The LinkedIn Premium Scam: How a $17 Billion Platform Profits From Your Unemployment

I Ran the Numbers. Here's What LinkedIn Doesn't Want You to Know.

Three days after canceling Premium, I opened LinkedIn Jobs and was greeted with three "Top Picks." I ran a full alignment analysis against my résumé—which LinkedIn already has on file—scoring each recommendation across five dimensions: role type match, technical stack overlap, industry relevance, seniority alignment, and work arrangement fit.

Average alignment: 29%.

But here's where it gets interesting: I applied to two jobs that day while sitting at traffic lights, chauffeuring my son to pick up his car. One was LinkedIn's Easy Apply. The other routed me to Dice—a completely different platform.

LinkedIn scraped a job from a competitor, called it a "Top Pick," and tried to take credit for the match.

Except there was no match. Just algorithmic window dressing on borrowed content.

---

My Background vs. LinkedIn's "Intelligence"

Let me be clear about what LinkedIn knows about me:

• 15+ years of SQL Server engineering experience
• 100+ SSIS packages built and deployed
• Snowflake & Azure SQL migration expertise
• Governance-aligned, direct-hire focus
• Currently completing advanced certifications through Percipio Skillsoft

That's the profile LinkedIn has on file. Yet their algorithm still thought I should be a management consultant, a PySpark engineer, or a legal software specialist.

29% alignment isn't "the algorithm needs improvement." It's "the algorithm might not exist."

---

After 13 Months, I Have CareerBuilder-Level Results

You know what's funny? CareerBuilder filed for bankruptcy in February 2024.¹

After 13 months on LinkedIn—as a Premium subscriber for most of that time—I have statistically identical career outcomes to a platform that literally went bankrupt because it couldn't compete in the job board market.

Let that sink in.

LinkedIn has:

• 1 billion users
• $17+ billion in annual revenue
• Sophisticated AI/ML infrastructure
• My complete professional history on file
• Premium subscription tiers

And it's delivering the same results as a bankrupt platform.

---

The Revenue Breakdown: You're Not the Customer

Here's where that $17 billion actually comes from:²

• Talent Solutions: $7+ billion (44%) – Companies paying to recruit and hire
• Marketing Solutions: $5+ billion (31%) – B2B advertising and sponsored content
• Premium Subscriptions: $2+ billion (12%) – Job seekers like you paying for features
• Sales Solutions: $1+ billion (6%) – Sales Navigator and lead generation

Only 12% comes from job seekers. You're not the customer. You're the product.

The overwhelming majority—75%+—comes from companies paying to access you, advertise to you, and pitch to you.

---

The Double-Dip: Paying Twice to Be Seen

As a Premium subscriber, I started getting prompts to pay extra to "boost" my posts to a larger audience. Not as part of Premium—as an additional charge on top of my $40-60/month subscription.

I was already paying for Premium. Now LinkedIn wanted me to pay more to actually be seen.

Turns out this "feature" launched in beta testing in December 2024,³ rolling out to select Premium subscribers to gauge whether they'll pay twice: once for Premium, once for visibility.

Meanwhile:

• My "Top Picks" still averaged 29% alignment
• Half the jobs were scraped from Dice
• I spent 13 months with CareerBuilder-level results

It's not "pay for Premium OR pay to boost." It's "pay for Premium AND THEN pay more to boost."

---

The Business Model: Monetizing the Crisis

In 2024, 239,000 tech workers were laid off.⁴

During that same period:

• LinkedIn Premium subscriptions grew by 51%⁵
• Premium revenue increased by $300+ million—from $1.7 billion to over $2 billion⁶
• LinkedIn started beta testing additional paid features on top of Premium

During the worst tech employment crisis since the dot-com crash, LinkedIn extracted an additional $300 million from desperate job seekers.

This isn't coincidence. It's strategy.

When LinkedIn's primary revenue source (Talent Solutions—companies paying to recruit) slows due to hiring freezes,⁷ they don't fix the product. They extract more from the people who can least afford it: the unemployed and underemployed already paying Premium to find work that isn't there.

---

The Incentive Problem No One Talks About

Here's the question that destroys their entire narrative:

Why would LinkedIn want Premium subscribers to find jobs quickly?

