AI Agents in Practice — Part 2: What Makes Something an Agent
📰 Dev.to · Gursharan Singh
Learn the engineering definition of an AI agent and its composition using primitives like MCP, RAG, and Skills
Action Steps
- Define the control loop of an AI agent using tools, state, and boundaries
- Identify the three primitives that an agent composes: MCP, RAG, and Skills
- Apply the concept of a control loop to bridge manual ReAct to native tool calling
- Configure an agent using MCP, RAG, and Skills to automate tasks
- Test the agent's functionality and adjust its composition as needed
Who Needs to Know This
Developers and engineers working with AI agents can benefit from understanding the control loop and primitives that make up an agent, to design and implement more effective AI systems
Key Insight
💡 An AI agent is a control loop with tools, state, and boundaries, composed of primitives like MCP, RAG, and Skills
Share This
🤖 What makes something an AI agent? Learn about control loops, primitives, and composition in AI agent design 💻
Key Takeaways
Learn the engineering definition of an AI agent and its composition using primitives like MCP, RAG, and Skills
Full Article
Define what an agent actually is in engineering terms — a control loop with tools, state, and boundaries. The bridge from manual ReAct to native tool calling, with MCP, RAG, and Skills as the three primitives an agent composes.
DeepCamp AI