Multi-agent AI systems transforming education, from classroom tools to infrastructure
AI-powered entrepreneurship coaching platform that guides students through the complete startup journey—from problem discovery to pitch-ready presentation—using 5 specialized AI agents. Each agent brings domain expertise in market research, brainstorming, validation, product planning, and pitch coaching. Deployed with 25 students in the summer 2025 pilot at Gies.
The production pilot of Learning 3.0—an adaptive learning architecture where faculty act as "shapers on the path." Faculty define course intent via NLSpec files, coordinated multi-agent swarms generate personalized content (textbooks, quizzes, labs, studio guides), and faculty approve before deployment. Currently powering BADM 554 with a 186-concept learning graph across 8 weeks of curriculum.
MCP server that gives AI coding agents full access to Canvas LMS. With 90+ tools and 8 agent skills, it enables Claude, Cursor, Codex, and 40+ other agents to manage assignments, grades, discussions, modules, and peer reviews through natural language. Available on PyPI, the MCP Registry, and as a hosted service—no installation needed.
Open architecture spec for WhatsApp AI teaching assistants. Feed the spec to any AI coding agent (Claude Code, Cursor, Copilot) and get a working bot customized for your course—complete with student Q&A, professor dashboard, and drip campaigns. Currently being tested in an ongoing BADM 554 deployment with 36 active students and 97+ hours of engagement.
Interactive teaching tool that stages a multi-agent Delphi debate on AI ethics dilemmas. Five philosopher-agents—Leibnitz (Rationalist), Locke (Empiricist), Kant (Duty), Hegel (Dialectical), and Singer (Pragmatist)—debate topics like autonomous hiring and deepfake regulation across three rounds with streaming responses. Students inject their own perspectives between rounds, then a coordinator synthesizes all positions into a final policy recommendation.
A real-time, multimodal brainstorming application for collaborative idea generation at scale. Participants join shared sessions, contribute ideas through voice, watch them cluster in a 3D swarm visualization, and converge through quadratic voting—with AI-powered idea extraction, intelligent clustering, and automatic artifact generation built in.
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