The Phenomenon of Bug Blindness

I have often wondered why my perception of software quality differs so drastically from that of the general population. While I routinely encounter hundreds or even thousands of bugs every week, most people I interact with seem to see nothing of the sort.

For a long time, I assumed this was a byproduct of my specific computing habits. However, I eventually realized the truth: most people are encountering the same bugs I am; they simply don't notice them.

While this "blindness" might be a more pleasant way for non-programmers to experience the world, I believe that curing this quality blindness is an essential skill for software developers.

Training the Eye

I have helped several friends and colleagues overcome this by simply pointing out the flaws in the software they use. For those with the right inclination, a few weeks of this guided observation is usually enough to start noticing bugs on their own.

Because of this trait, I've frequently been tapped by VPs, directors, and executives to provide an honest evaluation of a product. They want an opinion from someone who is likely to:

1. Spot the issues.
2. Fix them.
3. Or at least drive the necessary fixes.

The Spectrum of Severity

When evaluating a product, my findings generally fall into one of three categories:

The "Severe" category is the most perplexing. I often find products that require non-intuitive workarounds just to function, yet the internal documentation and team comments are a stream of praise, claiming the product is "great" and "works well."

"In many cases, a typical user wouldn't just struggle to use the product—they would have an experience so infuriatingly bad that they'd warn their friends to stay away."

Validating the Vision

For about a decade, I hesitated to write about this. I worried that I was just triggering weird corner cases I was an outlier who used software in a way that normal people don't. However, two things convinced me otherwise:

1. Product Launches: I've seen countless products launch and fail immediately because the general public hit the exact same walls I had predicted.
2. LLM Simulation: With the advent of Large Language Models, I can now simulate "normal" user personas to prove that these issues are reproducible across diverse scenarios.

def evaluate_product(user_persona):
    bugs_found = 0
    for feature in product.features:
        if user_persona.interact(feature) == "FAIL":
            bugs_found += 1
    return bugs_found

# Result: Even 'NormalUser' persona finds severe bugs.

Case Studies in Blindness

1. The Search Engine Paradox

I once published a study on search queries where Google, Bing, and Kagi all performed poorly, returning SEO spam and scam sites instead of quality results.

While most people accepted my critique of Google and Bing, many insisted I was wrong about Kagi. Even when presented with evidence—such as a user's specific filters and the resulting spam-filled pages—fans insisted the results were "good." The only exception was when users pinned GitHub to the top, which helped for software queries but did nothing for other types of searches.

2. The Volvo Effect

This blindness often stems from fandom. For instance, I drive a Volvo because of their performance in out-of-sample crash tests. However, while reliability data (and the consensus among mechanics) suggests Volvo reliability is mediocre to poor, the Volvo forums are filled with owners insisting their cars are the most reliable on the road.

3. The Blackboard Disaster

A prime example of widespread software hatred is Blackboard (the course management system). It was arguably the most detested software in my social circle, surpassed only by niche tools like Visual Source Safe.

The sentiment was backed by data:

• Wikipedia notes it became one of the most "detested" companies in education.
• A 2011 Fast Company report cited a survey where the "hate rate" was: $\text{Hate Rate} = 93\%$

In my younger, less filtered days, I once bluntly asked a Blackboard employee: "What is it like to work on software that so many people dislike?"

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Summary Checklist for Quality Assurance

• Identify the bug.
• Determine if it's a "corner case" or a general failure.
• Check if internal teams are suffering from "Bug Blindness."
• Validate using diverse user personas (or LLMs).