Knowledge-to-Action Prompt Pipeline
Turn collected expert knowledge into an AI workflow that improves real work
- Difficulty
- Easy
- Time to result
- ~days to results
- Steps
- 6
- Confidence
- 96%
The pipeline begins with knowledge acquisition: capture a credible expert source in a swipe file rather than merely bookmarking disconnected ideas. Next, extract the source's enduring principles and decide what practical task they should influence, such as evaluating copy or improving a launch. Translate those principles into an initial prompt with a defined input, process, and output. Work back and forth with an AI prompt-engineering assistant to expose omissions, refine instructions, and improve formatting. The final result should act like a small application: it accepts real work, applies the captured knowledge, and returns specific actions. This mechanism turns passive learning into a reusable operating tool while preserving the expertise that made the original source valuable.
Origin
The host developed this process after finding a collection of David Ogilvy's advertising lessons and deciding to turn that knowledge into an actionable copy-grading prompt. Extracted from Marketing Against The Grain.
Core principles
- 01Knowledge becomes more valuable when converted into action
- 02Expert material can supply the operating rules for an AI workflow
- 03Prompt quality improves through iterative dialogue with AI
- 04Useful prompts produce concrete outputs rather than passive summaries
How to run it
- 1
Capture Credible Knowledge
Add a substantive expert source to a swipe file. Prefer material containing durable principles, examples, or evaluation criteria rather than isolated opinions.
Pro tip Start with practitioners whose methods have remained useful across changing channels or technologies.
Watch out Weak source material will produce weak operating rules.
- 2
Extract the Principles
Identify the source's distinct principles and express each as a rule the AI can apply. Preserve enough specificity to distinguish one principle from another.
Pro tip Ask the AI to help organize the source into explicit criteria, then inspect the result yourself.
Watch out Do not reduce nuanced expertise to generic advice such as being clearer or working harder.
- 3
Choose the Action
Define the job the captured knowledge should perform, including the input the user supplies and the practical output they need.
Pro tip Frame the prompt as a point solution with one clear user outcome.
Watch out A prompt that only summarizes the source has not completed the knowledge-to-action conversion.
- 4
Draft the Workflow Prompt
Specify the AI's role, the supplied material, the principles it must apply, and the required output structure.
Pro tip Format the response sections explicitly so the output is easy to use.
Watch out Leaving inputs or outputs implicit invites inconsistent results.
- 5
Iterate With AI
Run the prompt on real work and go back and forth with an AI prompt engineer to improve instructions, scoring, and presentation.
Pro tip Treat surprising or awkward output as diagnostic evidence about the prompt.
Watch out Do not assume the first draft is the finished workflow.
- 6
Save and Reuse
Store the validated prompt in a prompt library and apply it whenever the same task recurs.
Pro tip Retain example inputs and outputs alongside the prompt to make future testing easier.
Watch out Recheck the prompt when the underlying task or source principles change.
In the wild
The host finds a detailed collection of David Ogilvy's advertising principles, converts fifteen of them into scoring criteria, and builds a prompt that evaluates a landing page. Instead of leaving the lessons in a swipe file, the prompt scores live copy, explains weaknesses, prioritizes improvements, and generates a rewrite.
→ A static collection of advertising knowledge becomes a reusable copy-improvement application.
Common mistakes
Stopping at collection
Saving expert material without defining an action leaves the knowledge dormant in the swipe file.
Accepting the first prompt
An initial outline often lacks the precision, formatting, or constraints needed for reliable repeated use.
Using knowledge without a task
Principles need a concrete input and desired output; otherwise the AI is likely to summarize rather than act.
Is it for you?
Best for
Marketers and knowledge workers who regularly collect expert articles, templates, examples, or playbooks.
Not ideal for
Situations where the source material is unreliable, purely inspirational, or too vague to support operational rules.
From the transcript
“AI turns all knowledge into action.”
“I'm acquiring knowledge, but then I go, Oh, cool. Well, I can turn that knowledge into action.”
“And the way I turn that into action is I work with my AI, I go back and forth, and then I craft a prompt.”
From the episode
I Built a Personal Marketing Coach With One Prompt