Let me tell you about a mistake I made for way too long.
Every time I sat down to use Claude or ChatGPT for client work, I'd start from a blank screen. I'd cobble together a prompt, get decent-ish results, tweak it manually, get better results, and move on. Then the next day I'd do the whole thing over again. From scratch. Like I had amnesia.
I was treating AI like a vending machine. Put in a coin, get something out, walk away.
That's not a system. That's just chaos with better grammar.
The shift happened when I stopped thinking about prompts as single inputs and started building what I now call a Prompt Stack. It's a layered, structured library of reusable prompt components that I stack together depending on the task. The result? Faster output, dramatically more consistent quality, and a workflow that actually scales.
Here's exactly how it works, and how you can build one this week.
Why Single Prompts Are Killing Your AI Output
Before we get into the system, let's talk about why most people struggle to get consistent results from AI tools.
The problem isn't the tool. It's that people treat every task like it's new.
A good AI output has three ingredients: context (who you are and what you're doing), instruction (what you want done and how), and constraints (what to avoid, length, tone, format). When you write a fresh prompt every time, you're rebuilding all three from zero. You miss things. You get inconsistent results. You blame the AI when the real issue is your input.
The Prompt Stack solves this by pre-building each of those three layers as reusable components. You plug in what you need, stack them together, and ship.
The Three Layers of a Prompt Stack
Layer 1: The Context Block
This is your foundation. It tells the AI who it's working with and in what capacity. You write this once and paste it at the top of nearly every prompt.
Here's mine:
"You are working with Jordan Hale, founder of The AI Newsroom. Jordan creates daily newsletter content for entrepreneurs and business owners who want practical AI implementation guidance. The tone is direct, conversational, and confident without being arrogant. Readers are time-constrained, results-focused, and skeptical of hype. Content should be immediately actionable."
That's it. Sixty words that eliminate roughly half the back-and-forth I used to do when fine-tuning outputs. The AI now has a frame for every single response it gives me.
For your business, your Context Block should include: who you are, who your customer is, your communication style, and one sentence on what success looks like for your output.
Write it once. Save it somewhere you can paste it in under ten seconds.
Layer 2: The Task Module
This is where you describe the specific thing you're trying to accomplish. Unlike the Context Block, this layer changes by task category, but you should have a library of pre-built task modules for your most common work.
For example, here are three task modules I use constantly:
Newsletter Edition Module: "Write a newsletter edition on [TOPIC]. The edition should open with a story or observation that draws the reader in, move into a clear problem statement, walk through a practical solution in numbered or structured steps, and close with a specific action the reader can take today. Target length is 2,000 words. Include subheadlines every 300 to 400 words."
Client Report Module: "Summarize the following data and findings into a client-facing report. Structure it as: Executive Summary (3 to 4 sentences), Key Findings (bullet list), What This Means (plain-language interpretation), and Recommended Next Steps (numbered, priority order). Avoid jargon. Write as if explaining to a smart non-expert."
Social Post Module: "Write five social media posts based on the following content. Each post should stand alone, have a hook in the first line, and end with either a question or a clear call to action. Keep each post under 220 characters for Twitter/X. Vary the angle across all five posts."
Notice how each module has a defined structure built in. You're not just saying "write me a social post." You're specifying format, length, angle, and goal. That's the difference between getting something usable and getting something you have to rewrite.
Layer 3: The Constraint Add-On
This is the layer most people skip, and it's where the magic is.
Constraints tell the AI what NOT to do. They're the guardrails that keep output from going sideways.
Build a set of standing constraints you add to prompts where relevant:
Tone constraints: "Do not use corporate jargon, filler phrases like 'in today's fast-paced world,' or vague platitudes. Write like a knowledgeable peer, not a textbook."
Format constraints: "Do not use em dashes. Use bullet points only when listing three or more items. Keep paragraphs to four sentences maximum."
Accuracy constraints: "Do not invent statistics, citations, or quotes. If referencing a concept, describe it accurately without fabricating sourcing."
You mix and match these based on what you're building. Some prompts get two constraints. Some get five. But having them pre-written means you're not reinventing them every time.
How to Stack Them Together
Here's what a finished stacked prompt looks like in practice. This is an actual prompt I used last week:
Context Block: You are working with Jordan Hale, founder of The AI Newsroom...Task Module: Write a newsletter edition about using AI for client onboarding automation...Constraint Add-Ons: Do not use em dashes. Do not use corporate jargon or filler phrases. Do not invent statistics. Keep paragraphs to four sentences maximum. Do not include a generic summary at the end.
That prompt took me about 90 seconds to assemble because I pulled from pre-built components. The output came back at 97% usable on the first pass. One light edit, done.
Compare that to a fresh one-off prompt that might take ten minutes to write and still require three rounds of revision. Over a week, across dozens of tasks? The Prompt Stack pays for itself over and over.
Building Your Own Stack: The 30-Minute Exercise
Here's how to get your own Prompt Stack built before you close this email.
Set a timer for 30 minutes. Open a Google Doc or Notion page titled "Prompt Stack."
First 10 minutes: Write your Context Block. Who are you? Who is your customer? What does good output look and sound like for your business? Keep it under 100 words. Be specific.
Next 15 minutes: List the five AI tasks you do most often. For each one, write a Task Module that specifies what you want, the structure you expect, and the target length or format.
Last 5 minutes: Write five constraint add-ons you'll use regularly. Think about the most common problems you run into with AI output and write a constraint for each one.
That's your first Prompt Stack. Rough edges and all, it's already better than nothing, which is what most people have.
The Tool That Makes This 10x More Useful
I run my entire Prompt Stack inside Make.com. Make lets me build automation scenarios that pull from my prompt library automatically, assemble finished prompts, send them to Claude or another model, and route the output wherever it needs to go. The result is a system that runs almost on autopilot for routine content tasks.
The free plan covers more than enough to build your first prompt automation. If you want to go from "I use AI sometimes" to "AI runs my workflow," Make is the infrastructure layer you need.
Want the complete Prompt Stack system, including templates, organization structure, and step-by-step setup? Reply with the word BLUEPRINT and I'll send you the details. It's $47 and it will pay for itself the first week you use it.
Tomorrow: AI-powered meeting prep. Once you see it, you can't go back.
Jordan Hale | The AI Newsroom | ainewsroomdaily.com