My Perfect
Resume
A CV builder SaaS with strong brand recognition and a significant content problem: an over-reliance on AI-generated articles that failed Google's quality filters, no process for humanising outputs, and a weak organic distribution strategy.
The brief, the context,
and the content problem
My Perfect Resume operates in a crowded SaaS market where organic search is the primary acquisition channel. The product is strong. The brand is established. The content, however, was scaling in the wrong direction.
The brief asked for three things: fix the existing content, build a prompt system, and create a distribut.
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AI-generated content without editorial oversight
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Thin content failing the Helpful Content standard
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No distribution strategy beyond publish and wait
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No prompt system . Quality was inconsistent and unrepeatable
Six moves across
content, prompts, and distribution
Editing out the AI-isms
Removing passive voice, transition scaffolding, and generic phrasing from existing articles
I started by simplifying the existing content. I removed repetitive introductions, unnecessary filler, and generic transitions that added length without adding value. I also rewrote passive sentences into active voice to improve clarity, readability, and engagement.
I removed vague statements, unnecessary hedging, and generic language, replacing them with specific insights, stronger reasoning, and more direct communication.
AI-pattern transitions replaced with direct logical connections. Each paragraph tightened to a single clear argument.
Injecting human insight and fact-checking
Adding original perspective, sourced data, and E-E-A-T signals to thin content
After strengthening the language, I enriched the content with research-backed insights and industry data. I incorporated relevant recruitment statistics and supporting evidence to reinforce key recommendations
I added practical insights that addressed common misconceptions, such as how ATS systems often reject resumes because of formatting issues rather than qualifications.
Upgraded article with sourced 2024–2026 recruitment data, expert-level perspective embedded in the body, and two external citations to high-authority sources. Content length increased from under 600 words to a structured 800-word article with FAQ section and quick-win list.
Building the master prompt system
A four-layer prompt chain that prevents low-quality drafts from entering the pipeline
I designed a master prompt chain that addresses this at source.
To ensure consistency, I built a structured AI workflow that defined the brand voice, audience, SEO objectives, and content structure before drafting began. I reviewed the outline before generating content and used section-by-section drafting to maintain quality and relevance.
Mster prompt chain with system role definition, SEO parameter injection, structure approval gate, and section-level drafting constraints. Includes voice rules, keyword placement requirements, AEO formatting guidance, E-E-A-T data prompts, internal and external link placeholders, FAQ structure, and CTA integration brief.
Layering AEO into the content structure
Structuring articles for citation by AI engines alongside traditional search rankings
I optimized the content for traditional search engines and AI-powered search experiences. I structured key sections around direct user questions and added FAQ content aligned with high-intent search queries.
Building the organic traffic strategy
Three precision moves to drive traffic and redirect authority with zero paid budget
I planned how each article would be pushed after launch: shared in relevant communities where people were actively looking for answers, linked from the site’s strongest pages to speed up discovery, and posted on LinkedIn in a simple carousel format to reach a wider audience.
I shared the content on r/resumes and r/jobs by contributing helpful replies to active threads, then included the article as a natural extension of the answer. For internal linking, I added two contextual links on high-traffic pages and set up CTR tracking in Google Analytics to measure performance.
Word-for-word social media copy
A LinkedIn carousel built on psychological precision, not generic promotion
The copy opens by reflecting the reader’s situation: experienced, skilled, and still not getting responses. It then explains the issue through three clear points. It ends with a simple action the reader can take in under 30 minutes
Opening hook
"Skilled. Strong experience. Solid career. Yet silence after every application."
The mechanism
"98% of Fortune 500 companies filter CVs with automated software. Multi-column layouts scramble your job titles. Text boxes hide your contact information. The wrong font turns your name into [NULL]."
The reframe + CTA
"You are not unqualified. You are unreadable. And you can fix this in less than 30 minutes."
