Executive Coach Agent – AI Agent MVP

A working MVP of an AI-powered executive coaching assistant that simulates structured leadership coaching conversations.
The system helps professionals reflect on decisions, clarify priorities, and receive structured guidance similar to a human executive coach.

---

Technology Stack

• Orchestration: LangGraph (stateful AI workflows)
• API Layer: FastAPI
• LLM Runtime: Ollama (local LLM execution)
• Language: Python
• Containerization: Docker
• CI/CD: GitHub Actions

---

AI & Agentic Design Patterns

• Agent orchestration using graph-based workflows
• Memory-augmented reasoning for contextual conversations
• Modular architecture enabling multi-agent expansion
• API-first AI service design
• Containerized AI deployment pattern

---

Capabilities Demonstrated

• Designing agent-based AI systems
• Building LLM-powered applications with memory and orchestration
• Structuring AI services for production-ready deployment
• Applying modern GenAI engineering practices (CI/CD, containerization, modular architecture)
• Creating a foundation that can scale into enterprise multi-agent AI systems

---

High-Level Flow

User → FastAPI → Agent Orchestrator → Executive Coach Agent → LLM

---

Future Plans

• Multi-agent system
• Leadership analysis agent
• Meeting reflection agent