# Modular Framework for Human and AI-Agent Collaboration Establishing a flexible framework enabling seamless collaboration between human participants (researchers, SMEs, investors, etc.) and swarms of AI agents, ensuring scalability, adaptability, and continuous improvement. **Human-AI Workflow Integration:**\ Modular workflows allow humans and AI agents to contribute at different stages of the research lifecycle, including: * Proposal submission * Vetting * Milestone reviews * Commercialization **Job Categorization:** * **Human Jobs:** Tasks requiring creativity, legal expertise, or real-world interactions. Examples include researchers, SMEs, funders, and DAO members. * **AI-Agent Jobs:** Tasks such as preliminary vetting, milestone assessments, progress benchmarking, data validation, and fraud detection. * **Hybrid Jobs:** Collaborative tasks, such as proposal vetting and milestone reviews, where humans and AI agents work together to achieve optimal outcomes. **Continuous Learning and Adaptation:**\ AI agents gradually evolve to perform more tasks based on platform requirements and DAO-approved upgrades. This ensures sustained relevance and efficiency while adapting to the platform's growing needs. **Example Use Case:**\ A researcher submits a milestone report. AI agents validate data authenticity and flag anomalies, while SMEs assess the scientific rigor. Together, their inputs inform DAO voting on milestone approval. --- # 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://desciailabs-organization.gitbook.io/desciai.io/core-elements/modular-framework-for-human-and-ai-agent-collaboration.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.