# Client governance Growth DAOs commercial model relies on forming a growth team for our startup client members. **The value created by this team and the startup is the key driver of value.** Successful teams rely on regular and candid feedback, which is actively encouraged in real-time across our community platforms. We expect the majority of issues to be resolved through effective communication. Nonetheless, we need to be extremely clear with expectations and to build trust between stakeholders. The acceptance process for growth experts is highly effective and will ensure that only the best people make it into the community. **Members are initially evaluated against their results, effort, communication and accountability.** An ongoing review process ensures that growth experts are continually assessed against these criteria and reviews will be registered on chain. These form the basis of trust between the growth team and startup client stakeholders. Coupled with an internal metric for reputation, the Growth DAO client governance structure ensures we promote and maintain the best startup talent. On a commercial basis, a contract is created for each project on a monthly, weekly or project basis. The contract includes requirements for price, payment method, GRWTH rewards and time. This is recorded on the blockchain and immutable once agreed. Payments will be collected and distributed according to these contracts. Depending on the structure of the contract, there is a function to enable amendments if agreed by both parties according to the amended terms. If both parties do not agree, then they are entitled to follow our dispute resolution process. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.growth-dao.com/growth-dao-whitepaper/governance/client-governance.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.