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"I know that I could be using AI much more than I am." — Sam Altman, Dec 2025 (Big Technology Interview, Paywalled).

"The overhang of what these models are capable of relative to what most people can figure out how to get out of them is huge and growing." — Sam Altman, Jan 2026 (OpenAI Town Hall).

The guy who runs the biggest name in AI admits he’s behind.

If the architect of the machine is struggling to keep up with its output, where does that leave your VP of Engineering? Where does that leave you?

The models are racing ahead exponentially, but organizational adoption is linear. This creates a vacuum.

And the people closing that gap fastest are the ones who were "non-technical" last year.

Logic suggests your most senior technical people should be the best at AI. They understand the underlying architecture. They know how systems think.

Reality says they are often the bottleneck.

For a senior developer, AI is a marginal gain. It makes them type faster, but it doesn't fundamentally change what they can build. They are trapped in their professional workflows.

For a non-technical operator in Ops, Marketing, or Sales, AI is an infinity multiplier. A true 0->1 technology.

It takes them from "I can't build this" to "I just shipped this."

Your cultural advantage becomes how fast your vibe-coders can teach your VPs to use and manage without making the VPs feel stupid. They know what will move the needle in the business, but they don’t know how to use AI to do it and they don’t have the time to learn.

Your senior leaders are stuck in Zoom all day. They don't have four hours of "play time" to figure out Replit or the latest Claude Code plugin. They are managing people, not exploring tools with family at home, no time for sleepless nights getting ahead of the adoption curve.

Second, senior team members have an "expert reputation" to protect.

Asking their report for help can feel like admitting weakness. Struggling to prompt a model feels like incompetence. So they stick to where they are already safe, fast, and knowledgeable.

The low-code operator has no opinion about code quality. They don't care if the Python script is elegant; they care if it automates the report properly. They have no shame in asking the "stupid" question because they were never expected to know the answer in the first place. That makes them ideal for fast moving breakthrough technology.

You can't hire your way out of this gap. You have to cross pollinate and educate.

This is what’s working for us (and our clients):

The "No Shame" Protocol: Set up 1:1 training where the best AI-using junior teaches the senior how to use AI to do what they used to do before they got promoted. Don’t make it optional.

This removes the ego barrier. The executive doesn't have to admit that they don’t know what a Project does in ChatGPT. As an added bonus: it energizes A-players by giving them permission to be beginners again (which they love).

The "Aha" moment happens when an exec realizes AI can take over the client account briefs they write every month, do half their Excel tables for them, and still have time to analyze their LinkedIn posts.

Bounties for Breakthroughs: Pay for shared learnings.

If a junior figures out a workflow that saves five hours of manual data entry every week, bonus them. If they build a tool that replaces a $10k agency retainer, bonus them handsomely. Give them money and accolades, I guarantee your top AI users are not getting enough of either.

Signal loud and clear that knowledge is rewarded and spread.

Skill Shares: Every other week we get on a team call and share what we’ve been doing with AI. Some people have apps they’re building, others are playing with new SaaS tools, and some just have a really great prompt. Everyone has to share.

2 Questions: Why did you you want to share this? What did you learn the hard way in process? Over half our bounties get awarded through these sessions.

The Penny Wise Trap: Don't get sticker shock at a $3000/month AI bill for an agent that does the work of a $10k/month employee. It will be half the cost in 6 months and a tenth in 12.

You have to fund the R&D phase, it’s rarely very long and the payoff has no upper limit.

In the age of Capability Overhang expertise can become a deadweight drag in just a couple weeks. You need people whose love of learning creates a vortex that pulls the rest of the org forward.

The models aren't waiting for you to catch up. And neither is your junior analyst.

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