This content originally appeared on DEV Community and was authored by Vitalii Oborskyi
“Why does every profile sound the same?”
If you’ve spent more than 5 minutes on LinkedIn, you’ve probably noticed something strange: Everyone is a visionary, impact-driven, cross-functional problem-solver with 15+ years of experience.
And somehow… no one says anything real.
In a world flooded with GPT-polished personal brands, how do we separate the signal from the noise?
That’s the question that inspired this: A simple but powerful AI prompt to critically audit any professional profile - yours, your peer’s, your client’s, or your hero’s.
Why This Prompt Matters
This isn’t about catching lies. It’s about closing the gap between:
What someone claims to be
What they’ve actually done (and whether it’s visible)
How well their public digital footprint supports those claims
For data scientists, design leads, PMs, and tech founders, the stakes are high. We hire people, fund projects, and build reputations based on online signals. So we need better tools to see through the fluff - without hiring an investigator:
The Prompt (Copy‑Paste Ready)
Paste this into your favorite LLM (tested with ChatGPT 4o/4.1). Replace the name/link with any target:
[FULL NAME] [linkedin-profile] - Structured Expert Profile with Critical Article Analysis 🚦
Instructions (ENGLISH):
Provide a concise, critically-structured professional profile of the subject as an expert, using ONLY up-to-date information from publicly available web sources (do not use your internal memory or prior knowledge).
For every section, display ALL available, relevant information without omission or summary.
⚡ Use tables, lists, and emoji for structure and emphasis.
MANDATORY REQUIREMENTS:
Do NOT omit, crop, or summarize ANY publication, fact, link, or thematic section found in public sources.
EVERY publication/article/post/quote found online MUST be individually analyzed and included-no "see above", "other similar", or "not reviewed for brevity".
All facts must be confirmed with accessible links.
For each section, if data is absent, explicitly state "No public data found" (with date of check).
Validate all dates, links, and organizational details.
Critically analyze content-do not copy, do not repeat, do not generalize.
Structure your output using the headings below.
1⃣ Key Activities & Experience
List all main areas of expertise (e.g., PMO, delivery, IT consulting, AI, risk, etc.).
State real job titles, companies, years (if known).
List all standout achievements, unique facts, and current roles.
Confirm ALL with links.
2⃣ Major Articles & Publications (with Quality & AI-Check)
📝 Title/Topic 💡 Key Idea 🌍 Platform 📅 Date (verified) 🌟 Impact/Discussion 🧠 Originality/Validity 🤖 AI/LLM Content Check
(Analyze EVERY found article/post/publication. For each: one phrase summary, impact, originality, validity, and specific AI-generated content check: ✅ Genuine, ⚠ Slightly formulaic, ❗ Possible AI. Confirm with link.)
3⃣ Influence & Community Presence
List all professional and social platforms where the expert is active (LinkedIn, Medium, forums, Slack groups, etc.).
List any notable engagement, viral posts, peer comments/quotes (with source).
Mention roles in professional communities, boards, or online groups.
4⃣ Expertise Assessment & Value
3–5 bullets: reputation, originality, strengths/weaknesses, audience, practical value.
Explicitly mention any "red flags" on originality, credibility, or suspected AI content.
Fact-based, no generalizations.
5⃣ Collaborations, Events & Certifications
List ALL professional collaborations (projects, joint publications, open source, partnerships).
List ALL conference presentations, panels, podcasts, workshops, juries (date, topic, platform, link).
List ALL professional certificates and courses (with date, organizer, validation link if possible).
Explicitly note any absence of public evidence.
6⃣ Web & Media Footprint
List EVERY instance where the expert is mentioned outside their own channels:
Third-party articles, reviews, interviews, analytics, "top experts" lists, company/industry sites, media, podcasts, YouTube, SlideShare, ResearchGate, etc.
For each, include link, date, context, and a brief summary.
Check for independent citations and discussions of their work.
Note: If none found, explicitly state this.
7⃣ Academic & Teaching Activities (optional)
List any teaching, mentoring, course design, scientific or academic publications, lectures, or participation in educational projects (dates, topics, links).
If nothing found, state so.
Technical Reminders:
DO NOT summarize or omit ANY discovered item, however minor.
ALWAYS provide validated links and dates.
If a claimed certificate/publication cannot be independently verified, mark as ⚠ "Unverified".
Structure all lists and tables for fast reading; add emojis for clarity.
OUTPUT HEADINGS:
1⃣ Key Activities & Experience
2⃣ Major Articles & Publications (with Quality & AI-Check)
3⃣ Influence & Community Presence
4⃣ Expertise Assessment & Value
5⃣ Collaborations, Events & Certifications
6⃣ Web & Media Footprint
7⃣ Academic & Teaching Activities
If any section yields no results, explicitly write:
"No public data found as of [date of check]."
What You Get (If Used Well)
A fact-based, no-BS profile analysis
Detected red flags, gaps, and unverifiable claims
A real sense of what the person’s actually doing, not just saying
Signal on originality - whether posts look human or AI‑templated
Surface-level brand vs. deep, verifiable contribution
Who This Is Useful For
Design Leads - evaluating candidates based on real case studies and traceable outcomes
Product Managers - assessing consultants, mentors, and subject-matter experts beyond buzzwords
Data Scientists - verifying collaborators and public figures in AI, research, and analytics
Hiring Teams - filtering inflated profiles and focusing on demonstrable expertise
Content Creators & Professionals - auditing their own digital footprint to improve credibility
What AI Still Can’t Fake (But Tries)
When you run this prompt on someone (or yourself), look out for:
Articles with real cases vs. SEO word soup
Projects with timelines, roles, and outcomes, not just jargon
Posts that show authorship, not just “here’s my new blog post”
Certifications that can’t be verified
Media mentions outside self-posted networks
If the AI comes back empty or vague - that’s the story, too.
Try It on Yourself
Here’s the brave part: Paste your own profile link into the prompt and read the result.
If it feels… flat - good. That’s data. Now improve what matters, not just your headline.
Why This Should Be Standard Practice
We’ve normalized a world where people claim “AI Strategy”, “Leadership Transformation”, or “Researcher” in one paragraph, then share Canva carousels in the next.
This prompt is an invitation to make things real again.
To bring back credibility - not by gatekeeping, but by showing what’s visible, verifiable, and valuable.
One Last Thought
If you found this useful:
Steal it.
Share it.
Remix it.
Use it on me.
Here’s my profile if you want to test it live: 
https://www.linkedin.com/in/vitaliioborskyi
Let’s make profiles worth reading again.
Written by Vitalii Oborskyi - PMO & Delivery Head
This content originally appeared on DEV Community and was authored by Vitalii Oborskyi