Your Brain Is a Warehouse. Here Is What That Means for Mentorship, AI, and Go-to-Market.
Think about a Home Depot on a Saturday morning. People are not there to buy the whole store. They come in for one specific thing: a drill bit, a specific gauge of wire, the right caulk for a wet room. They know something needs fixing. They are not always sure exactly what. But they walk in, find the right tool, and walk out ready to do the work.
That is how I think about the knowledge I have built up over the years. The warehouse is my brain. Everything I have learned across industries, projects, teams, and a genuinely uncomfortable number of 11 PM crises lives in there. When someone sits down with me for a coffee chat, or walks into a mentoring session, or brings me in on a complex operational problem, they are not trying to take home the whole warehouse. They are coming in for a specific tool.
My job is to hand them the right one.
## The Home Depot Pro Who Actually Explains Things
There is a version of mentorship that is basically just handing someone a wrench and wishing them luck. A lot of it looks like that, honestly. You get the contact, the introduction, maybe a thirty-minute call where someone tells you to "just figure it out" or "trust the process." The tool is technically in your hand, but you have no idea what to do with it.
Home Depot figured this out. They have the pros. The people in the orange aprons who do not just point you to aisle seven but actually walk you through why you need a particular type of fastener, how the material behaves, what will go wrong if you skip a step. That is the other half of the job.
For me, that shift from warehouse to educator has been the more interesting part of the work. You move fast, you learn across a lot of different environments, you accumulate enough pattern recognition that you start to see what other people cannot yet see. And then the question becomes: how do you get that out of your own head and into someone else's hands in a way they can actually use?
You teach. You explain. You get people to the point where they can go do the work themselves, without you standing next to them. That is the measure. Not whether they needed you once, but whether they needed you less the next time.
## The Problem with Handing Someone a Tool They Do Not Understand
AI is doing something interesting to this, and not entirely in a good way.
Right now, a huge number of people are walking around with extraordinarily powerful tools in their hands and very little understanding of how to adapt them. They know how to prompt. They can get an output. They are confident in the result because the result looks polished and authoritative. But the thing about a tool is that it will do exactly what you ask it to do, even if what you asked was the wrong question.
The human feedback loop that used to correct this is getting short-circuited. The one-on-one interactions, the small failures, the moment when someone you respect tells you that your thinking has a hole in it: those are the mechanisms that teach you how to distinguish good information from bad information. They are how you learn to calibrate. And they are uncomfortable, which is part of why they work.
We do a genuinely bad job of accepting feedback when we are young, and maybe at other ages too. Part of it is that when you are early in your career, you do not know what you do not know, and that confidence feels like competence. Nobody has told you yet that the way you are doing a thing is not quite right. And because AI will not tell you either, because it will cheerfully help you do the wrong thing more efficiently, the blind spots compound.
AI should be making us communicate more with each other. That is what I keep coming back to. The tool should be sharpening the question you bring to a real person, not replacing the conversation entirely. The most useful thing AI could do for someone early in their career is help them articulate a better question to take into a mentoring conversation. Instead, a lot of people are using it to skip the conversation altogether.
Failure teaches you things that tools cannot. Failure in a communication, in a relationship, in a business transaction. You learn bit by bit. Each piece of bad information you run into and recognize as bad teaches you something about how to read the next piece. That calibration is built through real interaction, and it does not transfer well through a screen.
## Mapping the Warehouse to a Go-to-Market
The warehouse metaphor is not just personal. It maps onto how businesses should think about their value chain and their partnerships, too.
When you are building a go-to-market strategy, one of the first things you need to do is map out where knowledge and tools actually move in your system. Which parts of your chain are producing something of real value? Where is information being exchanged, and is that exchange monetized or not? Those are different questions, and conflating them is a fast way to leave money on the table or over-charge for something that should be free to build trust.
Think of it in terms of six concentric circles. At the center is your core: the proprietary knowledge, the frameworks, the accumulated expertise that nobody else has. Moving outward, you have the tools you have built from that knowledge, the processes and structures that make those tools usable, the partnerships that extend your reach, the audiences those partnerships connect you to, and finally the broader ecosystem that your whole system sits inside. Each circle is a different kind of exchange. Some of it you charge for. Some of it you share because sharing is what builds the outer circles that eventually support the inner ones.
Partnerships sit in that middle territory, and they get structured badly all the time. The instinct is to negotiate a fixed split: you bring this, I bring that, we divide the outcome evenly. The problem is that a fixed split is a snapshot of a relationship that is going to move. Capacity changes. Volume changes. The person who was doing seventy percent of the work in month one might be doing thirty percent by month six.
Negotiate on real-time capacity and volume instead. Build the partnership around what each party is actually contributing at any given point, not around a static agreement made before either of you knew what the work would actually look like. That is how you stay aligned. That is how the partnership does not quietly break down six months in when the contributions have shifted but the split has not.
## What the Tool Can and Cannot Do for You
I can hand someone a framework. I can explain how to use it. I can walk them through the thinking behind it, the failure that built it, the specific context where it works and the context where it breaks. That is the Home Depot pro version of the job.
What I cannot do is make someone use it well in the field. That part is on them. And it requires the real thing: conversations that push back, failures that recalibrate, feedback that stings a little because it is accurate. No tool replaces that, and the ones that try to are doing the person a disservice.
The warehouse is full. The door is open. But if you come in and grab a tool and walk out without understanding what you have got, you are going to build something crooked. The goal is not to make you dependent on the warehouse. The goal is to get you to the point where you know exactly which aisle you need, and why.
That is what good mentorship looks like. And it is what AI, for all its reach, still cannot fully replicate.