Custom AI Course Prompt Architecture
Design a personalized, action-first executive course with one structured prompt.
- Difficulty
- Easy
- Time to result
- ~days to results
- Steps
- 6
- Confidence
- 98%
This architecture treats course generation as a specification problem rather than a request for general information. First, assign the model a hybrid persona representing the teaching, research, and operating perspectives needed. Then define the exact course, learner, duration, and transformation sought. Translate those goals into mandatory lesson components such as objectives, core insights, actions, prompts, tools, deliverables, and reflection questions. Add negative constraints that reject lectures, summaries, beginner material, and generic best practices. Finally, control verbosity and formatting so the entire curriculum can be returned without truncation. The resulting prompt functions as a reusable course-design template: change the persona, audience, subject, duration, or learning style while retaining the underlying specification.
Origin
Extracted from Marketing Against The Grain, where the host explains the iterated prompt used to make O3 generate a four-week executive AI marketing course.
Core principles
- 01Assign the AI a relevant hybrid expert persona.
- 02Define a precise learner, outcome, duration, and course title.
- 03Demand real work products instead of passive theory.
- 04Specify the response structure and prohibited content.
- 05Constrain length so the complete course fits in one response.
- 06Iterate the prompt until fluff and generic advice disappear.
How to run it
- 1
Assemble the Expert Persona
Tell the model which complementary experts it should emulate, combining academic knowledge with practical operating experience.
Pro tip Choose perspectives that cover theory, technical depth, and real-world execution.
Watch out A prestigious persona alone will not produce an actionable course.
- 2
Define the Learning Transformation
Name the course and specify its duration, audience, starting sophistication, and desired capability.
Pro tip Describe the learner by role and responsibility rather than using a broad label.
Watch out An undefined audience encourages generic, introductory material.
- 3
Specify the Lesson Contract
List every required component for each lesson, including its objective, insight, actions, prompts, tools, and deliverable.
Pro tip Require each lesson to produce a real artifact relevant to the learner's work.
Watch out Do not leave the output structure for the model to infer.
- 4
Install Negative Guardrails
State what the course must not contain, such as lectures, summaries, fluff, or regurgitated best practices.
Pro tip Turn each disappointing output from an earlier run into a new explicit prohibition.
Watch out Positive instructions alone may not suppress familiar but low-value material.
- 5
Constrain the Delivery
Set time limits for lessons and require concise bullets or short sections so the full course fits within output limits.
Pro tip Ask for concise yet complete material rather than merely requesting brevity.
Watch out An oversized specification can cause later weeks to be compressed or omitted.
- 6
Iterate Against the Result
Run the prompt, identify where the course remains theoretical or incomplete, and tighten the specification.
Pro tip Evaluate the generated deliverables, not just how impressive the prose sounds.
Watch out Treating the first prompt as final usually preserves avoidable fluff.
In the wild
A VP of marketing asks the model to combine the perspectives of an AI researcher, an executive educator, and a Fortune 500 CMO. The prompt defines a four-week course for experienced leaders, requires daily practical outputs, bans introductory lectures, and constrains each lesson to 45 minutes.
→ The VP receives a complete action-oriented curriculum tailored to leading an AI transformation.
A product-led growth leader reuses the architecture but changes the persona, audience, examples, and deliverables. Each lesson must improve an actual activation, retention, or expansion workflow and return a measurable experiment plan.
→ The same prompt structure creates a specialized course for a different operating context.
Common mistakes
Requesting a Course Without a Specification
A vague request leaves the model to choose the audience, depth, format, and balance between theory and action.
Using Persona as the Only Control
Expert mimicry can shape tone and perspective, but it does not replace explicit lesson requirements and guardrails.
Ignoring Output Limits
An unconstrained four-week curriculum may be truncated or summarized before all lessons are delivered.
Is it for you?
Best for
Time-constrained professionals who know what capability they want to develop and can evaluate the generated work.
Not ideal for
Beginners who cannot assess factual errors or safely execute technically advanced recommendations.
From the transcript
“And so the prompt is basically you are a hybrid of a Stanford GSP professor and MIT AI researcher at Fortune 500 CMO.”
“Typical prompts are you have the goal, you have the return format, which we talked about. Then you have these wardens, which is like, what…”
“Be concise yet complete, use shorter insights, tight in action steps, and apply bullet form and where health.”
From the episode
I Created a $200k MBA-Level Marketing Course with 1 AI Prompt