A two-hour rejection for a near-perfect role wasn’t a personal failure — it was a system diagnostic. It revealed an “Illusion of Quality” in hiring: where we optimize for measurable proxies instead of the immeasurable whole.
🕰️ The 120-Minute Diagnostic
The response arrived in the space between one meeting and the next —
a polite, automated “no”.
Two hours.
Just enough time for a system to run its diagnostics, but not enough for a human to feel curiosity.
At 10:07, I submitted an application representing a deliberate evolution of my career — a synthesis of years in testing, quality, and leadership.
At 12:07, the decision had already been made.
It wasn’t a person rejecting me.
It was a system event — a diagnostic log from a quality gate that had been programmed to measure the wrong thing.
For a moment, I felt the usual disappointment. Then the engineer in me took over.
🧩 What exactly had this gate tested?
When the system sees only syntax, the human disappears. (Gemini generated image)
🔍 The Autopsy: The Unit Test for a Career
An Applicant Tracking System (ATS) is a unit test for a human career. ⚙️
It checks for the presence of specific, isolated functions — “C++”, “Python”, “ASPICE”, “leadership”.
If the keywords are found, the test passes.
If not, it fails.
But a unit test is blind to architecture.
It cannot assess how components interact to form a coherent system.
🧠The same logic applies here:
The ATS can parse “MISRA,” but it can’t comprehend the significance of a system that neutralized 300,000 MISRA violations.
It detects the token, not the transformation.
Like a static code analyzer, it scans for patterns — yet remains oblivious to intent, elegance, or integration.
It validates syntax, but overlooks semantics.
In short: the algorithm measures the proxy, not the purpose.
Automation excels at reading code, not meaning. (Gemini generated image)
🌉 The Paradox: Conformity vs. Synthesis
This isn’t just my story.
It’s a pattern many of us recognize — especially those whose value lies in synthesis rather than specialization.
We are taught to build bridges between disciplines, between teams, between strategy and delivery.
Yet the system rewards a collection of well-labeled islands. 🏝️
The paradox is cruelly simple:
The very quality that makes us effective — the ability to weave a tapestry from scattered threads — becomes a liability in a system that only recognizes individual, labeled strands.
Our work is often the glue that holds complex structures together.
But to a parsing algorithm, we appear undefined, abstract — perhaps even irrelevant.
The deeper irony?
The system filters out exactly the kind of mind that could fix it.
Synthesis is the art of what machines still cannot see. (Gemini generated image)
🧪 The Reframe: A Flawed Quality Gate
Once I saw it that way, the rejection looked different.
This wasn’t a judgment of merit.
It was a false negative — a signal from a quality gate that failed its own purpose.
In testing, we know that a component can pass isolated checks yet fail integration.
Likewise, a CV can fail automated filters yet represent exactly the profile an organization needs.
The system measured the map, not the territory. 🗺️
In quality engineering, such behavior is not a rejection —
it’s a bug report.
The flaw is not in the product; it’s in the metric.
Every rejection is feedback — not about you, but about the metric. (Gemini generated image)
đź’ˇ Beyond the Illusion: Augmenting Judgment
The goal isn’t to rage against automation.
Automation, when designed with wisdom, amplifies judgment.
But judgment must still exist.
The most intelligent systems — in cars, in software, in hiring — are those that augment human discernment, not replace it.
That two-hour rejection was a reminder:
đź’ The deepest illusion is not that machines are judging us,
but that we have come to accept their limited proxies as our definition of merit.
The best systems don’t replace judgment — they extend it. (Gemini generated image)
🌿 Reflection: Hearing the Melody Within the Data
Every rejection is data — not about you, but about the system that rendered it.
Sometimes, being filtered out means you’ve discovered the limits of a gate not yet designed for synthesis.
The question, then, is not how to build a better filter.
It’s how to become better listeners.
🎵 How do we design systems — and cultures — that can hear the melody within the data, the soul within the syntax?
When systems forget to listen, even the data longs to sing. (Gemini generated image)
đź”– If you found this perspective helpful, follow me for more insights on software quality, testing strategies, and ASPICE in practice.
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