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Best Interview Evaluation Methods for Technical Roles
Updated: Fri, Mar 14, 2025
Adejoke (JK) Adekunle
Hiring the right technical talent is no small feat. It's not just about testing a candidate's ability to write a few lines of code—it’s about evaluating their real-world problem-solving skills, collaboration potential, and adaptability. Yet, many companies still rely on outdated coding tests that fail to capture a candidate's true capabilities.
So, how do you move beyond traditional assessments and ensure you’re hiring the best fit for your team? In this article, we’ll explore the most effective interview evaluation methods for technical roles, including ways to reduce bias, balance technical and soft skills, and deliver feedback that enhances your employer brand.
Moving Beyond Code Tests: Evaluating Real-World Problem-Solving Ability
Why Code Tests Alone Aren’t Enough
Many companies rely on algorithm-based coding assessments as the primary method of evaluating technical candidates. While these tests measure problem-solving skills and familiarity with data structures, they often fail to capture a candidate’s ability to work on real-world projects.
In a real engineering environment, software developers don’t just write isolated code snippets. They debug legacy systems, refactor inefficient code, collaborate with teams, and make architectural trade-offs based on time, performance, and business constraints. A developer who excels in LeetCode-style challenges might struggle when faced with integrating APIs, troubleshooting production issues, or working within a complex codebase.
To get a more holistic understanding of a candidate’s technical capabilities, hiring managers should incorporate alternative evaluation methods that better reflect day-to-day work in a software engineering role.
Alternatives to Traditional Code Tests
1. Project-Based Assessments
A project-based assessment is one of the most effective ways to evaluate a candidate’s real-world problem-solving skills. Instead of solving abstract algorithmic problems, candidates work on a task that closely resembles the responsibilities they’d have in the role.
Why It Works:
- Replicates real job scenarios – Candidates must navigate real challenges such as debugging, scalability, and maintainability.
- Tests end-to-end development skills – From planning to execution, candidates showcase their ability to write clean, structured, and efficient code.
- Highlights practical decision-making – Developers must weigh trade-offs, such as performance vs. readability or speed vs. security.
How to Implement It:
- Provide a small, time-boxed project that mirrors an actual task from your company.
- Give candidates the flexibility to complete it asynchronously within a set timeframe (e.g., 48–72 hours).
- Assess code quality, structure, and problem-solving approach rather than just whether the code “works.”
Example: If you’re hiring a backend developer, instead of a generic algorithm test, give them a small task like building a REST API that interacts with a database. This will allow you to assess how they structure their code, handle errors, and optimize performance.
2. Pair Programming Sessions
Pair programming is a live coding exercise where the candidate works with an interviewer on a technical task in real time. This method not only tests coding ability but also evaluates communication, collaboration, and problem-solving under pressure.
Why It Works:
- Simulates real-world teamwork – Engineers rarely work alone; this format tests how well a candidate can think aloud, ask clarifying questions, and take feedback.
- Assesses debugging and thought process – Watching a candidate debug code in real time provides insight into how they approach troubleshooting.
- Tests adaptability – Candidates may encounter unexpected challenges, revealing how they respond to ambiguity and changes in requirements.
How to Implement It:
- Choose a realistic and open-ended problem instead of a rigid coding challenge.
- Assign an experienced developer from your team to act as the “partner” in the session.
- Focus on collaboration and communication rather than expecting a perfect solution.
Example: A frontend developer candidate might be asked to fix a bug in an existing React component. This will allow the interviewer to observe how they read unfamiliar code, diagnose issues, and interact with a team member to clarify requirements.
3. Take-Home Assignments
Take-home assignments offer a structured but flexible way to evaluate candidates by allowing them to complete a technical task in their own time. Unlike live coding exercises, these assignments remove the stress of time constraints and help assess deeper thinking and creativity.
Why It Works:
- Reduces interview pressure – Candidates can work at their own pace, leading to a more thoughtful approach.
- Provides a more realistic coding environment – Developers can use their preferred tools, frameworks, and research solutions, just as they would in a real job.
- Allows for thorough code review – Hiring teams can evaluate code quality, documentation, and design decisions in depth.
How to Implement It:
- Define a clear, well-scoped problem that aligns with the role.
- Keep it reasonable in length (shouldn’t take more than 3–5 hours).
- Provide detailed evaluation criteria (e.g., code structure, logic, efficiency, documentation).
Example: For a data engineer role, instead of an algorithmic challenge, assign a take-home task where the candidate processes and cleans a dataset, writes queries to extract insights, and documents their approach. This provides insight into their ability to handle messy data, optimize queries, and write maintainable code.
The Problem with Unstructured Technical Interviews
Bias in technical hiring often stems from unstructured interviews and subjective evaluations. When interviewers rely on gut feelings rather than defined criteria, assessments become inconsistent and prone to unconscious bias.
Common issues with unstructured technical interviews include:
❌ Halo/Horn Effect – A strong first impression (positive or negative) influences the entire evaluation.
