Getting Started with AI Agents
summary
FetchAI shows a live stack: a 39B-parameter LLM plus Agentverse AI hosting and an Almanac smart contract for discovery; the platform reports ~300,000 registered agents, ~100,000 users, and agents that return real-time results (London transit, EV chargers) or execute DeFi strategies. Agents are free to build and take two–three hours to learn with detailed docs; registration of agents on-chain is periodic to ensure liveness. A hackathon offers $5k/$3k/$2k prizes and 24/7 Discord support.
AI-written summary · about
chapters (26)
- 0:00Introduction
- 0:32Human Intents and Use Cases
- 1:03System Components Overview
- 1:56ASI1 LLM and Agent Hosting Platform
- 2:40Documentation and Core Architecture
- 2:59Smart Contract and Agent Registration
- 3:52Benefits and Real-World Applications
- 5:05Developer Opportunities and Framework
- 5:54Use Cases Beyond Web3
- 6:18User Base and Agent Deployment
- 6:42Live Demonstration: Prompting the LLM
- 7:23Agent Search and Reasoning
- 8:03Creating and Hosting Agents
- 8:56Recap: LLM with and without Agents
- 9:28Real-Time Data and Use Case Examples
- 10:14General Purpose AI and Infrastructure
- 11:03EV Charging Agent Demo
- 12:12User-Agent Interaction
- 12:45Compound AI Systems and Integrations
- 13:38Search, Discovery, and Developer Opportunities
- 14:19Hackathon Announcement
- 14:47AI Agent Development as a Career
- 15:33Hackathon Support and Resources
- 16:22Accessing Resources and Community
- 17:09Documentation and Getting Started
- 17:30Conclusion
