The 31% Problem: How Systems Thinking (Not Just AI) Cut Our Development Cycle Time
The AI tools were 30% of the equation. The other 70% was systems thinking, planning, accountability, and trust.
Learning Operations
Intake systems, prioritization frameworks, workflow design, and the operating model behind L&D teams that move fast without burning out.
Learning Operations is the infrastructure layer of L&D. It covers how work gets in, how it gets prioritized, how it gets built, and how it gets measured. Most L&D teams treat it as a backlog problem. It's actually a systems design problem.
Everything here is written from direct experience running a 26-person global L&D team: intake that triaged hundreds of requests per year, workflows that scaled from 50 to 637 modules, and operating models that survived three platform migrations without losing quality.
How to Scope Every Training Request in Under 10 Minutes
A triage framework built on Thomas Gilbert's Behavior Engineering Model that separates real performance gaps from requests training can't solve.
Why Your L&D Team Doesn't Have a Playbook
The case for a minimum viable playbook when most L&D teams run on tribal knowledge.
How to Hire for Learning Operations
Operations-first hiring for modern L&D — why hiring IDs alone leaves the infrastructure unstaffed.
Why Your SME Review Process Is Broken (And How AI Fixes It)
The bottleneck isn't the SME. It's the process we built around them.
How We Built a Content Machine: From 50 to 637 Modules in One Year
12x content scaling in one year. What we built, what broke first, and what actually drove the number.