You know that moment when you implement a shiny new technology and immediately regret it? Welcome to the story of TechVenture Solutions, a mid-size software company that deployed an AI-powered resume screening system in November 2025.

To test the system, their CEO suggested that the entire executive team apply to open positions on the careers page—you know, to make sure the AI was working properly.

Spoiler alert: it was working. Just not how they wanted.

The Executive Team Applies

The setup was simple: TechVenture had just implemented an AI screening platform that automatically evaluates resumes, scores candidates, and either advances them to human review or sends automated rejection emails.

To validate the system, the CEO, CFO, CTO, VP of Sales, and VP of Marketing each created fake email addresses and applied to open positions on the company website that matched their expertise.

The CEO applied for a "Director of Product" role. The CFO applied for a "Senior Financial Analyst" position. The CTO applied for a "Lead Software Engineer" role. And so on.

They used their real resumes—with decades of experience, impressive credentials, and a track record of running successful companies.

Then they waited to see what would happen.

The Rejection Emails Start Rolling In

Within 24 hours, every single executive received the same automated response:

"Thank you for your interest in TechVenture Solutions. After careful review, we have decided to move forward with other candidates whose qualifications more closely match our needs. We appreciate your interest and wish you success in your job search."

Every. Single. One.

The AI had rejected the CEO for being overqualified. The CFO for having "too much job-hopping" (he'd been with the company for 8 years but had held different roles). The CTO for lacking specific programming language keywords in his resume (because executives don't write code anymore). The VP of Sales for not meeting the "3-5 years experience" requirement (he had 20 years, which apparently was too many).

According to sources who shared the story on Reddit, the CEO's exact words in the emergency meeting were: "So we've been auto-rejecting everyone remotely qualified for six weeks?"

The answer, unfortunately, was yes.

What the AI Got Wrong (Basically Everything)

Let's break down the AI screening fails:

Overqualification Filters Run Amok:

The AI was programmed to flag "overqualified" candidates to reduce flight risk. But the algorithm was overly aggressive—anyone with more than 10 years of experience for a role asking for 5-7 years got auto-rejected.

This eliminated the CEO, CFO, and both VPs immediately. The system assumed they'd leave for better opportunities, not considering that some experienced candidates actually want less responsibility or are genuinely interested in the company.

Keyword Obsession:

The CTO's resume didn't include "Python" or "JavaScript" because he hadn't written production code in 15 years—he managed engineering teams. But the AI screening tool was looking for exact keyword matches, not understanding that a Chief Technology Officer obviously knows technology even if he doesn't list every programming language.

"Job-Hopping" False Positives:

The CFO had held four different titles at TechVenture over 8 years as he was promoted. The AI saw four roles in 8 years and flagged it as job-hopping, not recognizing internal promotions.

Experience Range Rigidity:

The VP of Sales applied for a role requiring "3-5 years of sales experience." He had 20 years. The AI interpreted this as "outside the acceptable range" and rejected him, treating "too much experience" the same as "not enough experience."

Resume Format Penalties:

The VP of Marketing had a beautifully designed resume with custom formatting. The AI's resume parser choked on it, failed to extract key information, and scored her as "insufficient qualifications". Turns out, the AI preferred bland, text-heavy resumes over creative ones.

The Damage Assessment

Once the executive team realized what had happened, they ran an audit.

Results:

• 1,247 applications processed by the AI over 6 weeks
• 892 automatically rejected (71.5%)
• Only 355 candidates advanced to human review

When HR manually reviewed a sample of the rejected candidates, they found:

• 43% were actually well-qualified but got rejected for reasons like "overqualified," "non-standard resume format," or "missing specific keywords"
• 28% were borderline (could have gone either way)
• 29% were legitimately unqualified

Translation: the AI was rejecting nearly half of the qualified candidates based on overly rigid criteria that had nothing to do with actual job performance.

The Internal Fallout

The executive team's failed experiment became company legend immediately.

According to anonymous posts on Blind, internal Slack channels erupted with memes:

@EngineeringManager: "Turns out our CEO isn't qualified to work here. Maybe we should start a company-wide job search."

