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Was the training successful? How AI can help you measure the effectiveness of your training.

The way most law enforcement training is delivered does not match the way memory works. A four-hour course, delivered once, with a test at the end, is efficient to schedule and easy to document in a learning management system. It is far less effective at producing the durable recall officers need when they apply policy and technique under stress. The research behind that gap is neither new nor ambiguous. Microlearning, meaning short, frequent, and deliberately spaced trainin

We've all sat down for a training session and been handed a printout of the slides with the lines beside them. The instructor advances through slides while everyone reads along. The slides carry the background, the key points, the examples, and the policy language, and the instructor narrates what is already on the screen. Nobody is fully listening because everybody is reading. That format is not a failure of design judgment. It is the downstream result of a documentation gap

Training video used to mean a camera, a presenter, a quiet room, and a long edit. In 2026, a growing number of training developers are producing finished video by typing a script and choosing a digital presenter. AI video avatars have moved from novelty to a standard option in the L&D toolkit, and the platforms behind them are now valued in the billions. Speed is the obvious draw. The harder question for experienced training developers is where avatar video actually improves

Every learning technology vendor now claims its AI can build a course. For training developers who have spent years inside Storyline or Captivate, the useful question is narrower: can AI produce online learning that is genuinely better, not just faster to assemble? After testing it directly on two real modules, the honest answer is that AI changes some parts of e-learning development dramatically and barely touches others. This post walks through what happened when I rebuilt

Every learning technology pitch this year seems to include the word "agent." Agentic AI, software that plans and executes multi-step tasks on its own, has replaced generative AI as the dominant theme in L&D. The promise is appealing: a system that identifies skill gaps, assigns content, monitors progress, and adapts learning paths without a human touching anything. The reality is messier. Adoption is real but early, the failure predictions are serious, and the biggest gap is

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.