Hey, it's Sam.
Welcome to Week 3. Time to open up the engine room.
For two weeks, we've been focused on outputs: building blueprints, running critiques. We learned how to generate a V1 Blueprint and how to critique it with an AI Red Team.
This week, we’re shifting to the part that actually sets the ceiling for your results.
The inputs.
Why This Matters
I wasted my entire first year with AI.
Bought every prompt course.
Saved every "ultimate prompt" thread.
Built a swipe file of “god-tier” templates.
I thought a great output came from a perfect prompt.
It didn’t.
Here's when it clicked:
I was building a strategy for a major client. Spent two hours crafting this intricate prompt. Multiple personas. Detailed constraints. The works.
Then I fed it my client's notes - scattered emails, random PDFs, conflicting briefs.
The output?
Mediocre. Generic. Unusable.
That’s when it hit me:
The prompts weren’t the problem. The inputs were.
It’s like asking a Michelin chef to cook using expired ingredients from the garage fridge.
Doesn’t matter how skilled they are — garbage in, garbage out.
With AI, it's more like: mess in, vanilla out.
The Architect's Approach
Here’s the difference between builders and users:
AI users fixate on prompts.
AI architects obsess over inputs.
So what’s easier?
Spending hours tweaking prompts to make up for messy data?
Or organizing your data once so even basic prompts produce great work?
This week, we build the system that makes the second option possible:
Part 1: The Client Maturity Audit
Part 2: The Master Input Template
You’ll turn chaos into structured fuel.
Most people ignore this part because it’s not flashy.
That’s exactly why it works.
What If Average Wasn’t An Option?
Imagine never getting a meh output again.
Not because you found the perfect prompt, but because you built a system where average can’t survive.
Pristine inputs lift everything.
Chaotic inputs drag everything down.
Which game would you rather play?
Today’s Action (5-Minute Reflection) 🫵 💥
Get honest with yourself:
Think of your last disappointing AI output.
Review the input you gave it.
Now ask: "Did I feed the AI clean, company-grade data or a jumbled mess of scraps?"
Be ruthless. The distance between what you expected and what you gave it — that’s your leverage.
That’s what we’re fixing this week.
Tomorrow, we start with the Client Maturity Audit.
I’ll walk you through how to use AI to get a clear, objective read on any client’s strengths and weaknesses.
No fluff. No guessing. Just clarity.
Sam
P.S. Fair warning: The first time you audit your inputs, it stings. You’ll finally see why your results have been what they are. The upside? Once you see it, you can fix it.