@HRCoordinator: "The AI rejected our entire leadership team. This is either a catastrophic failure or the AI knows something we don't."

@SoftwareEngineer: "Plot twist: the AI is trying to save us from bad management. It's sentient and helpful."

@ProductDesigner: "I applied to a role last month and got rejected. Now I know I'm in good company. Literally—the CEO got rejected too."

The VP of Marketing reportedly created a PowerPoint titled "How Our AI Thinks We're All Unemployable" and presented it at the next all-hands meeting. It got a standing ovation.

The Fix (Sort Of)

TechVenture immediately disabled the auto-rejection feature and switched the AI to "recommendation mode" where it scores candidates but doesn't make final decisions.

They also:

• Removed the overqualification filter entirely (turns out, experienced people sometimes want less stressful roles)
• Fixed the job-hopping algorithm to recognize internal promotions
• Adjusted keyword weighting to value experience and leadership over exact technical skill matches
• Added manual review for all candidates scoring below 70% instead of auto-rejecting them
• Tested the system with dozens of employee resumes before re-enabling automation

The company also sent apology emails to the 389 rejected candidates they deemed actually qualified, inviting them to reapply. Approximately 12 people responded. The rest had already accepted offers elsewhere or were too annoyed to bother.

The Lesson Everyone Learned (Hopefully)

This story is hilarious, but it's also a cautionary tale about implementing AI screening without proper validation and human oversight.

What TechVenture Did Wrong:

1. Deployed AI screening without testing it first (or at least testing it properly)
2. Gave the AI full auto-reject authority with no human review
3. Set overly rigid criteria (exact experience ranges, keyword requirements, overqualification filters)
4. Didn't monitor outcomes until executives literally applied and got rejected
5. Assumed AI would be "better than humans" without validating that assumption

What They Should Have Done:

1. Pilot the system in recommendation mode first, using AI to score candidates while humans made final decisions
2. Test with known-good resumes (like their own executives, high-performing employees, etc.) before going live
3. Monitor rejection rates and audit samples regularly to catch problems early
4. Use AI to screen for minimum qualifications, not to make nuanced judgment calls about overqualification or culture fit
5. Keep humans in the loop for final decisions, especially for competitive roles

The Memes

This story went semi-viral in recruiting circles, spawning excellent memes:

Twitter/X:

@RecruiterHumor: "CEO: 'Our AI will revolutionize hiring!' AI: rejects CEO CEO: 'Not like that.'"

@TechRecruiter: "If your executives can't pass their own company's AI screening, maybe the problem isn't the executives."

@JobSearchMemes: "Me: gets rejected by AI Also me: finds out the company's entire executive team also got rejected I feel better now."

Reddit:

r/recruitinghell: "This is the most perfect metaphor for AI recruiting. The technology works exactly as programmed, which is why it's a disaster."

r/cscareerquestions: "TechVenture's AI rejected their CTO for not having enough Python keywords. This is why I stuff my resume with buzzwords even if they're irrelevant."

The Aftermath

As of this writing:

• TechVenture is still using the AI screening tool, but in recommendation mode only
• The CEO now personally reviews all rejected candidates scoring above 50%
• The company has filled 4 of the 8 open positions that were pending during the AI disaster
• Rejected candidates have been memeing about it on LinkedIn and Twitter, giving TechVenture some unintended viral marketing (of the "wow, that's embarrassing" variety)

The funniest part? One of the auto-rejected candidates tweeted: "I got rejected by an AI that also rejected the company's CEO. Not sure if I should be insulted or flattered."

Valid question.

The Takeaway

AI screening tools can be useful, but they're only as good as the criteria you give them and the oversight you maintain.

If you implement AI without testing, monitoring, and human oversight, you'll end up like TechVenture—rejecting your own leadership team while wondering why you can't find qualified candidates.

Test your AI. Monitor your outcomes. Keep humans in the loop. And for the love of all that is holy, don't give an algorithm full authority to reject candidates without review.

Or do. The stories are entertaining, at least.