AI Agent Design & Training

• Defined modular agent roles including content delivery, feedback, scheduling, and progress tracking.
• Used domain-specific corpora and simulated learner personas to fine-tune the GPT-based agents.
• Trained agents to handle curriculum adaptation based on learning speed and concept mastery.

UX & Learning Flow Design

• Mapped out various learner journeys based on grade, subject, and learning style preferences.
• Developed low-friction flows to onboard students, connect with tutors, and resume paused sessions easily.
• Tested interaction formats—chat, visual cards, and voice—with real learners to refine engagement.

Educator Panel & Oversight Tools

• Created dashboards that gave teachers full transparency over how agents interact with students.
• Built tools to adjust tone, difficulty, and response type for AI tutors per classroom context.
• Provided logs and summaries of AI-student conversations to support grading and follow-up.

Infrastructure & Deployment

• Designed serverless microservices for each agent class, supporting scale-out and isolated debugging.
• Used autoscaling and regional CDN deployment to ensure real-time interaction at global scale.
• Integrated a CI/CD pipeline with agent regression testing to ensure fast and stable deployments.

Pilot Program & Iteration

• Launched with 3 institutions in 2 countries, tracking engagement, learning speed, and dropout rates.
• Used educator and learner feedback loops to fine-tune content recommendation and feedback strategies.
• Ran weekly iteration sprints for 8 weeks to tune agent behavior, UI flow, and performance bottlenecks.