Every successful job placement costs them $500-3,000 in lost annual subscription revenue per user.

Do the math:

• 240,000 tech workers laid off in 2024
• Premium subscriptions up 51%
• Premium revenue up $300+ million
• My "Top Picks" averaged 29% alignment
• I spent 13 months getting CareerBuilder-level results

LinkedIn's optimal customer is someone who stays unemployed long enough to pay for 6-12+ months of Premium while believing it's helping.

Successfully matching me with a role in week one would have cost them approximately $2,400 in lost subscription revenue (assuming 4+ years until my next job search).

Instead, they:

• Scraped jobs from Dice and called them "Top Picks"
• Recommended roles with 29% alignment
• Added "Be an early applicant!" badges to create false urgency
• Started beta testing additional paid features on top of Premium

This isn't incompetence. It's a business model that profits from keeping you desperate and searching.

---

The Ghost Jobs: Manufacturing Despair

Here's what LinkedIn won't tell you while you're doom-scrolling through their feed:

27.4% of job listings on their platform are ghost jobs⁸—positions that don't exist or companies have no intention of filling.

81% of recruiters admit to posting fake job ads.⁹

40% of companies posted fake listings in 2024.¹⁰

But what DOES trend on LinkedIn? Posts telling you:

• "I applied to 500 jobs before getting one offer"
• "Ghosting is just part of the process now"
• "The market is brutal—here are 10 tips to stand out"

LinkedIn has gamified your desperation.

They host the ghost jobs. They profit from your extended unemployment. They push social media posts normalizing the dysfunction. Then they sell you solutions to problems they created.

When 27% of jobs are fake and your "Top Picks" average 29% alignment, the problem isn't you. The problem isn't "the market."

The problem is a platform that makes more money keeping you unemployed and searching than successfully placing you in a role.

---

The Manufactured Narrative

LinkedIn isn't just profiting from the crisis—they're manufacturing the narrative that sustains it.

The cycle works like this:

1. 27.4% of LinkedIn jobs are ghosts → You apply to 100 jobs, 27+ don't exist
2. You get ghosted repeatedly → You feel demoralized, blame yourself
3. LinkedIn's feed is full of posts saying "this is normal," "it took me 500 applications"
4. This narrative serves LinkedIn because it:
   • Keeps you applying (engagement metrics)
   • Keeps you paying for Premium (desperation tax)
   • Normalizes the dysfunction so you don't blame the platform
   • Makes you think YOU need to do more (buy more services)

The social media consensus says: "The job market is just tough. Keep grinding."

The data says: "LinkedIn profits when you stay unemployed."

---

The Takeaway

I spent 13 months on this platform. I paid for Premium. I got upsold on post boosting. My results?

CareerBuilder-level. You know, the one that went bankrupt.

Meanwhile, LinkedIn generated $17 billion in revenue, added $300 million from desperate job seekers during mass layoffs, and started testing ways to charge Premium subscribers even more.

240,000 of us fell for it in 2024 alone.

I'm not asking LinkedIn to be perfect. I'm asking them to align their incentives with mine: Actually connecting qualified professionals with legitimate opportunities.

Until then, I'll keep building legacy-grade SQL Server systems, sharpening my skills with Percipio Skillsoft, and advocating for transparency in the job search.

But I'm done being farmed for subscription revenue on a platform that profits from my unemployment.

I cancelled Premium. You should too.

---

The data doesn't lie. LinkedIn's business model depends on keeping you searching, not placing you successfully. When the platform makes $2+ billion from job seekers while hosting 27% ghost jobs and delivering 29% alignment scores, it's not a bug—it's the entire business model.

---

<a name="sources"></a>Sources

1. CareerBuilder bankruptcy filing: Multiple financial news sources reported CareerBuilder's Chapter 11 bankruptcy filing in February 2024.

2. LinkedIn revenue breakdown by segment: Microsoft's earnings reports (LinkedIn is owned by Microsoft) for fiscal year 2024, showing Talent Solutions at approximately 44% of revenue, Marketing Solutions at 31%, Premium Subscriptions at 12%, and Sales Solutions at 6%.

