What We Learned From 15 Hours of Anthropic Certification Training

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Fifteen years ago, I took my first online course on edX, a learning provider founded by MIT and Harvard. At the time, edX was cutting edge and I binge-watched a ton of courses. (I still love and recommend Michael Sandel’s course Justice, but that’s beside the point.)

I found myself recalling that time when I took four courses earlier this summer to earn our team Anthropic certification. After working closely with the Anthropic team for more than a year as alpha testers of unreleased models, we wanted to take our partnership farther. I went into the certification process curious about what level of instruction they’d provide and how they’d define their own tools. What I came away with was new insight into the state of AI development and industry standards right now.

AI development is still moving at a breakneck pace, but new releases no longer upend our work the way they used to. Anthropic’s Opus 4.5 and OpenAI’s GPT-5.5 marked a turning point as the models could reliably perform the tasks we provide, giving each subsequent release a dependable base to build on. The fact that Anthropic can even release a training course for its foundational tools like Claude Code and agent skills is a milestone for the AI era. (This time last year, I was constantly reworking the curriculum for our training sessions every three to six weeks when a new, more capable model came out.)

More stable models have allowed people to build AI workflows around their individual roles and careers. Anthropic’s training takes the opposite tack—it teaches foundational concepts. But the greatest value of these courses may not be sparking new ideas for the tools we use day to day. Instead, they offer an opportunity for the industry to align around terms and definitions—a heavy lift on its own.