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In February 2026, the U.S. Department of Labor's Employment and Training Administration released a national AI literacy framework, providing five foundational content areas and seven delivery principles to guide workforce training across the country. This is not conceptual guidance sitting in a policy archive. Within six weeks of its release, the DOL launched a free AI literacy course reaching American workers via text message. By May 2026, the Department of Commerce had anno

Assessment is the most under-discussed part of the AI conversation in learning and development. Most coverage focuses on content creation: instructional designers using AI to draft modules faster, scripts for video, slide decks pulled together in minutes. The harder question is whether AI is improving how we measure learning, or quietly making our assessments less defensible. By 2026, both are happening at once. This post breaks down where AI is genuinely strengthening asses

The conversation around AI in training has largely centered on tools: which one generates slides faster, which writes better scripts, which summarizes source documents with fewer hallucinations. That conversation is not wrong, but it is already becoming outdated. The next phase is agentic AI, and it operates differently. Instead of waiting for a prompt and returning a result, agentic AI systems plan, act, and iterate across multi-step tasks with minimal human input. For trai

Most training developers are familiar with AI as a prompt-and-response tool: you ask, it generates, you edit. That model is not going away, but it is no longer the only one worth knowing. AI agents represent the next step, and in 2026 they are moving from early experimentation into production workflows across L&D teams. According to Google Cloud's AI Agent Trends 2026 report, 65 percent of organizations are now actively experimenting with AI agents, and 84 percent of enterpr

The ADDIE model has been the backbone of training design for decades. AI does not change that. What it changes is how long each phase takes, what you can produce within each one, and where your time is best spent. For training developers who already work within this framework, the question is not whether to use AI, but where in the process it actually pays off. This post walks through each phase of ADDIE with specific, practical examples of where AI adds value and where your

In 2025, most training developers were experimenting with AI occasionally, on individual tasks, when the timing felt right. In 2026, that experimental window is closing. According to Synthesia's AI in Learning and Development Report 2026, 87 percent of L&D professionals now feel comfortable using AI, and 36 percent are using it in defined, repeatable workflows. The question is no longer whether AI belongs on your training team. It is how to structure the collaboration so it p

Most training developers using AI are focused on what it can do. Fewer are asking what they should be doing responsibly. Here is a practical look at privacy, bias, and whether you should disclose AI use in your training materials.

Most people use NotebookLM just for its AI podcast feature. Here are 8 other outputs — including a workflow for building fully editable slide decks — that training developers should know about.

Tested all four AI tools for building slide decks. Here's an honest breakdown of what each one actually delivers — and which to reach for depending on your situation.

AI tools will keep evolving indefinitely — so the smart strategy isn't to wait for things to stabilize. Here's how to start building your team's AI skills now without burning everyone out.

82% of organizations now provide AI training. 59% still report an AI skills gap. The problem isn't intention — it's design. Here's what the research says training developers are getting wrong, and how to fix it.

Vibe coding — using AI to build interactive tools without knowing how to code — is genuinely useful for trainers, but only for the right tasks. Here's an honest breakdown of when it's worth your time and when to walk away.

Moving from experimenting with AI to making it a reliable part of your daily workflow isn't about revolutionary change — it's about finding the specific moments in your process where AI saves the most time.

Tired of AI defaulting to lecture-format courses? Learn how a simple markdown context file gives any AI tool your training preferences—and dramatically cuts editing time.