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Let me show you two versions of the same Tuesday morning.

Version A:

You need to prep a business review for your VP:
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First, you open an AI tool.
Then type: "Help me write a business review."

Which gives you a clean, generic structure.

Then you spend the next two hours filling it in, deleting the parts that don't fit, and rewriting the parts that sound like a template.

Version B:

Same task. But you have a folder.

It has:​
last quarter's review,
notes on what your VP always asks about,
your team's top three priorities for the year,
and a bullet list of what landed well last time and what fell flat.

You drop that folder in.
Ask AI to draft the review.
4-minutes later you have something 80% done.
Then, you only need to spend 20 minutes making it yours.

Same tool. Completely different outcome.

The difference between spending 4 hours editing versus 20 minutes isn't the prompt, it's the context around the prompt.

The frame most people are missing

Right now, most professionals sit at one of three levels with AI:

Level 1: AI Curious. You use it occasionally. ChatGPT for a quick draft. Maybe a summary. You're experimenting but it's not in your workflow yet.

Level 2: AI Assisted. AI is in your daily work. You prompt it regularly. You save time on certain tasks. But you're starting every conversation from scratch, re-explaining your role, your project, your standards. Every single time.

Level 3: AI Native. AI doesn't just help you execute. It helps you think. And it can do that because you've built a system it can actually read.

Most people think they're at Level 3, while they are really at Level 2.

What's the gap between those two?

The context layer.

Which may sound like we are repeating the same message over and over again, but it's really that simple!

So, how do we build our own Context Layer that Levels us up from Level 2 to Level 3?

Down below, I've shared my personal 3-layer system for how I'm personally approaching this problem - steal it and level up your workflow immediately:

The 3-layer system

Layer 1: People​
This is you.

Your job is no longer just execution, but rather it's to make the call at the beginning (what are we trying to do, and why does it matter) and the call at the end (is this good, and does it reflect my judgment).

The middle, the research, the drafting, the formatting, the compiling, that is not where your brain needs to live anymore.

This reframe alone changes how you use AI.

You stop thinking "how do I get AI to help me write this" and start thinking "what decision am I making here, and what does AI need to know to help me make it well."

Layer 2: Agents​
This is AI doing the middle work.

Not one prompt.
A system.

You give it a goal, the right tools, and enough context to act without you micromanaging every step.

Think of it like a new hire.

If you handed a new hire a task with no background, no examples of what good looks like, and no access to past work, they'd produce something generic.

Give them a thorough onboarding and they produce something useful (but still work that needs reviewing at the beginning).

Your AI tools are the same! The quality of the output is a direct reflection of the quality of the onboarding you've given them.

Layer 3: Context​
This is the piece almost nobody builds.
And it is the only layer that compounds.

Context is the readable record of how you work. It includes:

• How you and your team make decisions
• What good work looks like in your specific role
• Past projects, outcomes, and lessons
• Stakeholder preferences and communication patterns
• Your SOPs, even if they're rough

When you build this and give AI access to it, something changes...

The outputs stop being generic, but rather they start sounding like someone who actually knows your work!
Because now, someone does.

What this looks like in a real job

One team I came across had built a simple version of this.
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For every major project, they kept a running document:

• Key decisions made and why.
• What the stakeholders cared most about.
• What format worked in previous reviews.
• What questions always came up.

When it was time to prep for a quarterly review, they dropped that document into their AI workflow. The draft came back specific, accurate, and in the right tone for the right audience.

But, (here is what I don't want you to miss) despite being able to automate their workflow, they actually spent more time thinking.

Why?

Because the execution was handled and they could focus on what actually required judgment.

That's the shift.
Not less work, but better work on the things that matter.

The one thing to do this week

You don't need to build the whole system at once.

Start with one folder.
Call it whatever you want.

And drop in three things:

1. A description of your current role and what success looks like in it
2. Notes from your last three major projects, what went well, what didn't, and what you'd do differently
3. How your key stakeholders communicate and what they actually care about

Next time you sit down to use AI for something real, start there. Give it that folder first.

That is your first context layer. (and it won't be perfect!)
But, it'll still be better than starting from scratch every single time.

The professionals who compound with AI are not the ones chasing every new tool. They are the ones building the thing that makes every tool work better.

Reply and tell me:

Where are you right now?

Level 1, 2, or 3?

And what's the one thing in your work you wish AI actually understood about how you operate?

I will try my best to respond and read every reply.

And if this was useful, forward it to one person on your team who's still starting from scratch every time.

It'll make you look a lot smarter for being the one to share it and it'll help me out a lot as I grow this newsletter going forward.

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