I built my first AI agent. It was mostly plumbing
📰 Dev.to AI
Building a multi-agent AI system involves significant plumbing work, as discovered by the author who created a research assistant in TypeScript
Action Steps
- Design the architecture of the multi-agent system, defining the roles of each agent
- Choose a programming language, such as TypeScript, to implement the agents
- Implement the agents, including an orchestrator, summarizer, and writer, and handle the handoff between them
- Test and debug the system, considering scenarios where one agent fails
Who Needs to Know This
Developers and AI engineers on a team can benefit from understanding the practical implementation of AI agents, as it helps them design and debug complex systems
Key Insight
💡 Implementing AI agents in practice requires significant attention to the details of function calling, error handling, and system architecture
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🤖 Building AI agents involves more plumbing than you think! 🚧
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