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Introducing Agentic Generative AI: Build Autonomous AI Systems with LLMs

A laptop displays a holographic interface with phrases like Generate image and Summarize text

A laptop displays a holographic interface with phrases like Generate image and Summarize text

Key Takeaways

  • Beyond Chatbots: Agentic AI enables autonomous systems that reason, plan, and execute complex goals independently.
  • Practical Frameworks: Gain experience using orchestration frameworks like LangGraph to build multi-agent teams and autonomous assistants with this new MSIS and MSBA elective at Leavey.
  • Close the Skills Gap: Prepare to lead agentic AI projects, filling the demand for technical leaders and architects in Silicon Valley and beyond.

Autonomous AI systems are rapidly redefining software. They no longer wait for step-by-step human instruction, but actively pursue complex goals. This marks an evolution in technology, moving beyond simple query-response models into systems capable of reasoning, planning, and executing multi-step tasks.

To address these changes, the Leavey School of Business is launching an agentic AI course, expected to be offered starting this February. Agentic Generative AI is specifically engineered to rapidly equip students who want to engineer and deploy these autonomous systems, not just use them. This elective offers developers hands-on experience building complex workflows and managers leading technical teams the mastery essential for driving innovation in today's dynamic Silicon Valley.

What Is Agentic AI?

Understanding agentic AI requires distinguishing it from standard generative AI. While typical LLMs offer single-prompt interactions, agentic systems utilize continuous loops for reasoning, planning, and execution.

This represents a qualitative leap in software capability. Instead of a human manually guiding every step, an autonomous agent can break down a complex goal—such as "research this competitor and draft a market entry strategy"—into sub-tasks, execute them using various tools, and self-correct when it encounters errors. This technology is already beginning to redefine industries, from automated research in finance to complex operations automation in healthcare.

What You’ll Build in This Course

This course is designed to be practical and output-oriented. Students in this program will walk away with a portfolio of functional autonomous systems, such as:

  • Personal Assistant Agents: Build autonomous systems that can manage your tasks, retrieve specific information, and take action on your behalf.
  • Customer Support Systems: Design multi-agent AI systems that triage inquiries, respond to technical issues, and escalate complex problems without human handoffs.
  • Domain-Specific Agent Teams: Orchestrate coordinated groups of specialized LLM agents that collaborate to solve complex, multi-step problems.
  • Multimodal Agents: Develop systems that can process and act upon data across text, audio, image, and video.

The Full Curriculum Stack

Our curriculum moves beyond basic prompt engineering to focus on LLM application development at scale.

  1. Foundation Layer: Master LLM fundamentals and advanced prompt engineering—the prerequisites that most AI users assume they already know.
  2. Orchestration Layer: Dive into a LangGraph tutorial environment to learn how agents coordinate, hand off tasks, and recover from failures.
  3. Production Layer: Build multi-agent AI systems using both commercial platforms and open-source tooling, while considering the real-world implications of deployment and safety.

Who This Course Is For

This autonomous AI agents course is designed for a dual audience:

  • Developers who want to master the architecture and code required to build robust agentic systems.
  • Technically-minded managers who need to evaluate, oversee, and direct these high-stakes projects.

This design is intentional: successful AI projects require developers and decision-makers to share a precise understanding of the technology’s capabilities and constraints.

Why Now? The Demand Signal

Agentic AI has shifted into a practical reality, with systems now actively deployed in sectors like finance, healthcare, and enterprise SaaS. Orchestration frameworks, such as , have emerged as the standard infrastructure for AI engineering teams worldwide.

Currently, the demand for leaders and engineers who can design agentic architectures significantly outpaces the supply. By enrolling now, you’ll learn the skills needed to create and lead the next wave of innovation.

Take the Next Step

Ready to build the future of autonomous software? We invite you to explore how the MS Programs at the Leavey School of Business can elevate your career.

Frequently Asked Questions

How long is the course, and how many units is it?

This is a 2-unit elective offered over a condensed 5-week format—ideal for students who want focused, intensive exposure to agentic AI. The accelerated structure is designed to keep pace with how fast this field is moving.

Do I need prior AI or machine learning experience to succeed in this course?

The course is explicitly designed for both technical developers and technically-minded managers, so deep ML experience isn't assumed. Students will need to take the 2-unit elective Generative AI, offered in January, as a prerequisite for Agentic Generative AI.

Note: MSIS applicants need at least one college-level programming course before enrolling (accepted languages are Python, Java, R, C, and C++ only).

Can I take this course if I'm in another Leavey graduate program?

Yes! Agentic Generative AI is an approved elective for the MS in Information Systems (MSIS) and MS in Business Analytics (MSBA) programs. If you're enrolled in another Leavey graduate program, such as the Evening MBA, you can often take this course through the GBP Anywhere Program–should you meet all prerequisites.

May 13, 2026
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