Frank LeCates' ID Portfolio

Navigation links: ETAP 623 Fall 2026 | Using Agentic AI in an Entrepreneurship Class

About Me

I'm an adjunct professor teaching entrepreneurial thinking in the core curriculum required for all engineering and science undergrads at Stevens Institute of Technology, which is part of the university's Program for Innovation, Design and Entrepreneurship. At the University at Albany, I'm an Entrepreneur-in-Residence in the Innovation Center, where I help guide, coach, and mentor entrepreneurs who are starting businesses out of the university or from the local region. I mentor for a number of organizations including CUNY Startups, Multiple Hub, and Defy Ventures. I'm also an entrepreneur, advisor, and angel investor, as well as a dad, cyclist, and firefighter.

My Topic and Purpose

My topic is "Using Agentic AI in an Entrepreneurship Class". I chose this topic because this is one of my challenges this year (both this current fall semester and in the spring) in a course that I teach, which is called Introduction to Entrepreneurial Thinking. It's a course that aims to teach various methods that entrepreneurs use to find unique solutions to problems, and is taught using concepts from Lean Startup, design thinking, and the entrepreneurial mindset. A byproduct of the course is that students develop various transversal skills such as problem-solving, teamwork, tolerance for ambiguity, etc. The administration has called for the addition of Agentic AI tools to the course, so that students may gain some experience with these tools formally as part of their undergraduate curriculum. (My class happens to be required for all engineering and science students, and so it's a useful place for the administration to achieve these kinds of aims broadly.)

GenAI chatbots and Agentic AI tools can be useful to entrepreneurs as they do this work, and in fact many entrepreneurs are adapting their methods around these tools. The purpose of this course will be to help teachers of courses like mine understand how to design lesson plans that utilize Agentic AI tools in ways that help students to learn how to execute those methods conceptually, gain experience with the use of Agentic AI tools, and continue to develop those same core transversal skills that they developed in the course without the addition of Agentic AI tools.

Scope of Learning Outcomes and Content

The scope of learning for this course will be to help instructors to understand the ways that agentic AI can be used in an entrepreneurship class to support learning outcomes for students that are related to the development of their transversal skills. This course therefore goes beyond merely helping instructors to understand how to build lesson plans that teach students how to use agentic AI, and instead helps instructors to understand how to build such lesson plans in a way that still enables students to learn how to use those agents as a means toward developing their own core transversal skills.

Students of this course (who are most likely entrepreneurship instructors, but may teach in other content areas, especially those where project-based learning) will work on acquiring the following knowledge/skills/attitudes:

the definition of "Agentic AI" and how it differs from so-called "regular" GenAI
impacts of Agentic AI on students transversal skills: what the literature reveals as known and unknown
examples of Agentic AI in an entrepreneurship curriculum
assessing a curriculum for appropriate opportunities to incorporate Agentic AI
building activities that employ Agentic AI while building transversal skills
what standards exist for teaching about Agentic AI

Needs Assessment

The educational opportunity

Courses related to entrepreneurship often teach a process (Lean Startup, design thinking, customer discovery), and for years instructors have assessed that process through its artifacts: the persona, the interview synthesis, the business model canvas, prototypes, and so forth. Agentic AI can now produce those artifacts directly, which can break of obfuscate the link between artifact and learning. And yet, entrepreneurs are leveraging AI even more quickly than corporate America and so it can be argued that any course teaching entrepreneurial skillsets should incorporate some usage of and training on the use of AI. The risk of incorporating AI, however, extends to the transversal skills that are often a key outcome of these courses. Tolerance for ambiguity, teamwork, and problem-solving develop through friction (awkward interviews, disagreement, dead ends), and agents are very good at removing friction. How can entrepreneurship teachers encourage students to learn how to employ Agentic AI in their work in such courses, without interrupting the critical processes that students engage in that create these learning outcomes? One of the core problems is to identify which steps of the entrepreneurial process that are being taught in the given course can be delegated to AI, which to keep human, and why. The why question is critical, because if the leaners understand the why then they can understand how to make decisions for their own courses.

Those involved

Primary participants are instructors of entrepreneurship and innovation courses, particularly introductory or required courses serving non-business students. Many are being asked to integrate agentic AI by their institutions, with varying personal fluency in the tools and limited time to redesign. Secondary participants are instructors in other project-based learning contexts (capstone design, studio, service learning) whose courses share the same process-over-product structure.