❌ Similarity Bias – Interviewers favor candidates with similar backgrounds, education, or interests.
❌ Vague Evaluation Criteria – Different interviewers assess the same candidate differently, leading to unfair hiring decisions.
To ensure a fair, objective, and data-driven hiring process, companies must implement structured feedback mechanisms that minimize bias and provide clear, actionable insights.
How to Introduce Structured Feedback
1. Standardized Scorecards
One of the best ways to ensure fairness in technical assessments is by using predefined rubrics or scorecards. These provide clear evaluation criteria and help interviewers focus on measurable skills rather than subjective impressions.
Why It Works:
- Ensures every candidate is assessed using the same criteria.
- Helps quantify strengths and weaknesses instead of relying on vague impressions.
- Creates a data-backed record of decisions, reducing the influence of personal bias.
How to Implement It:
- Define key evaluation categories (e.g., problem-solving, code quality, communication, collaboration).
- Assign numerical scores or descriptive ratings to each category.
- Use the same template across all interviews to maintain consistency.
Tools That Help:
- TBH – Offers built-in, customizable scorecard templates for technical interviews.
- Greenhouse & Lever – ATS platforms with structured feedback options.
- CodeSignal & HackerRank – Provide detailed evaluation rubrics for coding challenges.
Example: A backend developer interview might include a scorecard with these criteria:
- Algorithmic Problem-Solving (0-5)
- Code Readability & Structure (0-5)
- Debugging & Optimization (0-5)
- Communication & Collaboration (0-5)
Interviewers assign scores based on predefined expectations, ensuring fairness across all candidates.
2. Blind Reviews for Coding Assessments
Bias can creep into assessments when reviewers subconsciously judge candidates based on names, gender, nationality, or educational background. A simple yet effective way to reduce bias is by implementing blind code reviews—where personal identifiers are removed before evaluation.
Why It Works:
- Focuses entirely on technical ability rather than background.
- Reduces unconscious bias related to gender, ethnicity, or educational pedigree.
- Ensures assessments are merit-based rather than influenced by assumptions.
How to Implement It:
- Use code submission platforms that anonymize candidate identities.
- Assign unique identifiers instead of names.
- Reviewers assess purely based on code quality, efficiency, and correctness.
Tools That Help:
- Codility & CoderPad – Offer anonymized code assessments.
- HackerRank – Provides structured review features with anonymous grading.
Example: Instead of evaluating “John Doe’s code,” interviewers see “Candidate #253”, ensuring that judgments are made solely on the technical solution.
3. Multiple Evaluators for Fairer Assessments
A single interviewer’s bias—whether conscious or unconscious—can significantly affect a hiring decision. Using multiple reviewers helps balance out individual perspectives and ensures a more objective evaluation.
Why It Works:
- Reduces subjective opinions by introducing diverse perspectives.
- Improves hiring accuracy by incorporating feedback from multiple evaluators.
- Encourages structured decision-making rather than over-reliance on personal opinions.
How to Implement It:
- Require at least two or three reviewers per technical assessment.
- Use a blind calibration process where reviewers assess independently before discussing.
- Conduct a structured debrief to compare scores and resolve discrepancies.
Tools That Help:
- Greenhouse – Allows multiple interviewers to submit structured feedback before a final decision.
- Lever – Offers collaborative scorecards to capture multiple viewpoints.
- TBH – Supports multi-reviewer workflows to ensure fairer evaluations.
Example: After a technical assessment, three evaluators independently review and score the candidate. If one gives a significantly lower or higher score, a review panel discussion is held to align expectations and ensure a fair decision.
Balancing Technical Skills vs. Team Collaboration Potential
Hiring a software engineer based solely on technical skills can be a mistake. While coding ability is essential, software development is inherently a collaborative process—requiring engineers to communicate ideas, work within a team, and align with business goals.
A highly skilled but uncooperative engineer can slow down projects, create friction, and reduce team efficiency. On the other hand, a strong team player who learns quickly can often outperform a technically superior but uncooperative counterpart.
To build high-performing engineering teams, hiring managers must evaluate both technical expertise and collaborative potential.
Key Non-Technical Skills to Assess
Beyond coding ability, successful engineers need soft skills that enable them to work effectively in a team. Some of the most critical skills include:
✅ Communication – Can they explain their thought process clearly?
- Articulating complex ideas in simple terms.
- Asking insightful questions to clarify requirements.
- Actively listening and responding thoughtfully.
✅ Adaptability – How well do they handle new challenges?
- Learning new technologies quickly.
- Adjusting to project scope changes.
- Thriving in fast-paced or ambiguous environments.
✅ Problem-Solving Approach – Do they consider long-term scalability and maintainability?
- Thinking beyond just passing test cases.
- Writing clean, maintainable code.
- Making trade-offs between speed, performance, and business needs.
Assessing these skills ensures that new hires not only write good code but also fit well within the team dynamic.
