Dr. AGENTONOMICS: A Didactic Experiment of AGENTONOMICS
AGENTONOMICS is a framework treating AI agents as economic entities with an integrated management architecture. Dr. AGENTONOMICS is its first application: a lecture agent developed for the TUM course on AI agents in business administration. Conceived in winter semester 2025/26 and introduced in summer semester 2026, it serves as a didactic experiment where the agent is both the object of study and the learning medium. The current prototype is a web-based, retrieval-grounded tutor explaining AGENTONOMICS concepts and supporting student questions. The report argues the system can grow into three additional cumulative roles: an avatar lecturer, a design consultant guiding students through the ADMRF, and a meta-agent for constructing specified agents.
Dr. AGENTONOMICS is a didactic experiment applying the AGENTONOMICS framework, which treats AI agents as economic entities. Developed at TUM, it was conceived in winter 2025/26 and introduced in summer 2026. The prototype is a web-based, retrieval-grounded tutor that explains AGENTONOMICS concepts and answers student questions. The system is designed to potentially expand into an avatar lecturer, a design consultant for the ADMRF, and a meta-agent for agent construction.
The system uses a retrieval-grounded architecture, likely combining a knowledge base with a language model to provide accurate, context-aware responses. Its cumulative role expansion suggests a modular design where the same interface, intelligence layer, tools, and knowledge base can support increasingly complex tasks, from tutoring to agent construction.
This experiment demonstrates a trend toward using AI agents not just as tools but as integrated components of educational and business processes. It highlights the potential for AI to serve dual roles as both subject matter and delivery mechanism, which could influence how AI management frameworks are taught and applied in enterprise settings.
The AGENTONOMICS framework and its didactic application could provide a structured approach to managing AI agents as economic entities, potentially reducing costs and improving efficiency in agent deployment. For educational institutions and enterprises, it offers a scalable way to train personnel in AI agent management, with the agent itself serving as a cost-effective teaching assistant.
If successful, the Dr. AGENTONOMICS system could evolve into a comprehensive platform for AI agent design and management education. Observable next signals include the release of the avatar lecturer or design consultant modules, student feedback on effectiveness, and potential adoption of the AGENTONOMICS framework in other institutions or corporate training programs.