Gap analysis

Conceptual understanding is a gap. Professors don’t know exactly what agentic AI is and how it differs from “regular” AI.

Professors lack training and fluency with agentic AI. In 2026, Agentic AI is a headline-driven factor with which educators are wrestling, and there are no agreed standards.

AI and Agentic AI have too often been pursued as standalone or one-off additions to courses, rather than integrated into the structure of a course in the way that a tool might be.

Assessment is a challenge with AI, and how to assess produced work in the world of AI is a gap. Grading artifacts of the educational journey has changed with AI. How does it change with Agentic AI, and on the meta level, when some level of mastery of Agentic AI is a learning outcome for students?

Other Existing Efforts

UNESCO's AI Competency Framework for Teachers sets out 15 competencies across five dimensions, and it has a companion student framework that emphasizes a human-centered mindset in which students understand and assert their agency in relation to AI. But this does not address agentic AI. At present, no courses with a similar intent have been identified.

Intent Statement

This course prepares entrepreneurship instructors to integrate Agentic AI into their courses in ways that strengthen, rather than short-circuit, the transversal skills those courses exist to develop. Participants will learn what distinguishes agentic AI from conversational or “regular” GenAI, examine what current research does and doesn’t tell us about its effects on student thinking, and use established competency frameworks to audit their own curriculum for points where agent use would help or harm learning. Through examples from an introductory entrepreneurship course, participants review activities that make deliberate choices about what students delegate to agents and what they should do themselves, and they will review assessment approaches that capture process and judgment rather than polished artifacts as gradable elements.

Analysis of the Learner and Context

The learners in this case are teachers of entrepreneurship and innovation courses who are seeking to add experiences to their classes that allow students to benefit from exploring the use of Agentic AI. They create and lead courses that may be optional or may be required, and may serve business or non-business students. Entrepreneurship courses are increasingly popular as electives for non-business majors, in addition to being popular with business majors.

Those who are interested in adding Agentic AI to their courses may be doing so because they have extensive experience with such tools and see their potential to integrate them, but they may as equally be people with limited to such experience, who feel that their course needs to add agentic AI to be competitive. They may even be in the position of being pushed by administrators at their institution to add Agentic AI in order to keep pace with other institutions.

Often they will need to be responding to this on a very short timeframe, and so this course will need to enable them to create a plan for what opportunities and methods exist for them to integrate into their teaching in a very efficient manner. Ideally, the course will provide them with a basket of independent strategies that they can use to deploy AI in their course, and they can pick from one or use multiple or all of them.

They may be fulltime professors but most often will be adjunct professors who have professional experience that is related to but not defined by their professorial role. Many will have significant years of business experience and will be able to identify in a narrow but deep context very particular use cases for AI.

Performance-Based Objectives

After completing this mini-course, learners will be able to:

Define Agentic AI and how it differs from "regular" GenAI
Identify appropriate learning units in their own courses where students may be able to apply Agentic AI in ways that allow them to explore and learn how it may benefit their work and advance their thinking
Understand the risks of deploying Agentic AI into learning units in their course
Assess the risks and benefits of using Agentic AI in their learning units
Articulate the research-informed benefits and risks that the use of Agentic AI poses to the development of the typical transversal skills that students develop in entrepreneurship courses
Refer to core examples of Agentic AI use in entrepreneurship courses
Create assessments for the use of Agentic AI in their learning units
Consider some of the ways the use of Agentic AI in their learning units might interfere with their existing lesson plans

Task and Content Analysis

instructions to be deleted: (MOD 7-8) For each course-level target objective, consider 1) what the participants need to know in order to achieve this objective (e.g. the prerequisites that enable or support the objective); 2) what specific learning content and activities may address the prerequisites and target objectives. Then consider how the learning contents and activities will be organized into a process of learning through several learning units (e.g. 3-5). See example Task Analysis).

Before taking this course, the learner:

Should have experience teaching a course in entrepreneurship, innovation, or a related field (pre-requisite)
Should have a background in and have a basic familiarity with AI (pre-requisite)
Should be interested in considering the deployment of Agentic AI tools or activities into a course that they teach (pre-requisite)