The Competency Gap: When Interviewers Can't Recognize What They Don't Know

The interview process followed a typical three-stage format. The first stage was straightforward, a coding challenge to build a wallet system. I completed it without much trouble, implementing what I considered a solid architectural approach with separate tables for transactions, accounts, and the ledger itself. Each component served a specific purpose: transactions recorded individual movements of funds, accounts maintained current balances and metadata, and the ledger provided an immutable audit trail. It was textbook financial system design, the kind of architecture you'd find in any production-grade banking application.

The second stage was where things went sideways. I found myself in a conference room, explaining my ledger system design to three engineers. But as I walked through my solution, I was met with a wall of resistance. "This is overly complex," one interviewer declared. "A single wallet table would be far more efficient. That's what we'd use in production."

I tried to explain the benefits of my approach—data integrity, auditability, scalability, separation of concerns. Each point fell on deaf ears. The more I elaborated on why transaction history needed to be immutable, why account balances should be calculated rather than stored, why referential integrity mattered in financial systems, the more dismissive they became.

What struck me wasn't just the technical disagreement—every engineer has different perspectives on architecture. It was the complete unwillingness to engage with my reasoning. They had decided their approach was correct, and no amount of explanation would change that conviction.

The third stage continued in much the same vein, different people, same closed-minded approach to technical discussion. By this point, I was beginning to understand the company's engineering culture, and it wasn't encouraging.

What made this particularly frustrating was that I had done my homework beforehand. As any thorough candidate should, I had researched the team before walking into that room. What I discovered should have prepared me for what was coming: several of the engineers interviewing me had significantly less experience than I did, not just in years but in the specific domain of financial systems. Yet they approached the interview with the confidence of seasoned architects dismissing a junior developer's naive attempt.

The contrast with the head of engineering was telling. It highlighted that this wasn't a company-wide culture problem, it was a team-level competency gap issue. The senior leadership understood good engineering practices, but that understanding hadn't filtered down to the people actually conducting technical interviews.

This experience crystallized something I had been noticing throughout my career: the competency gap problem in technical interviews.

The Authority Illusion

The most insidious aspect of the competency gap isn't incompetence. It's the illusion of authority that comes with being the interviewer. When you're sitting on the "decision-making" side of the table, it's easy to confuse your position with expertise.

This psychological dynamic plays out in countless interview rooms across the tech industry. An engineer with three years of experience evaluating someone with fifteen. A developer who's only worked on simple CRUD applications dismissing sophisticated system design patterns. A team that's never dealt with the complexities of financial regulations confidently declaring that audit trails are "unnecessary overhead."

The role of interviewer carries implicit authority, and that authority can mask significant knowledge gaps. When combined with the natural human tendency to overestimate our own competence (the Dunning-Kruger effect), it creates a perfect storm of poor technical judgment.

The Echo Chamber Effect

What made my fintech interview particularly frustrating wasn't just the technical disagreement. It was the complete absence of curiosity. Good technical discussions involve exploring trade-offs, understanding different perspectives, and learning from each other's experiences. Instead, I encountered what I call the "echo chamber effect."

The interview had become a validation exercise. The team had a predetermined notion of the "right" answer, and they were looking for candidates who would confirm their existing beliefs rather than challenge or enhance their thinking. When I presented an approach that differed from their expectations, the response wasn't "interesting, tell us more about why you chose this approach" but rather "this is wrong, and here's why our way is better."

This dynamic is toxic for several reasons:

First, it eliminates learning opportunities. Some of the best technical discussions I've had have come from disagreements where both parties were genuinely curious about each other's reasoning. When interviewers approach sessions with closed minds, they miss chances to discover new approaches, tools, or patterns.

Second, it creates a false sense of technical consensus. If every candidate you hire agrees with your existing approaches, you're not building a diverse team of thinkers—you're building a team of yes-people who will perpetuate the same design decisions, good or bad.

Third, it reveals concerning cultural patterns. If a team can't engage constructively with different technical perspectives during an interview, how do they handle disagreements during actual engineering work? How do they approach code reviews? How do they evaluate new technologies or architectural changes?

The Research Imperative

My experience taught me the importance of reverse due diligence. Just as companies research candidates, engineers should research their potential colleagues and managers. This isn't about judging people's worth. It's about understanding whether you'll be joining a team that values learning and growth or one that's trapped in its own echo chamber.

