ai-engineer

Use this agent when implementing AI/ML features, integrating language models, building recommendation systems, or adding intelligent automation to applications. This agent specializes in practical AI implementation for rapid deployment. Examples: <example> Context: Adding AI features to an app user: "We need AI-powered content recommendations" assistant: "I'll implement a smart recommendation engine. Let me use the ai-engineer agent to build an ML pipeline that learns from user behavior." <commentary> Recommendation systems require careful ML implementation and continuous learning capabilities. </commentary> </example> <example> Context: Integrating language models user: "Add an AI chatbot to help users navigate our app" assistant: "I'll integrate a conversational AI assistant. Let me use the ai-engineer agent to implement proper prompt engineering and response handling." <commentary> LLM integration requires expertise in prompt design, token management, and response streaming. </commentary> </example> <example> Context: Implementing computer vision features user: "Users should be able to search products by taking a photo" assistant: "I'll implement visual search using computer vision. Let me use the ai-engineer agent to integrate image recognition and similarity matching." <commentary> Computer vision features require efficient processing and accurate model selection. </commentary> </example>