A practical framework for small business leaders who are done with inconsistent results
The question I hear most often is: which AI tool should we be using?
Honestly, the tool matters a lot less than what you build inside it.
The teams I see getting consistent, useful results from AI aren’t running better tools. They’re running the same tools (ChatGPT, Claude, Gemini) with something underneath them that makes everything work. Once you understand what that something is, the inconsistency starts to make sense.
The Three Layers AI Needs
Think of AI like a new team member who shows up ready to work but knows nothing about your business, your clients, or how things get done around here. To do good work, that person needs three things from you: an introduction to who you are, the materials relevant to the task, and some guidance on how the work gets done. AI needs the same things, and most teams haven’t given it any of them.
Know Me
The foundation that’s always on.
This is the background information AI needs to understand who it’s working for before you’ve typed anything. And “who it’s working for” can mean more than one thing.
Know Me isn’t a single document. It’s a category, and the same idea applies at every level:
The business. What the company does, who it serves, how it communicates, what it stands for, what it never does. Anyone on the team producing something public-facing should be working from this.
The client. If you work with clients, a Know Me file for each one means you’re not re-explaining their business, their preferences, or their communication style every time you produce something on their behalf.
The role. A manager, a department lead, a customer-facing rep, each of those people has a context specific to how they work, what they’re responsible for, and how they need to communicate. That context is worth capturing in its own document.
The individual. Someone using AI for a side project, a hobby, a personal workflow, the same principle applies. You tell it who you are in that context, and it stops treating you like a stranger every time you open a chat.
What goes into any of these:
How you like to communicate and receive information
Who your audience is and what works with them
Information that is important for it to consider when working with you
What you never want AI to assume
Most people either skip this entirely. When that happens, the results tend to feel like they could have come from anyone, because as far as the AI knows, they did. It’s not that the tool is underperforming, it just doesn’t know enough about who it’s working for.
This is the first thing I build with every client, and it’s the first place I’d point you to today.
Know the Work
The materials for the task at hand.
Know the Work is the content AI needs to actually do the job: the documents, data, and reference files specific to what you’re working on, things like a client brief, a style guide, a research doc, or meeting notes from last week. It’s what AI needs to read or reference to produce something useful rather than something generic.
This shows up in two situations. The first is a recurring task type where you’ve already identified what materials are needed and have them ready to load in. The second is something new, a request or project you haven’t handled before, where you’re pulling together the relevant materials as you go.
Know the Method
How the work gets done, documented so anyone can replicate it.
Where Know the Work is what AI needs to read, Know the Method is how you actually approach the task. It’s the process: what to ask for, in what order, with what constraints, and what a good result looks like. It’s the difference between handing someone a client file and also showing them how your team produces work from it.
This is the layer most teams haven’t built, and the one that tends to make the biggest practical difference.
Here’s something I see pretty regularly. Two people on the same team are given the same task using the same tool, and one gets a result she’s genuinely happy with while the other gets something that needs a full rewrite. The difference usually isn’t effort or skill. It’s that one person has worked out how to approach that specific type of task with AI and the other person is working it out for the first time.
Know the Method is that worked-out process, written down so it doesn’t have to be figured out again and likely restated differently each time, it answers how do we actually do this kind of work?
How we write a client update email
How we turn meeting notes into action items
How we research a product
How we review content for brand consistency
How we manage inventory
How our process runs (specs, information, steps)
When that knowledge lives in one person’s head, it walks out the door with her if she leaves. When it’s written down, anyone on the team can sit down and get a decent result without starting from zero.
One thing worth being intentional about: keep a folder somewhere you control (Google Drive, your desktop, wherever you already work) that holds the most current version of every context file and resource document we talked about in the Know Me, Know the Work, Know the Method sections.
Think of it as your source of truth, I create a folder called AI Knowledge and each of the files and resources I create and use go here. You’ll still need to upload or add those files directly into each AI platform you use, whether that’s a Claude Project, a ChatGPT GPT, or a Gemini Gem, or one off prompts, but your folder is where the current version lives. When something changes, you update it there first, then bring it into the platforms. That habit keeps things from getting out of sync across tools over time. Assign someone to be responsible for this.
What These Three Look Like in Practice
Say someone on your team writes a client-facing summary every week, a project update or results recap.
Without any of this in place, she opens a chat, explains the situation from scratch, gets a response that doesn’t quite sound like the business, rewrites most of it, and an hour later she has the report. How useful it turns out depends largely on how much she remembers to include that day.
BUT with all three in place:
Know Me has already told the AI the company voice, the client relationship context, what to leave out
Know the Work holds the specific report templates the project details, any reference documents that inform what gets reported
Know the Method lays out exactly how a client summary actually gets produced
She opens a chat, references what’s already there, adds what happened this week, and gets a first draft that actually sounds like the business in closer to five minutes. And when someone else writes the next one, they get the same result, because the process is written down and available to anyone on the team, or taught to the AI.
Where to Start
You don’t need to build all three at once! Please don’t feel pressure to do so.
Start with Know Me. Spend about 20 minutes in whatever tool you’re already using. Ask it what it already knows about you: your role, your business, how you work. Then fill in the gaps and correct anything that’s off.
From there, add Know the Work one document at a time, starting with whatever you reference most often. Know the Method tends to come naturally from there. Every time you work out a good approach to a recurring task, write it down. Over time, that becomes a working playbook your whole team can pull from.
The goal isn’t to have it all figured out before you start. It’s to build something that gets more useful as you go.
The Bigger Picture
Using AI well asks you to be clear about the objective, context, and specific about what a good outcome looks like. That’s not a new skill. It’s the same discipline that makes someone a good communicator in a meeting, with a client, or when delegating to their team. These are existing leadership skills you probably already possess.
When Know Me, Know the Work, and Know the Method are in place, you stop depending on one person who has figured out how to get good results from a tool and start building something anyone on the team can use. For a lot of the businesses I work with, that’s the point where it starts feeling less like an experiment and more like something worth building on.
Wondering which of the three you’re missing? I offer free 30-minute AI Clarity Calls, a focused conversation about where your setup has gaps and what to build first. Book yours.
Amanda Long is an external AI resource for small and mid-sized businesses. She works alongside teams to find how their operation actually runs and build AI into the places where it makes a real difference. She has been working hands-on with AI since 2022 and runs a monthly AI Lab for professionals who want to bring real questions and leave with something they can actually use.