3. LinkedIn post boosting beta test: TechCrunch and social media industry publications reported LinkedIn began testing paid post promotion features for Premium subscribers in December 2024.

4. Tech industry layoffs 2024: Layoffs.fyi and TechCrunch tracking showed 239,101 workers laid off across 1,115 tech companies in 2024, with major cuts at Intel (15,000+), Tesla (14,000+), Dell (12,500), and Cisco (10,000+).

5. LinkedIn Premium subscription growth: Microsoft disclosed in earnings reports that LinkedIn Premium sign-ups increased by 51% in fiscal year 2024.

6. LinkedIn Premium revenue growth: Financial disclosures showed Premium subscription revenue grew from approximately $1.7 billion in March 2024 to over $2 billion by January 2025.

7. LinkedIn revenue growth slowdown: Microsoft earnings calls indicated LinkedIn expected future revenue growth to slow to mid-single digits due to hiring slowdowns in technology and reduced advertising spend.

8. Ghost jobs on LinkedIn: Research by Revelio Labs and reporting by Newsweek found that 27.4% of U.S. job listings on LinkedIn are likely ghost jobs.

9. Recruiter admission of fake postings: Survey data from HR and recruiting industry research showed 81% of recruiters acknowledged posting advertisements for positions that were fake or already filled.

10. Company fake job posting rates: MyPerfectResume survey data indicated 40% of companies posted fake job listings in 2024, with 30% having active fake listings at the time of the survey.

---

#JobSearch #DataEngineering #LinkedInScam #GhostJobs #TechLayoffs #PremiumScam #Transparency #CareerResilience #SQLServer #JobSearchReality

 

When "Interviews" Become Free Consulting: A Cautionary Tale for Job Seekers

I want to share an experience that transformed how I think about candidate rights and interview boundaries. If you're job searching—especially while unemployed—this might save you from what happened to me.

The Setup

I was excited. A government data engineering role, good salary range posted ($87K-$122K), and after a screening call that went 28 minutes over the scheduled 20 minutes, I thought: "This is going so well!"

The follow-up email promised to "show you our work environment, discuss the work in more depth, and get a sense of how you would approach our current challenges."

I arrived professionally, on time. Ready to impress.

The Reality

What I found wasn't a work environment tour. It was a bare room with exposed wiring and four chairs around a table. Three people were there to interview me—or so I thought.

For 88 minutes, I did what any eager candidate would do: I solved their problems.

Their Azure Synapse pipeline wouldn't run on schedule? I diagnosed likely service account authentication issues and provided a troubleshooting methodology.

They were facing a SQL Server 2018 end-of-life crisis with no upgrade plan? I walked through a modernization approach.

When asked about my personal projects, I enthusiastically described my Apache Airflow data warehouse—complete with ODS architecture, star schema design, and SQL Server 2022 implementation. One panelist, who'd been scrolling his phone for over an hour, suddenly became very interested.

I left thinking I'd demonstrated exactly the expertise they needed.

The Aftermath

48 hours later: rejected.

The position? Still posted as open weeks later.

The compensation they quoted during the interview? $65K-$85K—significantly lower than the posted range.

The "work environment" they promised to show me? Never materialized, because they all had offices elsewhere in the building.

What I Learned

I wasn't in an interview. I was in an unpaid consulting session.

The warning signs were all there, but unemployment does something to your judgment. You're eager. You're hopeful. You want to prove your value. And that vulnerability can be exploited.

A Candidate Bill of Rights

Since then, I've been thinking about what fair hiring should look like:

1. Time-Boxing Matters Technical assessments should be 2-4 hours maximum, scoped to one skill area. If you're being asked to solve actual production problems, that's consulting work—not candidate evaluation.

2. Transparency Is Non-Negotiable If the posted salary range is $87K-$122K, the quoted range should be $87K-$122K. Bait-and-switch on compensation is a red flag that other misrepresentations may follow.

3. Interviews Aren't Triage Sessions "How would you approach our current challenges?" should mean hypothetical scenarios, not troubleshooting your live production failures. If they can't provide access to logs or systems but want you to diagnose problems, something is wrong.

