In this course, you will learn how to create AI roleplay agents that reliably train specific selling skills—and how to do it in a way that is scalable, repeatable, and instructionally sound. L&D and instructional design teams are often asked to “build roleplays” quickly, but speed without structure leads to inconsistent experiences, unclear assessment, and low adoption. This course provides a disciplined build methodology so your agents produce consistent practice outcomes and align to your competency model.You will explore three creation pathways:(1) building agents from real sales calls to preserve authenticity and capture “what great looks like,”(2) building agents from prompts to rapidly test new scenarios and emerging use cases, and(3) building agents from templates to standardize practice for common call types (cold call, discovery, objection handling). For each pathway, you will learn how to set context, define success criteria, design objection and tone behavior, and connect the experience to a scorecard so performance can be measured.By the end, you will produce one complete roleplay agent and an accompanying instructional spec: learner goal, constraints, scoring rubric, remediation tips, and recommended practice cadence. You will also learn how to avoid common simulation pitfalls—over-scripting, unrealistic buyer behavior, and assessments that measure knowledge rather than performance—so your program can scale across teams and regions with quality intact.Throughout the course, you will work from an L&D perspective: you will translate sales competencies into observable behaviors, choose the right practice modality, and define evidence for mastery. Each lesson includes a practical build artifact—persona brief, scorecard, or rollout plan—so you can apply the content directly to your enablement roadmap.
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