Estimating in the Age of AI (Part 1): Shifting from Micromanagement to Flow Optimization
Why does capacity planning feel harder in the age of AI? Discover how shifting from micromanagement to flow optimization helps L&D teams estimate smarter.
The True Cost of Training: Mapping L&D Capacity to Business Outcomes
The true cost of training isn’t on your budget spreadsheet—it’s in your team’s capacity. Here’s how to map L&D bandwidth to business outcomes.
Book Review: A Practical Approach to AI Implementation in Learning Operations
AI tools don’t fix undefined problems. A review of Megan Torrance’s AI Implementation Guide for L&D — and what it means for learning operations teams.
The Post-Implementation Bottleneck: Operationalizing AI Workflows in L&D
The AI honeymoon in L&D is over — and handing your team a ChatGPT license isn’t a strategy. Here’s what it actually takes to operationalize AI workflows at scale.
AI-Native Learning Operations: The 5-Layer Stack
Understanding the 5-Layer AI Revolution In recent discussions, NVIDIA CEO Jensen Huang introduced a framework that helps us see AI not just as a software update, but as a full-scale industrial shift. He calls it the “5-Layer Cake.” If we only look at the top layer—the apps we interact with—we miss the massive infrastructure being […]
Beyond the Path of Least Resistance: Why L&D Needs More Than a General Productivity Tool
Written by Learning Leader, Debbie Richards. In the race to scale organizational learning, many companies fall into a common trap: they adopt the tools that are already “there.” Whether it’s Microsoft Forms for intake, ServiceNow for requests, or Monday.com for project tracking, these platforms represent the path of least resistance for IT. However, for those […]
