eLearning Industry's Guest Author Article Showcase [April 2026]

"Most AI-powered learning tools send far more to the AI than they need to. According to Brady Licht, there's a way around this. By handling what you can with structured data and saving the generative call for what you genuinely cannot, you get tools that are cheaper, more reliable, and often produce better results."

"Dr. Athena Stanley's article explores eight practical ways L&D professionals can use images with LLMs to strengthen Instructional Design workflows, turning visual artifacts such as whiteboards, notes, environments, and dashboards into actionable learning insights."

"Filip Kokotović presents four reasons why skills-based learning is the most effective training approach for adult learners, as it is practical, engaging, and adaptable across delivery formats."

"Elizabeth Sramek's article shows L&D professionals how to adapt five core start-up marketing measurement principles-attribution modeling, cohort analysis, CAC-style cost accounting, experiment velocity, and payback periods-to finally measure training programs the way the business measures everything else."

Most AI-powered learning tools send more information to AI systems than necessary. A structured-data approach can handle what is determinable while limiting generative calls to cases that truly require them, reducing cost and improving reliability. Large language models can support instructional design by using images to turn visual artifacts such as whiteboards, notes, environments, and dashboards into actionable learning insights. Skills-based learning is presented as more effective for adult learners because it is practical, engaging, and adaptable across delivery formats. Training measurement can be improved by applying startup marketing measurement principles, including attribution modeling, cohort analysis, CAC-style cost accounting, experiment velocity, and payback periods. Traditional assessment methods may miss student strengths, and an AI-enabled approach can continuously analyze diverse learning behaviors for more accurate skill recognition.

Read at eLearning Industry