A postgraduate student developed a modular AI system composed of reusable skills, expert agents, and prompts tailored to Public Health Biotechnology coursework. The system automates complex tasks such as statistical test selection, study design critique, pedigree analysis, primer design, and scientific slide generation. It uses structured decision trees, domain-specific knowledge references, and expert personas to provide reliable, context-aware assistance without repeated prompt engineering. The setup integrates with tools like VS Code and GitHub Copilot and is portable across multiple LLM platforms. This approach saves significant time by eliminating repetitive context explanations and improves output quality through procedural guidance and constraints.

Jun 10, 2026, 5:00 PM