AI Enablement in the Real World: 30 Minutes, $200K on the Table

I recently ran an AI coaching session with the CEO of an 8-figure e-commerce company focused on one very specific business problem: building the evidence package for an R&D tax credit worth roughly $200,000.

This was not a generic “here’s how to use AI” walkthrough.

This was practical executive

AI enablement: connect the right tools, structure the project clearly, point the model at the right company knowledge, and use AI to accelerate work that normally gets buried in documents, folders, reports, and institutional memory.

In under 30 minutes, I showed the CEO how to use Claude with the company’s Google Drive, how to describe the tax-credit project in a way Claude could actually work with, and how to prompt Claude to search for rich supporting evidence across the company’s internal files.

The goal was not just to “ask Claude questions.” The goal was to teach a repeatable workflow:

define the business objective, identify the evidence needed, connect the right source material, include existing team work, and guide the AI toward a usable business outcome.

We also talked through what additional context Claude should have beyond Google Drive. That included reports his team had already prepared, so existing work could be included instead of forgotten, duplicated, or left sitting in some folder nobody had time to dig through.

That part matters. A lot of business AI value is not magic. It comes from knowing how to frame the problem, how to feed the model the right context, and how to make sure the company’s existing knowledge actually gets used.

By the end of the session, the CEO had what he needed that same day to move forward with the R&D credit submission.

In his words, the workflow could have saved him a month.

That is the kind of AI consulting I am building Wolfpack around.

Not hype. Not vague transformation theater. Just practical AI workflows applied directly to real business problems with real money, real deadlines, and real operational pressure.

Even though this session focused on a tax-credit project, the skills transfer immediately across executive and operator workflows: diligence, finance, operations, vendor research, board prep, customer analysis, internal documentation, strategic planning, and any project where the answer is somewhere inside the company’s own information.

This is where AI becomes powerful for leadership teams. If you are interested in learning AI by working on actual projects, Wolfpack can help.

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