# How to Hire Developers in the Age of AI

Stack Overflow recruiter explains why soft skills now outweigh technical coding tests.

- **Source:** [Stack Overflow Blog](https://brifing.si/source/11890bf5-d92c-4d67-ac83-335ff1a11a3f)
- **Published:** 2026-11-12
- **Topic:** [careers](https://brifing.si/c/careers)
- **Original article:** <https://stackoverflow.blog/2026/11/12/how-do-you-hire-a-human-q-and-a-with-tom-harvey-stack-overflow-technical-recruiter/>
- **On Brifing:** https://brifing.si/s/549d9f95-fae8-4aad-9809-2bf11a4b0627

## The New Hiring Reality

The landscape for hiring developers has shifted significantly due to widespread AI adoption. Both recruiters and candidates now operate in an antagonistic environment, utilizing AI tools to either generate applications or screen them. This digital arms race has fundamentally altered the traditional recruitment process, making human-centric evaluation more challenging than ever before.

## Defining Role Requirements

Before posting a job, recruiters must collaborate closely with hiring managers to identify essential traits beyond technical skills. At companies like Stack Overflow, the focus is shifting toward a candidate's ability to explain their work, navigate team dynamics, and demonstrate coachability. These qualitative markers are now prioritized over rigid language proficiency.

## Shifting Engineering Priorities

Modern software engineering roles are evolving away from pure code production. Engineers are increasingly expected to participate in strategic discussions and project direction. Recruiters now seek candidates who are willing to learn these collaborative skills, as technical tasks are often handed off or automated, changing the core definition of developer success.

## Obsolescence of Technical Tests

Traditional quantitative assessments, such as LeetCode challenges, have become largely irrelevant in the age of LLMs. Because AI can easily solve these problems, they no longer accurately measure a candidate's true capability. Instead, some companies are experimenting with debugging AI-generated code to better evaluate practical, real-world technical problem-solving skills.

## The Resume Inflation Crisis

A major irony in modern recruiting is that every candidate now appears exceptionally qualified on paper. Resumes often fail to provide a reliable picture of actual experience, as AI tools help applicants polish their profiles to perfection. This makes it difficult for recruiters to distinguish between genuine talent and inflated credentials.

## Valuing Qualitative Experience

Recruiters are moving toward seeking qualitative insights rather than just years of service at specific companies. They want to hear stories about specific production failures, complex bugs, and the lessons learned from those events. These narratives provide a more reliable and engaging indicator of a developer's growth and professional maturity.

## The Human Screening Preference

Despite the volume of applications, many recruiters remain wary of automated AI screening tools. They prioritize a personal connection, aiming to engage with candidates who are genuinely excited and informed. The goal is to build a narrative arc that leads to a meaningful conversation, rather than relying on cold, algorithmic filtering.

## Limitations of Tracking Systems

Most Applicant Tracking Systems remain optimized for basic keyword filtering and location matching. While some include fraud detection, these tools often foster an atmosphere of distrust between recruiters and applicants. This adversarial start to the hiring process can negatively impact the candidate experience and hinder the discovery of true talent.

## Evolving Recruiter Technicality

The role of the technical recruiter has changed rapidly over the last six months. Recruiters are now expected to possess deeper technical knowledge to discuss team workflows and business strategy. They must understand the company's six-month trajectory to effectively assess if a candidate is a genuine long-term fit for the team.

## The AI Answer Paradox

Candidates often use AI to provide perfect, immediate answers to technical screening questions. This creates a challenge for recruiters, as they need to distinguish between authentic thought and AI-generated responses. Recruiters must now ask more open-ended, weightier questions that require reflection, rather than accepting polished, instant replies that lack depth.

## Accepting Imperfect Responses

In this new environment, recruiters are learning to value flaws in candidate responses. Because AI provides perfect answers, a candidate who takes time to think or shows vulnerability can actually be more impressive. Both parties must be willing to embrace imperfection to foster a more honest and effective interview dialogue.

## Future of Talent Acquisition

The future of hiring lies in moving past the superficial perfection enabled by AI. Success will depend on the ability to conduct deep, qualitative explorations of a candidate's history and potential. As technical barriers lower, the ability to communicate, collaborate, and learn will remain the most critical, irreplaceable human assets.

## Sources covering this story

- https://stackoverflow.blog/2026/11/12/how-do-you-hire-a-human-q-and-a-with-tom-harvey-stack-overflow-technical-recruiter/ — 

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_Summary written by Brifing from the original reporting. Copyright in the original article belongs to its publisher; read the full piece at the link above._
