What does your LinkedIn really say about you? Here’s a method to test it, powered by AI and brutal honesty. What does your LinkedIn really say about you? Here’s a method to test it, powered by AI and brutal honesty. “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. visionary impact-driven cross-functional problem-solver 15+ years 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? signal 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. simple but powerful AI prompt any 🚀 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 🧱 What someone claims to be What someone claims to be claims 🔍 What they’ve actually done (and whether it’s visible) What they’ve actually done actually done ⚙️ How well their public digital footprint supports those claims 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: data scientists design leads PMs tech founders see through the fluff 🛠️ 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.

1️⃣ 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.

2️⃣ 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.)						

3️⃣ 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.

4️⃣ 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.

5️⃣ 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.

6️⃣ 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.

7️⃣ 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:
1️⃣ Key Activities & Experience
2️⃣ Major Articles & Publications (with Quality & AI-Check)
3️⃣ Influence & Community Presence
4️⃣ Expertise Assessment & Value
5️⃣ Collaborations, Events & Certifications
6️⃣ Web & Media Footprint
7️⃣ Academic & Teaching Activities

If any section yields no results, explicitly write:

“No public data found as of [date of check].” [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.

1️⃣ 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.

2️⃣ 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.)						

3️⃣ 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.

4️⃣ 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.

5️⃣ 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.

6️⃣ 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.

7️⃣ 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:
1️⃣ Key Activities & Experience
2️⃣ Major Articles & Publications (with Quality & AI-Check)
3️⃣ Influence & Community Presence
4️⃣ Expertise Assessment & Value
5️⃣ Collaborations, Events & Certifications
6️⃣ Web & Media Footprint
7️⃣ 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 A fact-based, no-BS profile analysis fact-based Detected red flags, gaps, and unverifiable claims A real sense of what the person’s actually doing, not just saying what the person’s actually doing actually 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 🧩 Design Leads – evaluating candidates based on real case studies and traceable outcomes Design Leads 📦 Product Managers – assessing consultants, mentors, and subject-matter experts beyond buzzwords Product Managers 📊 Data Scientists – verifying collaborators and public figures in AI, research, and analytics Data Scientists 🧑💼 Hiring Teams – filtering inflated profiles and focusing on demonstrable expertise Hiring Teams 🪞 Content Creators & Professionals – auditing their own digital footprint to improve credibility Content Creators & Professionals 🤖 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 Articles with real cases vs. SEO word soup real cases Projects with timelines, roles, and outcomes, not just jargon timelines, roles, and outcomes Posts that show authorship, not just “here’s my new blog post” authorship Certifications that can’t be verified Certifications 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. visible verifiable valuable 🔄 One Last Thought If you found this useful: Steal it.
Share it.
Remix it.
Use it on me. 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 https://www.linkedin.com/in/vitaliioborskyi Let’s make profiles worth reading again.

Here's My Exact AI Prompt to Audit Any Professional Profile on the Internet — Including Your Own

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