Why Your Tech Hiring Process Optimises for Interviews, Not Performance.

Let’s be honest: most tech hiring processes are built to produce a feeling.

A feeling that we were thorough. A feeling that we “tested for fit”. A feeling that the person who spoke well will also ship well.

But production doesn’t care how someone interviews. Your platform won’t stay up because someone nailed a STAR story. Your roadmap doesn’t move because someone was charismatic for 45 minutes.

Most hiring processes don’t optimise for performance. They optimise for interview performance. And in tech, that’s expensive.

The uncomfortable truth: interviews reward the wrong skills (in isolation)

Interviews (especially unstructured ones) tend to reward:

• confidence over clarity
• pattern-matching over problem-solving
• storytelling over ownership
• polish over delivery
  

Research in personnel selection has been pointing at this for decades: different selection methods predict performance with very different levels of validity, and the strongest outcomes come from combining methods that actually sample the work (e.g., structured interviews + work samples / cognitive measures), rather than relying on “good conversations.” 

Even structured interviews (the better version) can vary significantly in validity depending on how they’re designed and executed. Meaning “we do structured interviews” isn’t a magic spell. 

So if your hiring process is mostly:

1. CV screen
2. Chat with recruiter
3. Chat with hiring manager
4. Panel interview
5. “Culture” interview

…you may be running a confidence tournament, not a performance assessment.

Welcome to “Hiring Theatre”

Hiring theatre looks professional. It’s full of ceremonies:

• the panel
• the case study with no context
• the “culture add” chat that’s actually vibe-matching
• the technical interview that tests trivia instead of judgement
• the feedback loop that turns into subjective negotiation

The output of hiring theatre is not “best engineer.”
It’s “person who performed best in our theatre.”



Technology work is rarely performed like an interview. It’s performed in ambiguity, in collaboration, under constraints, across systems, with trade-offs.

The real question you should ask

Instead of “Would I grab a beer with this person?” or “Did they answer quickly?”

Ask this:

“Does our process measure how they’ll behave in our environment, on our work, with our constraints?”

If the answer is “not really”, you’re not alone. You’re just paying the same hidden tax most teams pay:



• slow ramp-up
• churn disguised as “not the right fit”
• strong talkers who don’t deliver
• quiet high-performers you screened out too early
  

What high-performing tech teams do differently

They don’t make hiring harder. They make it more honest.

They build selection around performance proxies - signals that resemble the work:

• problem framing
• decision making under constraints
• collaboration and trade-offs
• code quality and review habits
• ownership mindset
• systems thinking appropriate to level

And they treat interviews as one component, not the whole product.



The selection research consistently supports the idea that combining methods improves predictive validity. For example, structured interviews paired with other job-relevant measures.

The MAYDAY “Performance Stack” (a better hiring design)

Here’s a clean, tech-aligned approach we see work without turning hiring into a six week marathon.

1) Work sample that mirrors reality

Not a “build Twitter in 2 hours” stunt.

A good work sample looks like your actual work:

• debugging a real-ish issue
• reviewing a PR and explaining trade-offs
• designing a small component with constraints
• prioritising a backlog slice with risks and dependencies

This is where you reduce “theatre” and increase signal. Selection research recognises the value of methods that are closer to the work itself (work samples consistently show strong predictive validity in classic meta-analytic findings). 

2) Structured interview focused on judgement

Structured doesn’t mean robotic. It means:

• consistent questions
• anchored scoring
• clarity on what “good” looks like



The research shows structured interviews can be strong predictors — but outcomes vary depending on the quality of the structure. Translation: structure with intent, not as a checkbox.

3) Calibration interview (team reality)

This is where you test:

• how they collaborate
• how they communicate uncertainty
• how they challenge respectfully
• how they take feedback



But keep it real: make it about working together, not performing “culture.”

4) References as verification, not validation

References shouldn’t be “they were great.” That’s noise.
They should confirm patterns you already observed:



• ownership
• delivery under pressure
• collaboration style
• reliability
• growth trajectory
  

The “Interview Smells” checklist (edgy, but fair)

If you spot these, you’re probably hiring for interview performance:

• You reward speed of answers more than quality of thinking
• You treat confidence as competence
• You ask “tell me about a time…” more than “show me how you work”
• You don’t define what good looks like at each level
• Interviewers aren’t calibrated (everyone scores differently)
• Candidates leave with no clear picture of success in the role
• The process filters out quieter talent early
• You optimise for consensus, not accuracy



None of this is a moral failing. It’s a design problem.

What this looks like in practice

High-performing hiring is:

• clear about the work
• consistent in how it evaluates
• kind in how it runs
• honest about constraints
• accountable for outcomes



That’s the intersection MAYDAY Technology sits in: people, platforms and long-term delivery.

A simple reset you can run this week

If you want one move that creates immediate impact:

Audit your process against the job.
List the top 5 things success requires in the first 90 days, then map where (if anywhere) your hiring process actually tests those things.



If you can’t map it, it’s not measured.
If it’s not measured, you’re guessing.
If you’re guessing, you’re paying for it later.