Designing AI-assisted authoring tools for workforce learning
Amplifire is a workforce learning platform built on decades of cognitive science research, helping organizations create more effective training experiences through adaptive learning methodologies.
As AI capabilities began entering mainstream software products, Amplifire saw an opportunity to streamline course creation and content development for subject matter experts and instructional designers. Worked across both the learner-facing experience and a new suite of AI-assisted authoring tools designed to help teams create educational content more efficiently while maintaining quality and instructional rigor.
Challenge
Creating high-quality educational content is a time-intensive process.
Course authors often spend significant time transforming source materials, subject matter expertise, and organizational knowledge into structured learning experiences. While AI presented opportunities to accelerate content creation, the challenge was ensuring generated content remained accurate, reviewable, and aligned with educational goals.
The product needed to balance automation with control, allowing users to move faster without sacrificing confidence in the output.
Approach
The design process focused on identifying where AI could remove friction while keeping educators and content creators firmly in control of the authoring process.
We explored workflows that allowed users to:
- Upload and reference existing knowledge sources
- Generate course structures and learning objectives
- Draft educational content and assessments
- Review and refine AI-generated materials
- Maintain oversight throughout the creation process
Rather than treating AI as a replacement for expertise, the experience positioned AI as a collaborative tool that helped authors move from initial ideas to working course content more quickly. A major focus of the work was designing clear feedback loops and review workflows so users understood what content had been generated, modified, or approved before publication.
Outcome
The resulting experience enabled authors to accelerate content creation while maintaining ownership of the educational process. By combining AI-assisted generation with structured review workflows, the platform supported faster course development without compromising instructional quality or educator trust.
The project also provided valuable early experience designing human-centered AI systems, reinforcing principles that continue to influence my work on AI-powered enterprise products today.