Nathaniel Whittemore

Now, I think if you try to take this argument together, the subtext of what Seb is arguing is something that I agree with wholeheartedly, which is that AI use is now a core primitive of organizational operations.

It is not something that can be outsourced or externalized because it is functionally core to how we work going forward.

Taking the time to build this, then, is actually doing double duty.

It is building the new muscles that need to be built, while also building the system that can help those muscles flex to actually do things that the business is tasked to do.

The last section of Seb's piece is called What We Learned, and it's basically an argument for learning by doing.

He writes, "...the people who got the most value weren't the ones who attended our training sessions.

They were the ones who installed a skill on day one and immediately got a result.

The product taught them faster than we ever could."

This realization reframed how we think about the entire project.

Every feature in Glass is secretly a lesson.

Skills show you what great AI output looks like before you know how to ask it for yourself.

Memory shows you that context is the difference between a generic answer and a useful one.

Self-healing integrations show you that errors aren't your fault, the system has your back.

None of this was designed as education, but it turns out that when you hand someone a tool that just works, they learn by doing and they learn fast.

Seb concludes, this is what excites me most about what we're building.

Not the product itself, but what happens to an organization when the floor rises for everyone at once.

When a new hires for a session in Glass already knows their team, their projects, and their tools.

When someone who's never opened a terminal is running scheduled automations that would have required an engineer six months ago.

The compounding is real and we're only at the beginning of it.

We don't believe in lowering the ceiling.