A Better Way to Design Employee Training with AI

TLDR: This article presents a superior approach to using AI for employee training design through four focused prompts based on learning science principles, avoiding the common pitfalls of generic mega-prompts.

Summary

The author addresses a common problem many professionals face when tasked with designing employee training programs: limited time, budget, and instructional design expertise. The typical solution of using elaborate AI "mega-prompts" with multiple sections and detailed steps often produces generic, unusable content that needs significant revision.

The core issue identified is that trying to handle everything in a single prompt - needs assessment, curriculum design, timeline creation, assessments, and reinforcement planning - results in shallow treatment of each component. Additionally, early assumptions made by AI models compound into errors throughout the process, making the output difficult to fix without starting over.

The proposed solution is a staged prompting approach using four focused prompts, each handling a single job with learning science principles built in. This method produces training content specific enough to actually deliver, working across various skills including data analysis, client communication, software onboarding, and leadership development.

The article begins to outline the first stage - skill decomposition - which involves breaking down complex skills into manageable components that can be effectively taught and learned. This methodical approach ensures each aspect of training design receives proper attention and can be refined before moving to the next stage.

For architects and development teams, this approach demonstrates how to structure complex AI interactions by breaking them into smaller, manageable components. Rather than attempting to solve entire problems with single prompts, the staged approach allows for iterative refinement and ensures each component receives appropriate attention.

The learning science principles built into these prompts help ensure the resulting training is based on proven educational methodologies rather than generic content generation, making it more effective for actual employee development.

Key takeaways

• Mega-prompts that try to handle everything at once produce generic, shallow content
• Staged prompting with focused, single-purpose prompts delivers better results
• Learning science principles should be built into AI prompts for training design
• Breaking complex tasks into stages allows for iterative refinement and correction
• This approach works across various skill areas from technical to soft skills

Link: A Better Way to Design Employee Training with AI