More Than a Machine: How I Use AI for Strategic Content Outlining
Role:
Content Strategist, AI Prompter
Skills:
Strategic Prompt Engineering
AI Ethics & Evaluation
Content Editing
Tools:
ChatGPT-4
Microsoft Word
My AI Credentials: I have completed a certification in “Start Writing Prompts Like a Pro” from Google and am currently completing the next level of certification. In my current position, I have used AI to brainstorm new blog post ideas, create content outlines, and ethically draft content for projects.
The problem / context
The team needed to develop a new, authoritative blog post on "The Importance of Eliminating Technical Debt." The target audience was tech professionals and CTOs who are aware of technical debt but struggle with prioritizing its removal.
The challenge was to create a comprehensive, well-structured article that went beyond generic definitions. I needed to do this efficiently to save time for the most valuable parts of the process: in-depth research and adding a unique, human-led perspective.
The process: from strategic prompt to final post
My process for using AI is not about generating a final draft. It's about using a strategic "creative brief" (the prompt) to generate a high-quality scaffold, which I then build upon with my own expertise.
1. The strategy: designing the prompt
A successful AI output starts with a prompt that functions as a creative brief. My prompt (below) was intentionally specific to constrain the AI and guide it toward a useful, structured result.
I didn't just ask for "an article on tech debt." I strategically defined:
The Topic & Title: "The Importance of Eliminating Technical Debt"
The Target Audience & Pain Point: "tech professionals who have technical debt but don't know how to prioritize getting rid of it."
Specific Structural Requirements: "Ensure the article has sections explaining what technical debt is, what causes it, five reasons to eliminate tech debt, and a list of AI solutions for getting rid of tech debt."
A "Hook" Requirement: "Start with an introduction that includes a fun fact or statistic with a cited source."
2. The prompt
This is the exact prompt I provided to ChatGPT-4:
3. The output & evaluation
The AI returned a strong foundational outline that correctly followed my structural requirements. It provided a solid, logical flow and identified the key concepts I requested.
However, the AI-generated outline was only a B+ starting point. It lacked the expert nuance and specific data our audience requires. My next step was to move this outline into a document for human-led refinement and writing.
4. The "human-in-the-loop" refinement
I did the following to ensure the output was factual and human-first:
Fact-checking and validation: I immediately fact-checked the statistic the AI provided to ensure its accuracy and source.
Adding expert nuance: The AI's "Causes" and "Reasons" were generic. I rewrote these sections to tie directly to specific business-level outcomes (like ROI, innovation speed, and team morale), which I know resonates with our target audience.
Adding authority: The AI cannot provide original thought leadership. I used the time I saved on outlining to find more authoritative sources to quote, such as the G20's VP of Technology (as seen in the final article).
Writing and polishing: I wrote the full article, infusing our brand's voice and tone, ensuring the narrative flowed smoothly from one section to the next.
The Result & Outcome
The final published article (below) is a product of human-AI collaboration—not just AI generation.
By using a well-thought-out prompt, I created a scalable and repeatable workflow:
Efficiency: This AI-assisted process saved approximately 2-3 hours of foundational outlining and research time.
Higher-quality output: That saved time was reinvested directly into higher-value tasks: finding unique data points, adding expert quotes, and refining the article's core arguments. This made the final piece far more authoritative and useful for our specific audience than a 100% human- or 100% AI-generated article could ever be.