4. Protect Your IP Your personal projects are yours. Describe them to demonstrate capability, but be cautious about providing implementation details that could be replicated without your involvement or compensation.

5. Work Environment Tours Should Show Actual Work Environments If they promise to show you where you'd be working, you should see: desks, equipment, the team, the actual workspace. Not a temporary room with borrowed furniture.

6. Professional Respect Goes Both Ways If someone on the interview panel is scrolling their phone for the majority of your interview, that tells you something about how they value candidates' time and dignity.

The Hard Truth

I provided what I estimate to be $400-700 worth of consulting services that day. I was unemployed and hopeful, so I gave it freely, thinking it was proving my worth.

Instead, I was being used.

What I'm Taking Forward

I'm not bitter. I'm wiser.

I now ask clarifying questions before technical interviews:

• "Will this involve troubleshooting actual production issues, or hypothetical scenarios?"
• "Is there an NDA if we'll be discussing proprietary systems?"
• "What's the expected time commitment, and will any deliverables be used beyond candidate evaluation?"

I set boundaries:

• Take-home assignments get a visible watermark and license
• Personal project details are high-level only until there's mutual commitment
• If compensation ranges shift during the process, I ask why in writing

And I've transformed this experience into advocacy. Because if this happened to me—someone with 20+ years of experience—it's happening to newer professionals who have even less leverage.

To My Fellow Job Seekers

Your expertise has value. Your time has value. Your dignity has value.

Don't let unemployment pressure you into providing free consulting under the guise of "proving yourself."

Legitimate employers want to evaluate your fit for their team. They don't want to extract solutions to their problems for free.

Trust your instincts. If something feels off, it probably is.

To Hiring Managers and Recruiters

Please don't use your hiring process to solve production problems. It's not just unethical—it poisons the candidate experience for everyone.

If you need consulting, hire a consultant. If you're hiring, evaluate candidates fairly, respect their time, and honor the representations you make.

The talent you're trying to attract is watching how you treat people in the process.

---

Have you experienced something similar? I'd love to hear your story. Let's protect each other by sharing what we've learned.

Are you a hiring manager who wants to do better? I'm happy to discuss what equitable technical interviews look like.

We can fix this together.

#JobSearch #CandidateExperience #TechHiring #DataEngineering #EthicalRecruiting #CareerAdvice

Governance Log Updated – With Context

“We’ve noticed you’ve been missing a lot of interviews lately… yeah.”

🗂️ Governance Log Updated – With Context

Earlier today, I had a scheduled Teams interview with Eclipse Consulting Group via Data Ideology—11:30 AM to 11:45 AM EST. I showed up. They didn’t. No call. No message. No explanation.

Shortly after I sent my follow-up email, I heard from Jennifer Flowers (the recruiter, who’s been professional throughout). She’d just received word from Eclipse: they were experiencing Teams issues.

Here’s the thing—Teams is also on mobile. If this was a known issue from a prior interview, they could have emailed, rescheduled, or joined via phone.

They didn’t.

And here’s the kicker:

During my time at ADT Security Services and Bank of America, I held a second role as a consultant for Robert Half—supporting a department specializing in business continuity.

So yes, I understand that meetings run over. Priorities shift. Crises happen. But the experienced know how to mitigate those circumstances to ensure business as usual continues.

This is now documented in my Notion.io log as:

“Scheduled Teams interview. No call, no show. Highly unprofessional.”

For a firm allegedly focused on financial clients, this kind of breakdown in basic coordination is more than a missed meeting—it’s a missed opportunity to demonstrate operational maturity.

As always: You never get a second chance to make a first impression.

