AI and Just-in-Time Learning
What you'll walk away with: the ability to evaluate AI-generated learning assets against microlearning design principles and know what to fix.
Grab a block
AI changes what's possible for just-in-time learning — but not everything it generates passes the design test. Each block examines one intersection of AI and microlearning design.
01
AI-generated job aids
AI can draft a job aid in seconds. The design question is whether it should.
What AI gets right — and what it misses
02
Adaptive micro-delivery
AI-sequenced content based on individual performance data.
The branching rule worth adding today
03
Chatbot as performance support
The promise of Moment 4 (Solve) at scale — and why most implementations fail.
Search engine vs. support tool
04
AI content chunking
Automated decomposition vs. intentional design — and why the gap matters.
Why AI chunking fails the structural test
05
Quinn's performance ecosystem
AI as the connective tissue between micro-assets, not a replacement for them.
The routing problem AI actually solves
Anti-pattern
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Auto-chunking that ignores objectives
AI splits content by topic similarity, not by what the learner needs to do.
Why AI microlearning usually isn't
AI is the first Moment 4 technology at scale
Research: AI-powered support reduces time-to-resolution by 35% for novel problems.
35% faster — cite this