DAOGEN Learning Labs
DAOGEN is an idea incubator and product innovation lab focused on the intersection of decentralized identity, generative AI, L1 blockchain, and DAO technology.
DAOGEN Learning Labs take place within the fictional world and social network of DAOGEN, allowing for the creative exploration of these technologies.
Project Catalyst Fund 10 Proposal
Support Student Reader DAOGEN AI Learning Labs by commenting, sharing, and voting for our Project Catalyst Fund 10 proposal!
Build and deploy DAOGEN Master, an AI assistant that provides personalized guidance for DAO participation on the Summon Platform through interactive quests and in-game crypto payouts.
This proposal will create more developers within the Cardano ecosystem by accelerating and driving more adoption of our AI Agents 103: The DAOGEN Master Learning Lab.
AI In Production: Kubernetes and Slack Integration
Join us on a five-day journey towards an unforgettable DAOGEN experience!
This boot camp aligns with our Catalyst proposal: 🎧💠🧿 DAOGEN.ai: Building Open-Source AI Agent Infrastructure, Stimulating New Methods of Developer and General Education 🧿💠🎧
By bridging the gap between complex technologies and user-friendly applications, our course fosters a decentralized, inclusive, and open-source community, expanding Cardano’s user base and establishing its position as a leading blockchain platform. As a foundational element contributing to the DAOGEN proposal’s vision, we explore the transformative potential of AI agent development, creating captivating and educational gaming experiences within the DAOGEN ecosystem.
Five-Day Boot Camp Curriculum: Production Infrastructure for AI Agents in a Slack Room
Day 1: Introduction to Falcon A. Quest and AI Agent Architecture
- Overview of Falcon A. Quest, the friendly AI concierge for DAOGEN
- Understanding the overall architecture and components
- Introduction to Kubernetes and its role in AI agent deployment
- Hands-on exercises: Setting up a Kubernetes cluster
Day 2: Harnessing the Power of LangChain for Natural Language Processing
- Exploring the capabilities of LangChain as a language orchestration engine
- Creating conversational flows and context-aware interactions
- Implementing language models for realistic responses
- Practical exercises: Designing and testing AI agent dialogues
Day 3: Leveraging Data Stores and ActiveLoop for Knowledge Management
- Introduction to vector stores and their significance in AI agent intelligence
- Using ActiveLoop vector databases for efficient data storage and retrieval
- Implementing data handling and updating strategies
- Hands-on project: Building a knowledge repository for Falcon A. Quest
Day 4: Integrating Slack for Real-time Interactions
- Understanding the integration of Falcon A. Quest with Slack platform
- Implementing real-time messaging and notifications
- Creating interactive channel integrations for seamless user experience
- Practical exercises: Testing and refining Slack integration
Day 5: Deploying Falcon A. Quest and Final Showcase
- Setting up production infrastructure for Falcon A. Quest using Kubernetes
- Conducting performance and scalability tests
- Fine-tuning AI agent behavior for optimal user engagement
- Final showcase: Presenting Falcon A. Quest in action