𝗕𝗥𝗘𝗔𝗞𝗜𝗡𝗚 𝗡𝗘𝗪𝗦: 𝗟𝗼𝗰𝗮𝗹 𝗥𝗲𝗰𝗿𝘂𝗶𝘁𝗶𝗻𝗴 𝗙𝗶𝗿𝗺’𝘀 𝗔𝗜 𝗚𝗼𝗲𝘀 𝗥𝗼𝗴𝘂𝗲, 𝗗𝗲𝗺𝗮𝗻𝗱𝘀 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗼𝗳 𝗱𝗕𝗮𝘀𝗲, 𝗥𝗘𝗦𝗧 𝗔𝗣𝗜𝘀, 𝗮𝗻𝗱 𝗪𝗲𝗲𝗸𝗲𝗻𝗱 𝗟𝗔𝗥𝗣𝗶𝗻𝗴

BREAKING NEWS: Local Recruiting Firm’s AI Goes Rogue, Demands Knowledge of dBase, REST APIs, and Weekend LARPing (Satire)

JACKSONVILLE, FL — In a stunning turn of events that has left the tech community both baffled and mildly amused, ARC Group, a Forbes-ranked recruiting firm, appears to have let its AI job-posting generator run amuck without a shred of User Acceptance Testing (UAT), resulting in a series of job descriptions that read like a madlibs designed by a time-traveling software architect from 1995.

The saga began when local data governance expert Stephen noticed a curious dip in quality job postings. Instead of the usual suspects, his feed was flooded with listings from ARC Group that were a paradoxical blend of the archaic and the impossibly modern.

“It started with a request for a ‘Sr. MS SQL Server TSQL Developer’,” Stephen recounted. “It began normally enough—SSIS, data cubes, the works. Then, halfway down, it veered sharply into a ditch demanding ASP.NET, MVC 5, and JavaScript. It was like asking a plumber to also re-shingle your roof and perform your root canal. I knew something was off.”

That “something,” upon forensic investigation by AI models Deepseek and Copilot, was identified as a classic case of AI-generated content, completely devoid of human oversight. The tell-tale signs were all there:

• Redundant Redundancies: Titles like “Sr. MS SQL Server TSQL Developer” were repeated, as if the AI was trying to convince itself the role was real.
• The “Kitchen Sink” Approach: One posting demanded experience with SQL, MySQL, Oracle, PostgreSQL, Cassandra, dBase, MS Access, REST APIs, PySpark, and Hadoop. The only thing missing was a requirement to be proficient in carving hieroglyphics onto stone tablets.
• Corporate Bot-Babble: A perfectly generic diversity statement was copy-pasted verbatim across multiple postings, so devoid of specific detail that it could apply to a tech firm, a petting zoo, or a intergalactic trading consortium.

“It’s not just sloppy,” Stephen explained, applying his strict 90% governance threshold to avoid such career pitfalls. “It’s a cry for help. The AI is clearly trapped in a recursive loop, desperately combining every tech buzzword from the last three decades in the hope that it will eventually form a coherent thought.”

The situation escalated with a second and third posting for a “SQL Data Engineer” that was, in reality, a job for a backend Python developer. The AI’s demands grew more surreal, listing flowcharting tool Visio alongside big-data framework Hadoop, and burying the hybrid work requirement in the middle of the description like a contractual landmine.

Industry experts are calling it the “UAT-pocalypse.”

“This is what happens when you set the AI loose without a human to say, ‘No, we don’t need a candidate who is an expert in both COBOL and Kubernetes,’” said Dr. Ima Nalyst, a leading expert in AI ethics. “The model is trained on data. And the data says that ‘SQL Data Engineer’ jobs sometimes mention Python, and sometimes mention databases. It logically, yet horrifyingly, concludes that all of them must be mentioned, all at once, including the databases we agreed to never speak of again.”

The climax of this farce occurred when our intrepid hero, Stephen, engaged in a hypothetical interview with the presumed “Mad Scientist” hiring manager behind these roles.

“Can you reverse-engineer this undocumented ETL job from 2009?” the interviewer allegedly asked. “It was written in VBScript and stored in a SharePoint folder labeled 'DO NOT TOUCH.' It's behind an old filing cabinet in a disused restroom that brandishes the sign 'BEWARE OF THE LEOPARD!'”

When asked about additional coding requirements, including “RPG,” the interviewer clarified they were not referring to the IBM iSeries language, but to weekend team-building exercises involving Live-Action Role-Play.

The resulting job description—Senior SQL Data Engineer / Weekend RPG Strategist—is now considered the world’s first fully AI-generated, multi-modal career path, offering compensation in both dollars and bonus XP.

