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AI Agent - How to Grow Your Company (Se)

AI Agent - How to Grow Your Company (Se)

Project Description
  • What an AI agent is and what is genuinely new about it
o agents as a paradigm shift in knowledge work (the perception–reasoning–action loop, tool use, goal-directed autonomy).
  • From LLMs to agents: prompting, context, tool and function calling, memory, planning and orchestration.
  • What an AI agent can and cannot do: current capabilities, the “jagged technological frontier”
  • Democratisation of creation: how non-specialists can now act as creative artists, analysts and software developers.
  • Working effectively with agents: delegation, context provision, iteration and human-in-the-loop review.
  • Vibe coding and agentic engineering: rapid natural-language prototyping versus disciplined, testable, production-grade agentic software.
  • Tooling and orchestration: agent frameworks, tool and plug-in ecosystems, the Model Context Protocol and IDE-integrated coding agents.
  • Multi-agent systems and “Agents-only Companies” (AoC): orchestrator–worker patterns, autonomous teams and their governance.
  • Steering autonomous teams of agents: task decomposition, roles, evaluation, guardrails, escalation and oversight.
  • The economics of AI – “are tokens the new currency?”: token-based pricing, cost estimation, unit economics and cost control for agentic products.
  • Limitations, risks and responsibility: hallucination, reliability, security (e.g. prompt injection), bias, data protection and ethical and legal considerations.
  • Outlook: AI agents and its implications for entrepreneurship and firm growth.
Teaching Method
  • Interactive lecture with live demonstrations of AI agents
  • Hands-on build-along labs with agent tools and coding agents
  • Project-based group work: setting up and steering an agentic team
  • Case studies and critical discussion of opportunities and limitations
  • Guided self-study with practical assignments
Learning Results
Die Studierenden…
Learning Outcomes The students...
Professional Competence
  • are able to explain the fundamentals of AI agents and describe their differences com-pared to conventional programs and chatbots.
  • understand the key building blocks of agent-based systems (Large Language Models, prompting, context management, tool and function calling, memory, planning, and or-chestration).
  • are able to realistically assess the capabilities and limitations of current AI agents and evaluate their potential applications in different contexts.
  • understand the key opportunities, risks, and challenges associated with the use of AI agents, particularly regarding reliability, security, data protection, bias, as well as ethical and legal considerations.
  • understand the economic foundations of AI systems, particularly token-based cost models, cost estimation, and the relevance of unit economics for agent-based pro-ducts.
  • are familiar with current developments in multi-agent systems, autonomous agent teams, and their relevance for entrepreneurship and company growth.
Methodological Competence
  • Are able to explain the fundamentals of AI agents and describe how they differ from conventional programs and chatbots.
  • Understand the key building blocks of agent-based systems (Large Language Models, prompting, context management, tool and function calling, memory, planning, and orchestration).
  • Are able to realistically assess the capabilities and limitations of current AI agents and evaluate their potential applications in different contexts.
  • Understand the key opportunities, risks, and challenges associated with the use of AI agents, particularly regarding reliability, security, data protection, bias, and ethical and legal considerations.
  • Understand the economic foundations of AI systems, particularly token-based cost models, cost estimation, and the relevance of unit economics for agent-based pro-ducts.
  • Are familiar with current developments in multi-agent systems, autonomous agent teams, and their relevance for entrepreneurship and company growth.
Social Competence
  • Enhance their communication and collaboration skills through project-based teamwork in the development and management of AI agent teams.
  • Are able to structure complex tasks within teams, define roles, and collaboratively develop solutions using AI agents.
  • Are able to critically discuss case studies and practical applications of AI agents in teams while incorporating different perspectives.
  • Are able to jointly reflect on the impact of AI agents on organizations, ways of working, and business models, and derive appropriate recommendations for action.
Personal Competence
  • Develop the ability to critically reflect on their own use of AI agents and realistically assess their benefits and limitations.
  • Are able to reflect on their own role in the context of increasing automation and the digital transformation of knowledge work.
  • Strengthen their ability to independently learn and apply new AI technologies and assess their future relevance for entrepreneurship and company development.
  • Develop confidence and autonomy in the responsible use of emerging agent-based technologies.
Requirements
Keine
Examination
Portfolio assessment: (50%)
Individual vibe-coding build (25%)
Individual reflective essay (25%).
Module number:
6212768
Courses:
27 L / 21 h
Self-study:
70 h
Scheduled Semester:
3