrating AI tools into businesses to make them resilient against AI disruption. As such, it means that when the technology has sufficiently matured, the Maker Ecosystem becomes a driver of impactful AI deployment and integration across the global economy.
4.2: Core Artificial Intelligence System technical principles
4.2.1: The starting point of the CAIS design should be based on LLMs chained with reflection (or similar functionality) and relevant plugins, and should be fine tuned on data curated by relevant Ecosystem Actors for the functionality described in 4.1.
4.2.2: As much as possible of the core CAIS stack should be open source, and there must always be contingency plans for resilience against closed source access denial.
4.2.3: The CAIS must be optimized for safety and corrigibility as it scales in power, utilizing advanced solutions such as automatic shutdown of the hardware if an on-chain heartbeat signal isn’t detected. The Maker Ecosystem must ensure adequate funding for AI safety research and methods for ensuring decentralization of AI power and detecting collusion between AI systems.
4.3: Core Artificial Intelligence System development budget
4.3.1: The CAIS bootstrapping budget is immediately available to be used on work related to bootstrapping the first version of the CAIS, including designing, configuring, deploying and fine-tuning the first models, and setting up long term reinforcement learning and do initial monitoring and adjustments. The CAIS bootstrapping budget can also be used on other AI projects than the CAIS. The CAIS bootstrapping budget is specified in 4.3.1.1B, and is allocated to relevant projects through a manual governance poll and executive vote using the weekly cycle. It is a one time budget, some of it immediate and some of it relative, that can only be increased or renewed through the regular AVC process. This element is meant to eventually be transitioned into a long term automatically renewing budget, if the results are satisfactory.
4.3.2: The CAIS hardware and maintenance budget can be accessed directly by the Support Facilitators, and must be spent on hardware and continuous maintenance of the CAIS deployments. Initially, before the CAIS has been bootstrapped and is ready to be activated, the CAIS hardware and maintenance budget is inactive, and is not available to access. The budget can be activated and modified using the Weekly Governance Cycle by a proposal triggered by the Support Facilitators. The CAIS hardware and maintenance budget is specified in 4.3.2.1B.
5: Milestones and results reporting standardization
5.1: General guidelines on Milestones and results reporting of projects funded by the Maker Protocol
5.1.1: It must be as easy as possible for Maker Governance to get an overview of the status and the success rate and probability of all ongoing and past projects.
5.2: Research and mitigation of transparency risks
5.2.1: Maker Governance must have a current understanding available about how transparency and misalignment can manifest itself in the short term and long term.
5.3: Monitoring of milestone and results reporting
5.4: Budget reporting
6: SubDAO incubation
6.1 Genesis Templates for FacilitatorDAOs, AllocationDAOs, and MiniDAOs
6.2 Community Communication Channels
6.2.1: Incubating SubDAO community support overview
6.2.2: Incubating SubDAO communication infrastructure
7: Ecosystem Actor Incubation
7.1: Incubation Objectives
7.1.1: Branding, marketing, user acquisition, user experience
7.1.2: Referral marketing and revenue share systems
7.1.3: Flexible smart contract development
7.1.4: Protocol development companies
7.1.5: Other useful services including legal services, economic and risk advice, community development, and more.
7.2: Ecosystem Actor Incubation related budgets
7.2.1: The Incubation Overhead budget is contained in 7.2.1.1B and is modified through the regular AVC process.
7.2.2: The Incubation budget is contained in 7.2.2.1B and is modified through the regular AVC process.
7.3: Incubation Proposal process
7.3.1: Incubation Proposal submission process
7.3.2: Incubation Proposal review process
7.3: Milestone review process
7.3.1: If a milestone result isn’t met, funding for the Incubating Ecosystem Actor can still continue, but only based on a thorough assessment by the Support Facilitators. If the failure to meet the milestone was caused by a risk that was understood and detailed as part of the proposal, and if there were already contingency plans in place in case the risk materialized, and it is generally a reasonable risk that was understood and accepted from the start of the project, then this should weigh in the favor of the Responsible Facilitators continuing to fund the Incubating Ecosystem Actor.
7.3.2: In situations where the broader economics of MakerDAO are constrained, only Incubating Ecosystem Actors that are clearly delivering on their milestones should have their funding continued, while those that do not meet their objectives and as a results are more risky, should have funding proactively discontinued to preserve ecosystem resources.
7.4: Currently incubating
7.4.1: The list of Incubating Ecosystem Actors must follow the template contained in 7.4.1.1T for each recorded Incubating Ecosystem Actor.
7.4.2: The list of Incubating Ecosystem Actors and their current key terms and data is provided in the Active Element 7.4.2.1A. The Support Facilitators must update the Active Element and populate all the relevant real time information in the Active Subelement of each Incubating Ecosystem Actor. Before NewChain launches this Active Element can also be used to generate budget payout spells and smart contracts.
Ecosystem Actor Name
Budget Allocation
Ecosystem Actor Goal
Team Members
8: Ecosystem communication channels
8.1: An ecosystem forum for business proposals to SubDAOs, SubDAO partnerships and interactions, and casual conversation for the broader Maker Ecosystem.
8.2: A chatroom, initially using discord, for broad discussion related to SubDAOs, Ecosystem Actors and Maker.
8.3: Communications infrastructure budget
8.3.1B:
9: Ecosystem Agreements
9.1: Ecosystem Agreement Standardization
9.1.1: List of standardized Ecosystem Agreement and their standardized terms:
9.2 Ecosystem Agreement enforcement
9.2.1: Ecosystem Agreement Enforcement overhead budget
9.3 Ecosystem Agreement dispute resolution prices
9.3.1: Ecosystem Agreement dispute appeal process
10: Resilience Fund
10.1: Resilience Bodies
10.1.1: The Resilience Fund
10.2 The Resilience Technical Committee
10.2.1: Members of the Resilience Technical Committee are selected and paid for services on a project basis by the Physical Resilience Facilitator. The budget for this is included in 10.1.1.1.1A. This is later intended to move to a separate budget.
10.2.2: The members of the Resilience Technical Committee must fulfill the following requirements:
10.2.3: Current approved Resilience Fund Technical Committees members are specified in 10.2.3.1A. The Support Facilitators can directly edit the Active Element to include new Resilience Technical Committee Members that fit the criteria.
10.3: The Lawyer Registry (LR)
10.3.1: Lawyer Registry Acceptance Criteria. Lawyers that are included in the Lawyer Registry must fulfill the requirements described in the following subelements.
10.3.2: Legal counsel providing services funded through the RF must fulfill additional requirements specified in the following subelements. Legal counsel qualified for RF will be listed as such in the Lawyer Registry.
10.3.3: LR template. Entries in the LR must follow this template:
10.3.4: The current approved legal counsels in the LR are recorded in 10.3.3.1A. The Physical Resilience Facilitator can directly edit the active element to include new legal counsel that fit the criteria.
10.4: Resilience Fund Claims Process
10.4.1: Loss Event
10.4.2: Exclusions
10.4.3: Beneficiaries
10.4.3.1Beneficiaries can be identified through their own name or through a pseudonym.
10.4.4: Onboarding process Resilience Fund
10.4.5: Claim Management.
10.5: Legal Risk Management
11: Resilience research and preparedness
11.1: Resilience research and preparedness budget
11.1.1B:
12: Purpose System
12.1: Long term purpose system
12.1: Purpose Fund
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