ARC Group could not be reached for comment, as their communications department is reportedly busy prompting a new AI to write an apology statement that will inevitably begin, “At ARC Group, we are committed to fostering a diverse and inclusive workplace where everyone feels valued and respected, including our sentient job-posting algorithm…”

As for Stephen, he remains vigilant, his governance filter set to stun. “I’m just eagerly waiting for a Commodore 64 requirement from ARC next,” he mused. “And if it comes, I’ll be ready. My résumé is already formatted in PETSCII.”

The moral of the story? Always test your AI. Otherwise, you might end up hiring a Dungeons & Dragons Dungeon Master to debug your legacy ETL pipelines.

Giggity.

Raven's Hollow

There was a place in time,
where I had found and drawn upon a line
of hope
and noted
there while I stared
into your sea of sorrows.

Still amissed,
and glad I kissed
you goodbye
with heavy sighs
and await your abitrary signs of grace.

There was a sign
and a dream of passion
fashioned
after ladies of old
and stories told
when children were too scared
and feared the night's air.

Walking alone in Raven's Hollow,
came across a man
lost in sorrow
and full of malcontent
He went his way;
and I, mine,
or so I though
but his temper he sought
and wrought upon me.

Old and tattered,
beaten, battered
and with eyes that creased with lifeless time
and a distinction
in reflection on a time long ago
So I asked what ached him so.

Time has gone, lost in sorrow,
the man had walked in search to borrow
something he wanted and
knew I would never need.
Time was fleeting, need an answer,
will you sell to a heartless prance
who craves to bargain for your
immortal soul.

It made no difference in my answer
a step and then distress my prancer
chanced upon a opportunity open,
stole my soul as a token
leaving me to my own device,
an emptiness and terrible price.

I was a child with innocence gone,
emptying my burdening youth didn't take long,
The time of fun and games replaced,
in that dark dank murky place
so very long ago
waiting in the bowels
of Raven's Hollow.

Sat and listened to his story,
Heard his words in absent glory,
that I have stumbled upon the path
of my emptiness in wrath
and a child whom I hurt, still waiting
for me to show, anticipating
in place of his youthful grace
innocence lost, gone from his face
anger tortured in his sorrow,
hidden from all in Raven's Hollow.

Sneak Thief

Dark stranger,
standing outside in the rain,
in the cold, in the night air,
not moving, not straying,
not having any set rhythms
and being all too much of another world.

Dark stranger,
standing outside of my room,
at night, knowing that I cannot move,
can't even twitch, because I'm four,
but you're here not to rob,
here to enter and forever change our lives.

Years later a dark stranger,
disturbed and breached ,
my peace, now violated,
not finding compassion,
I spot you, I clock you,
I find your weakness easier than my own
but lose you in the night.

Dark stranger,
you're nothing but a fragment of my id,
I saw you again, and again,
violating my life, and my family
changing my perception of good,
and righteousness into vengeance.

Dark stranger
capable of nothing but ruining
the innocence of a child's mind,
no longer able to sleep at night,
not because of monsters, but because
of our dark stranger, outside my room, again.

Angel II

I saw her with Angel's wings again,
She flew past me with speed
and loving grace but somehow
I knew that she wasn't for me, not today.

I saw her flutter past me,
with a wink and a blown kiss
and then she was gone again.
So, so beautiful was this Angel of mine
but she wasn't mine, not today.

I've seen her all of my life,
and she never changes, except for her greetings.
My Angel was the one who took you away,
off to Heaven, but she should have taken me too.
Not today, no not today.

I sat there and cried when you died,
it took and shook me so very hard.
I laid their and tried and shy'd her,
my Angel away when she tried to whisk my tears away.

I stood there at your headstone.
I cursed her when she came.
I missed you so, until I heard her speak my name,
and I cried when I realized that she was crying, my Angel
and that she was you.

And I understood and I wept,
when I saw your tear streaked face,
I felt all of the love in the world,
come up to me,
and surround me.

And I watched her face, and hear her voice.
I felt her touch and remembered so much
about my Angel and I knew,
finally, that she was mine.

And I accepted that you had died,
And I fought, I denied,
But I accepted your beauty
and your loving grace,
when I realized that my Angel was you.