Asif | Blog, Resume, Community

Traditional coding interviews fail to predict job performance. Here's how we redesigned our interview process to assess real engineering skills.

The Problem with Coding Interviews LeetCode-style problems test algorithm knowledge—not day-to-day engineering skills. We don't reverse binary trees in production. We review code, debug systems, collaborate with teams. Studies show: algorithm interviews correlate poorly with job performance. They favor candidates who grind LeetCode, not necessarily strong engineers. Worse: these interviews exclude great candidates who don't have time to practice algorithms (career switchers, parents, people with jobs).

Our Interview Process Stage 1: Resume screen (15 minutes) Look for: impact stories (reduced latency by 40%), open source contributions, clear communication.

Stage 2: Initial phone screen (30 minutes) Behavioral questions about past work, technical discussion about their projects (not algorithms). If they built X, how did they make technical decisions?

Stage 3: Take-home project (3-4 hours, optional) Build a small real-world feature: "Add REST API endpoint to this service with tests." Use their preferred language/stack. Give candidates 1 week to complete. Respect their time—no marathon projects. Alternative: Work sample from their past work (with permission).

Stage 4: On-site (4 hours) - System design (1 hour): Design a real system like our product. Assess architecture thinking. - Code review (1 hour): Review their take-home code together. Discuss trade-offs, improvements. - Pair programming (1 hour): Extend their take-home project together. Assess collaboration. - Behavioral/values (1 hour): Culture fit, past challenges, leadership examples.

What We Assess Technical skills: Can they build production-quality code? Understand trade-offs? Debug effectively? Communication: Can they explain technical concepts? Ask clarifying questions? Give constructive feedback? Collaboration: Do they listen to ideas? Incorporate feedback? Work well with others? Values fit: Do they value quality? User impact? Continuous learning? Team success over individual glory?

Red Flags - Arrogant "I'm the smartest person here" attitude - Can't explain technical decisions ("I don't know, that's just how I did it") - Blames others for past failures - Doesn't ask questions about the role or team - Treats non-technical interviewers poorly

Candidate Experience Respect candidates' time. No surprise problem statements. Clear expectations at each stage. Give feedback to all candidates. Even rejections: "Strong system design, but code quality below our bar. Work on X and reapply." Pay for take-homes. Candidates invest hours—compensate at $100/hour. Move fast. Slow processes lose great candidates. Complete process in 2 weeks max.

Results

After changing our process: - Offer acceptance rate increased from 60% to 85% (candidates love the process) - 6-month retention improved by 20% (better fit assessment) - Diversity increased (removed algorithm bias) - Engineers report: "This was the best interview experience I've had"

For Candidates: How to Prepare Study the company's tech stack and product. Read their engineering blog. Prepare questions about their architecture, culture, challenges. Review fundamentals: data structures, REST APIs, SQL, debugging strategies. Not algorithms. Prepare stories using STAR method (Situation, Task, Action, Result): "We had X problem, I did Y, resulting in Z impact." Ask about: team structure, on-call expectations, deployment frequency, tech debt management. Good interviews are two-way conversations. We're assessing you; you're assessing us. Both should leave informed to make a good decision.