The team is building several core systems: an agent harness that runs agentic workflows durably in production, a retrieval-augmented generation (RAG) platform that grounds agents in enterprise knowledge, an insight engine that turns agent execution data and signals from related systems into live domain knowledge and context for both people and agents, an eval harness that measures agent quality and catches regressions, and a skills marketplace where teams publish and reuse agent capabilities. Experience building GenAI applications and agentic harnesses, using frontier and open-weight models (e.g., GPT, Claude, Gemini, Llama, Qwen) and frameworks such as LangGraph, Microsoft Agent Framework, OpenAI Agents SDK, or Claude Agent SDK.