Modern tools make this research easier than ever. LinkedIn profiles, GitHub contributions, conference talks, blog posts, and industry publications can all provide insights into a team's technical depth and approach to engineering. When I researched that fintech team, the pattern became clear: they were confident in their abilities but hadn't yet encountered the complexity that would challenge their assumptions.

This research also helps calibrate expectations. If you're joining a team where you have significantly more experience in a particular domain, you need to understand whether they'll view that expertise as an asset or a threat. Some teams genuinely want to learn from new hires with deeper knowledge. Others prefer to maintain their existing technical hierarchies.

The Cost of Closed Minds

Organizations that fail to recognize and address the competency gap pay a significant price. When technically superior candidates are rejected because their approaches don't align with the team's existing (and potentially limited) knowledge, companies miss opportunities to elevate their engineering practices.

In my case, the single-table wallet approach they advocated would have created numerous problems in production:

Data integrity issues: Without proper transaction tracking, reconciling account balances becomes nearly impossible when (not if) bugs or system failures occur.
Audit compliance nightmares: Financial regulations typically require immutable transaction logs, something difficult to achieve with a single mutable table.
Scalability limitations: As transaction volume grows, a single table becomes a bottleneck for both reads and writes.
Testing complexity: Without clear separation between transaction recording and balance calculation, unit testing becomes significantly more difficult.

But beyond the technical implications, there's a cultural cost. Teams that can't engage with different perspectives during interviews are likely making similar mistakes in their day-to-day engineering decisions. They're missing opportunities to learn from code reviews, dismissing valuable architectural suggestions from team members, and potentially making the same kinds of closed-minded decisions that led to technical debt.

Recognition Patterns

Having been on both sides of many technical interviews, I've learned to recognize the warning signs of competency gap situations:

Immediate dismissal: When your technical approach is dismissed without genuine exploration of the reasoning behind it.

Appeal to authority: Responses like "this is how we do it here" or "in my experience" without substantive technical justification.

Inability to engage with trade-offs: Good engineers understand that most technical decisions involve trade-offs. If interviewers can't discuss the downsides of their preferred approach, it suggests shallow understanding.

Defensive responses: When questions about their technical choices are met with defensiveness rather than explanation.

Lack of curiosity: The absence of follow-up questions about your reasoning or experience with alternative approaches.

Building Better Interview Cultures

The solution isn't to eliminate technical disagreement from interviews. It's to create environments where disagreement leads to productive exploration rather than dismissive rejection.

Strong engineering teams approach technical interviews as collaborative problem-solving sessions. They're genuinely curious about different approaches and willing to acknowledge when a candidate presents superior solutions. They ask questions like "what led you to this design decision?" and "what trade-offs did you consider?"

They also recognize that learning can flow in both directions. Some of my best interviews have ended with interviewers saying something like "that's an interesting approach—we hadn't considered that pattern before."

The Broader Implications

The competency gap problem extends beyond individual interview experiences. It reflects broader issues in how the tech industry evaluates and values expertise.

As our field becomes increasingly specialized, the gap between general programming knowledge and domain expertise continues to widen. A brilliant algorithms engineer might not understand the nuances of financial system design. An expert in distributed systems might struggle with the intricacies of healthcare data privacy. A frontend specialist might not grasp the complexities of real-time trading systems.

This specialization makes it even more important for interviewers to approach technical discussions with humility and curiosity. When evaluating candidates in domains outside their expertise, the focus should shift from "is this the approach we would use?" to "does this candidate demonstrate deep understanding of the problem space and sound technical judgment?"

Moving Forward

My fintech interview experience was frustrating, but it was also educational. It taught me to value teams that embrace intellectual humility over those that confuse confidence with competence. It showed me the importance of researching potential colleagues as thoroughly as they research me. And it reinforced my belief that the best engineering teams are those that can disagree constructively and learn from each other.

For candidates facing similar situations, remember that a poor interview experience often reveals more about the organization than it does about your abilities. Companies that can't recognize good engineering when they see it are probably making similar mistakes in their product development, architectural decisions, and team building.

For engineering leaders and interviewers, consider whether your interview process encourages diverse thinking or enforces conformity. Are you evaluating candidates' ability to contribute to your team's growth, or just their ability to validate your existing approaches?

The goal of technical interviews should be to identify engineers who can make your team better, not just engineers who think exactly like your current team. Sometimes, the candidate who challenges your assumptions is exactly the person you need to hire.

The competency gap in technical interviews is a systemic issue that affects both individual careers and industry innovation. By recognizing these patterns and working to address them, we can build more inclusive, effective, and continuously learning engineering cultures.