Most AI training ends with excited teams and productivity gains. But a few weeks in, people are spending their AI time re-explaining context. Skills — portable, shareable instructions that teach AI how to handle specific work — change that pattern and help training compound across an organization.
This is a guide for the people who get a little nervous when they need to open Terminal (or don't know what it is). I'll try to break down the complexity, simplify the buzzwords, and allow you to build something quite incredible within the next hour.
AI runs my week. I started this as an experiment to test the capabilities of the latest models over a year ago. Since then, it has become a core part of my daily workflow. This post outlines that system, how it works, how it helps me, and where it still fails to do the innately human stuff.
Why AI pilots stall in 'pilot purgatory' and why failure is often the signal that teams are learning fast enough to make the next model jump count.
A practical look at the 30-day Implementation Launchpad approach for mapping workflows, shipping focused pilots, and building AI agents that actually work.
At CES, it was obvious how wide the gap still is between knowing about AI and actually running it inside everyday work. Even advanced audiences can describe the tools but very few are operating with autonomous agents or the workflows that make them worth it.
The companies pulling ahead are the ones that keep failing fast, redesigning team structures, and shrinking the human layer to make space for always-on execution partners. That shift is already here, and most organizations are not ready for it.