Operationalizing AI: Proven workflows that generate measurable revenue Clio

Operationalizing AI: Proven workflows that generate measurable revenue

 Clio

Your best knowledge goes with your people

Let’s say a new SEO or AEO hire takes six months to onboard. They compose everything they learn in their heads. Then they leave, all that compound is gone, and the team starts over again.

Panopto’s research he puts a number on it: 42% of institutional knowledge is unique to the person who owns it, so when he leaves, his colleagues can’t do 42% of their work.

This is how we have always worked. Around September 2025, the situation changed.

Everyone uses artificial intelligence. Few are making it worse.

At MozCon, a good portion of the room raised their hands when I asked who uses Claude Code or Codex. When I asked about autonomous agents like Hermes or OpenClaw, I counted about three hands.

This is an audience that is very familiar with artificial intelligence, and I bet most of them don’t use these tools in any meaningful way anyway. BCG found the same gap in 1,250 companies: only 5% achieve AI value at scale, while 60% achieve little or none despite massive investments.

People who move faster stopped writing tips. On X we instead talk about loops. For weeks I couldn’t figure out what a loop was and I’m not a technical person. But if faster moving works that way, it doesn’t make sense to me not to. It doesn’t make sense for you not to either.

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