Interview Techniques for Assessing Collaboration
To effectively evaluate collaboration potential, companies should go beyond standard coding tests and introduce behavioral and situational assessments.
1. Behavioral Interviews – Understanding Past Teamwork Experiences
The best predictor of future behavior is past behavior. Behavioral interview questions help assess how candidates have worked in teams before.
Key Questions to Ask:
- “Tell me about a time you disagreed with a teammate. How did you handle it?”
- “Describe a situation where you had to explain a complex technical concept to a non-technical person.”
- “Give an example of a time when you had to adapt to a major project change. How did you manage it?”
What to Look For:
- Clear and structured responses.
- Willingness to accept feedback and resolve conflicts professionally.
- Evidence of teamwork, adaptability, and communication skills.
Tools That Help:
- Karat & HireVue – AI-powered behavioral interview platforms that assess communication and collaboration.
- Greenhouse – Provides structured behavioral interview templates for fair assessment.
2. Live Code Reviews – Observing How They Handle Feedback
Instead of just evaluating what candidates code, assess how they respond to feedback in a live code review session.
How It Works:
- Have the candidate walk through their code and explain design decisions.
- Ask why they chose a particular approach and what trade-offs they considered.
- Provide constructive feedback and observe their reaction.
What to Look For:
- Do they defend their decisions thoughtfully or become defensive?
- Are they open to suggestions and eager to learn?
- Can they explain their code clearly to others?
Tools That Help:
- GitHub PR Reviews & CodeSignal – Simulate real-world code reviews.
- CoderPad & Coderbyte – Enable collaborative coding with live feedback.
Example Scenario: A candidate submits a coding assignment. Instead of grading it privately, the interviewer conducts a live review, asking questions like:
- “How would you improve this function for scalability?”
- “What edge cases did you consider?”
- “Would this code be easy for another engineer to maintain?”
The goal is to evaluate mindset, flexibility, and ability to collaborate—not just technical correctness.
3. Situational Role-Playing – Evaluating Conflict Resolution Skills
Software engineers don’t just write code—they navigate team dynamics, conflicting priorities, and occasional disagreements. A great way to assess collaboration is through situational role-playing.
How It Works:
- Present a realistic team conflict scenario and ask the candidate how they would respond.
- Role-play a situation where a stakeholder requests last-minute changes to a project.
- Observe their ability to negotiate, compromise, and communicate effectively.
What to Look For:
- Ability to stay calm and professional under pressure.
- Clear logical reasoning in conflict resolution.
- Willingness to find common ground instead of escalating conflicts.
Tools That Help:
- Mursion & Pymetrics – Use AI-driven role-playing simulations for soft skill evaluation.
Example Scenario: An interviewer might say: “Imagine you’re leading a project, and a teammate keeps missing deadlines. How would you handle this situation?”
The candidate’s response reveals their leadership, empathy, and conflict-resolution approach.
Why Technical Candidates Demand Faster Feedback Than Other Roles
Technical hiring moves at lightning speed. The best software engineers, data scientists, and developers often receive multiple job offers within days, and if your hiring process is slow, you risk losing top candidates to competitors.
Unlike other roles, technical hiring is heavily demand-driven. Companies compete aggressively for the same talent pool, meaning that delayed feedback can cost you a great hire.
Common Issues with Slow Feedback in Technical Hiring:
- Candidates lose interest or accept other offers.
- The employer brand suffers—no one wants to work for a company that takes too long to respond.
- Recruitment teams waste resources re-interviewing or searching for new candidates.
Solution? Faster, more structured feedback processes.
How to Speed Up the Feedback Process
1. Automated Evaluation Tools – Instant Technical Assessments
Technical hiring often involves coding tests, system design challenges, and algorithm assessments. Instead of waiting for manual review, companies can use AI-driven coding platforms to evaluate candidates instantly.
Recommended Tools:
- HackerRank & CodeSignal – Auto-score coding tests based on accuracy, efficiency, and edge case handling.
- Codility & CoderPad – Real-time coding interview platforms with automated grading.
- TBH – Uses AI to collect, analyze, and summarize structured interview feedback.
Why It Works:
- Immediate scoring means no delays in moving candidates forward.
- Standardized evaluation ensures fairness.
- Interviewers get real-time data to discuss during debriefs.
2. Structured Post-Interview Debriefs – Fast Decision-Making
One of the biggest bottlenecks in hiring is interviewers taking days (or weeks!) to submit feedback. A structured post-interview debrief ensures decisions are made quickly and collaboratively.
Best Practices for Faster Debriefs:
- Hold a 10-15 minute sync after each interview round.
- Require immediate feedback submission (no more “I’ll send it later”).
- Use structured scorecards to align decision-making.
How TBH Helps:
- Pre-built scorecards make feedback submission effortless.
- Voice-to-text feedback allows interviewers to speak their thoughts instead of typing.
- Instant hire/no-hire recommendations summarize input from all reviewers.
With this, hiring teams make decisions on the spot, reducing turnaround time dramatically.
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