Disclaimer: This guide documents BETA software. The information in this article is subject to change as Docebo continuously updates its software to address evolving market needs, leverage new technologies, fix defects, and incorporate customer feedback.
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Introduction
The Reinforcement agent turns course completion into an ongoing learning experience by automatically scheduling follow-up practice sessions and delivering in-platform notifications when sessions are ready. The Reinforcement agent is proactive: it runs automatically in the background based on course completion triggers and cannot be initiated manually from the agent menu. Superadmins and Power Users have the ability to manually trigger reinforcement sessions for testing purposes in the course agents configuration menu. To ensure all features of the reinforcement agent work for testing purposes, make sure the Superadmin or Power User you are testing with is actively enrolled in the relevant course.
Activation and configuration
Superadmins and course administrators manage the Reinforcement agent through a combination of platform and course-level settings:
- Global enablement: Superadmins enable the agent in Agent Hub and configure its global branding (icon, color, title, and description). Ensure the “Search and discovery” AI assistant capability is enabled for all users in the Artificial intelligence control panel.
- Course-level opt-in: Administrators with required permissions explicitly enable reinforcement on a per-course basis within the course settings ("Agents" tab).
- Cadence configuration: Set the reinforcement schedule and session frequency per course to control how practice moments are spaced out over time.
- Content eligibility: Ensure course materials match the supported content types for text extraction and transcript generation (such as Creator lessons, uploaded documents, audio/video transcripts, or supported SCORM/xAPI packages) so the agent can extract content to build practice activities.
Capabilities
- Trigger reinforcement automatically on course completion
- Dynamically adjust difficulty and content per user, based on the interaction history
- Build progressively across sessions without repeating covered ground
- Deliver interactive reinforcement activities with contextual feedback
Use cases
- New-hire onboarding retention: Automatically space out policy, culture, and operational check-ins across a new hire’s first 30, 60, or 90 days to increase long-term recall without manual manager follow-up.
- Sales and product enablement: Keep product differentiators, positioning, and objection-handling talk tracks top of mind after a major launch or enablement push.
- Frontline and compliance training: Reinforce critical safety protocols or regulatory standards through short, digestible practice moments delivered directly in the platform.
Best practices
- Enable selectively: Focus reinforcement on high-impact courses with substantive content where long-term retention directly affects job performance.
- Align cadence with course depth: Match session frequency to the complexity of the material, avoid long reinforcement sequences for lightweight or simple courses.
- Verify material readiness: Ensure course assets contain clear text or video transcripts before enabling reinforcement so the agent has accurate source context.
- Use for practice, not evaluation: Position reinforcement sessions as supportive learning practice rather than a replacement for formal course assessments or certifications.